The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your -projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions -specific to their job function.
-With Deadline Cloud, content production teams can deploy resources for their workforce -securely in the cloud, reducing the costs of added physical infrastructure. Keep your -content production operations secure, while allowing your contributors to access the tools -they need, such as scalable high-speed storage, licenses, and cost management -services.
+The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions specific to their job function.
With Deadline Cloud, content production teams can deploy resources for their workforce securely in the cloud, reducing the costs of added physical infrastructure. Keep your content production operations secure, while allowing your contributors to access the tools they need, such as scalable high-speed storage, licenses, and cost management services.
## Installing diff --git a/clients/client-deadline/package.json b/clients/client-deadline/package.json index 057451715609..51ca4c2d7bd3 100644 --- a/clients/client-deadline/package.json +++ b/clients/client-deadline/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-deadline", "description": "AWS SDK for JavaScript Deadline Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-deadline/src/Deadline.ts b/clients/client-deadline/src/Deadline.ts index 50f6eb176122..87c6d0413864 100644 --- a/clients/client-deadline/src/Deadline.ts +++ b/clients/client-deadline/src/Deadline.ts @@ -2120,14 +2120,7 @@ export interface Deadline { } /** - *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your - * projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions - * specific to their job function.
- *With Deadline Cloud, content production teams can deploy resources for their workforce - * securely in the cloud, reducing the costs of added physical infrastructure. Keep your - * content production operations secure, while allowing your contributors to access the tools - * they need, such as scalable high-speed storage, licenses, and cost management - * services.
+ *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions specific to their job function.
With Deadline Cloud, content production teams can deploy resources for their workforce securely in the cloud, reducing the costs of added physical infrastructure. Keep your content production operations secure, while allowing your contributors to access the tools they need, such as scalable high-speed storage, licenses, and cost management services.
* @public */ export class Deadline extends DeadlineClient implements Deadline {} diff --git a/clients/client-deadline/src/DeadlineClient.ts b/clients/client-deadline/src/DeadlineClient.ts index 344e3e1ef892..a715d8f13e61 100644 --- a/clients/client-deadline/src/DeadlineClient.ts +++ b/clients/client-deadline/src/DeadlineClient.ts @@ -745,14 +745,7 @@ export type DeadlineClientResolvedConfigType = __SmithyResolvedConfiguration<__H export interface DeadlineClientResolvedConfig extends DeadlineClientResolvedConfigType {} /** - *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your - * projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions - * specific to their job function.
- *With Deadline Cloud, content production teams can deploy resources for their workforce - * securely in the cloud, reducing the costs of added physical infrastructure. Keep your - * content production operations secure, while allowing your contributors to access the tools - * they need, such as scalable high-speed storage, licenses, and cost management - * services.
+ *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions specific to their job function.
With Deadline Cloud, content production teams can deploy resources for their workforce securely in the cloud, reducing the costs of added physical infrastructure. Keep your content production operations secure, while allowing your contributors to access the tools they need, such as scalable high-speed storage, licenses, and cost management services.
* @public */ export class DeadlineClient extends __Client< diff --git a/clients/client-deadline/src/commands/AssociateMemberToFarmCommand.ts b/clients/client-deadline/src/commands/AssociateMemberToFarmCommand.ts index b47685a9fd45..9f680b4af5af 100644 --- a/clients/client-deadline/src/commands/AssociateMemberToFarmCommand.ts +++ b/clients/client-deadline/src/commands/AssociateMemberToFarmCommand.ts @@ -64,15 +64,13 @@ export interface AssociateMemberToFarmCommandOutput extends AssociateMemberToFar *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssociateMemberToFleetCommand.ts b/clients/client-deadline/src/commands/AssociateMemberToFleetCommand.ts index 31196ef60cf8..c3f717965bc1 100644 --- a/clients/client-deadline/src/commands/AssociateMemberToFleetCommand.ts +++ b/clients/client-deadline/src/commands/AssociateMemberToFleetCommand.ts @@ -65,15 +65,13 @@ export interface AssociateMemberToFleetCommandOutput extends AssociateMemberToFl *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssociateMemberToJobCommand.ts b/clients/client-deadline/src/commands/AssociateMemberToJobCommand.ts index 6ea6babdf19e..d095eb1cb1f2 100644 --- a/clients/client-deadline/src/commands/AssociateMemberToJobCommand.ts +++ b/clients/client-deadline/src/commands/AssociateMemberToJobCommand.ts @@ -66,15 +66,13 @@ export interface AssociateMemberToJobCommandOutput extends AssociateMemberToJobR *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssociateMemberToQueueCommand.ts b/clients/client-deadline/src/commands/AssociateMemberToQueueCommand.ts index 4f14fc43d66f..1e7602f724f0 100644 --- a/clients/client-deadline/src/commands/AssociateMemberToQueueCommand.ts +++ b/clients/client-deadline/src/commands/AssociateMemberToQueueCommand.ts @@ -65,15 +65,13 @@ export interface AssociateMemberToQueueCommandOutput extends AssociateMemberToQu *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssumeFleetRoleForReadCommand.ts b/clients/client-deadline/src/commands/AssumeFleetRoleForReadCommand.ts index ccac82961c46..ac62ff1d3f3a 100644 --- a/clients/client-deadline/src/commands/AssumeFleetRoleForReadCommand.ts +++ b/clients/client-deadline/src/commands/AssumeFleetRoleForReadCommand.ts @@ -32,8 +32,7 @@ export interface AssumeFleetRoleForReadCommandInput extends AssumeFleetRoleForRe export interface AssumeFleetRoleForReadCommandOutput extends AssumeFleetRoleForReadResponse, __MetadataBearer {} /** - *Get Amazon Web Services credentials from the fleet role. The IAM permissions of the credentials are - * scoped down to have read-only access.
+ *Get Amazon Web Services credentials from the fleet role. The IAM permissions of the credentials are scoped down to have read-only access.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -76,8 +75,7 @@ export interface AssumeFleetRoleForReadCommandOutput extends AssumeFleetRoleForR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssumeFleetRoleForWorkerCommand.ts b/clients/client-deadline/src/commands/AssumeFleetRoleForWorkerCommand.ts index 5f8150f18665..ca450c1c14df 100644 --- a/clients/client-deadline/src/commands/AssumeFleetRoleForWorkerCommand.ts +++ b/clients/client-deadline/src/commands/AssumeFleetRoleForWorkerCommand.ts @@ -67,8 +67,7 @@ export interface AssumeFleetRoleForWorkerCommandOutput extends AssumeFleetRoleFo *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -80,8 +79,7 @@ export interface AssumeFleetRoleForWorkerCommandOutput extends AssumeFleetRoleFo *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssumeQueueRoleForReadCommand.ts b/clients/client-deadline/src/commands/AssumeQueueRoleForReadCommand.ts index 274aa27d565f..96093e9ad7fc 100644 --- a/clients/client-deadline/src/commands/AssumeQueueRoleForReadCommand.ts +++ b/clients/client-deadline/src/commands/AssumeQueueRoleForReadCommand.ts @@ -32,8 +32,7 @@ export interface AssumeQueueRoleForReadCommandInput extends AssumeQueueRoleForRe export interface AssumeQueueRoleForReadCommandOutput extends AssumeQueueRoleForReadResponse, __MetadataBearer {} /** - *Gets Amazon Web Services credentials from the queue role. The IAM permissions of the credentials are - * scoped down to have read-only access.
+ *Gets Amazon Web Services credentials from the queue role. The IAM permissions of the credentials are scoped down to have read-only access.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -76,8 +75,7 @@ export interface AssumeQueueRoleForReadCommandOutput extends AssumeQueueRoleForR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssumeQueueRoleForUserCommand.ts b/clients/client-deadline/src/commands/AssumeQueueRoleForUserCommand.ts index 57d40bae57eb..6f26c413b269 100644 --- a/clients/client-deadline/src/commands/AssumeQueueRoleForUserCommand.ts +++ b/clients/client-deadline/src/commands/AssumeQueueRoleForUserCommand.ts @@ -75,8 +75,7 @@ export interface AssumeQueueRoleForUserCommandOutput extends AssumeQueueRoleForU *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/AssumeQueueRoleForWorkerCommand.ts b/clients/client-deadline/src/commands/AssumeQueueRoleForWorkerCommand.ts index 7bc566a16281..9ab4bdbaac4f 100644 --- a/clients/client-deadline/src/commands/AssumeQueueRoleForWorkerCommand.ts +++ b/clients/client-deadline/src/commands/AssumeQueueRoleForWorkerCommand.ts @@ -68,8 +68,7 @@ export interface AssumeQueueRoleForWorkerCommandOutput extends AssumeQueueRoleFo *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -81,8 +80,7 @@ export interface AssumeQueueRoleForWorkerCommandOutput extends AssumeQueueRoleFo *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/BatchGetJobEntityCommand.ts b/clients/client-deadline/src/commands/BatchGetJobEntityCommand.ts index a10477ce57f9..4063ec44c98b 100644 --- a/clients/client-deadline/src/commands/BatchGetJobEntityCommand.ts +++ b/clients/client-deadline/src/commands/BatchGetJobEntityCommand.ts @@ -187,8 +187,7 @@ export interface BatchGetJobEntityCommandOutput extends BatchGetJobEntityRespons *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CopyJobTemplateCommand.ts b/clients/client-deadline/src/commands/CopyJobTemplateCommand.ts index 0511bd2f1d60..1230fb9ff430 100644 --- a/clients/client-deadline/src/commands/CopyJobTemplateCommand.ts +++ b/clients/client-deadline/src/commands/CopyJobTemplateCommand.ts @@ -71,8 +71,7 @@ export interface CopyJobTemplateCommandOutput extends CopyJobTemplateResponse, _ *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateBudgetCommand.ts b/clients/client-deadline/src/commands/CreateBudgetCommand.ts index 79bdbf518462..cad34715c112 100644 --- a/clients/client-deadline/src/commands/CreateBudgetCommand.ts +++ b/clients/client-deadline/src/commands/CreateBudgetCommand.ts @@ -82,15 +82,13 @@ export interface CreateBudgetCommandOutput extends CreateBudgetResponse, __Metad *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateFarmCommand.ts b/clients/client-deadline/src/commands/CreateFarmCommand.ts index dad940605b3b..5582c0dbde01 100644 --- a/clients/client-deadline/src/commands/CreateFarmCommand.ts +++ b/clients/client-deadline/src/commands/CreateFarmCommand.ts @@ -28,10 +28,7 @@ export interface CreateFarmCommandInput extends CreateFarmRequest {} export interface CreateFarmCommandOutput extends CreateFarmResponse, __MetadataBearer {} /** - *Creates a farm to allow space for queues and fleets. Farms are the space where the - * components of your renders gather and are pieced together in the cloud. Farms contain - * budgets and allow you to enforce permissions. Deadline Cloud farms are a useful container for - * large projects.
+ *Creates a farm to allow space for queues and fleets. Farms are the space where the components of your renders gather and are pieced together in the cloud. Farms contain budgets and allow you to enforce permissions. Deadline Cloud farms are a useful container for large projects.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -71,15 +68,13 @@ export interface CreateFarmCommandOutput extends CreateFarmResponse, __MetadataB *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateFleetCommand.ts b/clients/client-deadline/src/commands/CreateFleetCommand.ts index 922254118d7b..3bf817d87eb5 100644 --- a/clients/client-deadline/src/commands/CreateFleetCommand.ts +++ b/clients/client-deadline/src/commands/CreateFleetCommand.ts @@ -28,9 +28,7 @@ export interface CreateFleetCommandInput extends CreateFleetRequest {} export interface CreateFleetCommandOutput extends CreateFleetResponse, __MetadataBearer {} /** - *Creates a fleet. Fleets gather information relating to compute, or capacity, for renders - * within your farms. You can choose to manage your own capacity or opt to have fleets fully - * managed by Deadline Cloud.
+ *Creates a fleet. Fleets gather information relating to compute, or capacity, for renders within your farms. You can choose to manage your own capacity or opt to have fleets fully managed by Deadline Cloud.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -148,6 +146,10 @@ export interface CreateFleetCommandOutput extends CreateFleetResponse, __Metadat * tags: { // Tags * "The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateJobCommand.ts b/clients/client-deadline/src/commands/CreateJobCommand.ts index 432ea3eaca4e..4d40bf4289fa 100644 --- a/clients/client-deadline/src/commands/CreateJobCommand.ts +++ b/clients/client-deadline/src/commands/CreateJobCommand.ts @@ -28,9 +28,7 @@ export interface CreateJobCommandInput extends CreateJobRequest {} export interface CreateJobCommandOutput extends CreateJobResponse, __MetadataBearer {} /** - *Creates a job. A job is a set of instructions that Deadline Cloud uses to schedule - * and run work on available workers. For more information, see Deadline Cloud - * jobs.
+ *Creates a job. A job is a set of instructions that Deadline Cloud uses to schedule and run work on available workers. For more information, see Deadline Cloud jobs.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -98,15 +96,13 @@ export interface CreateJobCommandOutput extends CreateJobResponse, __MetadataBea *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateLicenseEndpointCommand.ts b/clients/client-deadline/src/commands/CreateLicenseEndpointCommand.ts index 76dddfea9854..20f707e30ee8 100644 --- a/clients/client-deadline/src/commands/CreateLicenseEndpointCommand.ts +++ b/clients/client-deadline/src/commands/CreateLicenseEndpointCommand.ts @@ -28,8 +28,7 @@ export interface CreateLicenseEndpointCommandInput extends CreateLicenseEndpoint export interface CreateLicenseEndpointCommandOutput extends CreateLicenseEndpointResponse, __MetadataBearer {} /** - *Creates a license endpoint to integrate your various licensed software used for - * rendering on Deadline Cloud.
+ *Creates a license endpoint to integrate your various licensed software used for rendering on Deadline Cloud.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -67,22 +66,19 @@ export interface CreateLicenseEndpointCommandOutput extends CreateLicenseEndpoin *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateLimitCommand.ts b/clients/client-deadline/src/commands/CreateLimitCommand.ts index 80d76cac0127..374b4dd25f51 100644 --- a/clients/client-deadline/src/commands/CreateLimitCommand.ts +++ b/clients/client-deadline/src/commands/CreateLimitCommand.ts @@ -28,11 +28,7 @@ export interface CreateLimitCommandInput extends CreateLimitRequest {} export interface CreateLimitCommandOutput extends CreateLimitResponse, __MetadataBearer {} /** - *Creates a limit that manages the distribution of shared resources, such as floating - * licenses. A limit can throttle work assignments, help manage workloads, and track current - * usage. Before you use a limit, you must associate the limit with one or more queues.
- *You must add the amountRequirementName to a step in a job template to
- * declare the limit requirement.
Creates a limit that manages the distribution of shared resources, such as floating licenses. A limit can throttle work assignments, help manage workloads, and track current usage. Before you use a limit, you must associate the limit with one or more queues.
You must add the amountRequirementName to a step in a job template to declare the limit requirement.
The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateMonitorCommand.ts b/clients/client-deadline/src/commands/CreateMonitorCommand.ts index 8a1c86467284..e82b00bc0957 100644 --- a/clients/client-deadline/src/commands/CreateMonitorCommand.ts +++ b/clients/client-deadline/src/commands/CreateMonitorCommand.ts @@ -28,9 +28,7 @@ export interface CreateMonitorCommandInput extends CreateMonitorRequest {} export interface CreateMonitorCommandOutput extends CreateMonitorResponse, __MetadataBearer {} /** - *Creates an Amazon Web Services Deadline Cloud monitor that you can use to view your farms, queues, and - * fleets. After you submit a job, you can track the progress of the tasks and steps that make - * up the job, and then download the job's results.
+ *Creates an Amazon Web Services Deadline Cloud monitor that you can use to view your farms, queues, and fleets. After you submit a job, you can track the progress of the tasks and steps that make up the job, and then download the job's results.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -66,15 +64,13 @@ export interface CreateMonitorCommandOutput extends CreateMonitorResponse, __Met *Deadline Cloud can't process your request right now. Try again later.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateQueueCommand.ts b/clients/client-deadline/src/commands/CreateQueueCommand.ts index fae41e8d6276..1fe468387487 100644 --- a/clients/client-deadline/src/commands/CreateQueueCommand.ts +++ b/clients/client-deadline/src/commands/CreateQueueCommand.ts @@ -28,8 +28,7 @@ export interface CreateQueueCommandInput extends CreateQueueRequest {} export interface CreateQueueCommandOutput extends CreateQueueResponse, __MetadataBearer {} /** - *Creates a queue to coordinate the order in which jobs run on a farm. A queue can also - * specify where to pull resources and indicate where to output completed jobs.
+ *Creates a queue to coordinate the order in which jobs run on a farm. A queue can also specify where to pull resources and indicate where to output completed jobs.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -92,15 +91,13 @@ export interface CreateQueueCommandOutput extends CreateQueueResponse, __Metadat *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateQueueEnvironmentCommand.ts b/clients/client-deadline/src/commands/CreateQueueEnvironmentCommand.ts index 9b944c21130a..162e181a9177 100644 --- a/clients/client-deadline/src/commands/CreateQueueEnvironmentCommand.ts +++ b/clients/client-deadline/src/commands/CreateQueueEnvironmentCommand.ts @@ -71,15 +71,13 @@ export interface CreateQueueEnvironmentCommandOutput extends CreateQueueEnvironm *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateQueueFleetAssociationCommand.ts b/clients/client-deadline/src/commands/CreateQueueFleetAssociationCommand.ts index bd3c2cd634b0..0752238a0222 100644 --- a/clients/client-deadline/src/commands/CreateQueueFleetAssociationCommand.ts +++ b/clients/client-deadline/src/commands/CreateQueueFleetAssociationCommand.ts @@ -70,8 +70,7 @@ export interface CreateQueueFleetAssociationCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateQueueLimitAssociationCommand.ts b/clients/client-deadline/src/commands/CreateQueueLimitAssociationCommand.ts index b2849f44410c..9dd07d910343 100644 --- a/clients/client-deadline/src/commands/CreateQueueLimitAssociationCommand.ts +++ b/clients/client-deadline/src/commands/CreateQueueLimitAssociationCommand.ts @@ -33,10 +33,7 @@ export interface CreateQueueLimitAssociationCommandOutput __MetadataBearer {} /** - *Associates a limit with a particular queue. After the limit is associated, all workers
- * for jobs that specify the limit associated with the queue are subject to the limit. You
- * can't associate two limits with the same amountRequirementName to the same
- * queue.
Associates a limit with a particular queue. After the limit is associated, all workers for jobs that specify the limit associated with the queue are subject to the limit. You can't associate two limits with the same amountRequirementName to the same queue.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateStorageProfileCommand.ts b/clients/client-deadline/src/commands/CreateStorageProfileCommand.ts index bac391c237f1..3e4c9cdf57fd 100644 --- a/clients/client-deadline/src/commands/CreateStorageProfileCommand.ts +++ b/clients/client-deadline/src/commands/CreateStorageProfileCommand.ts @@ -32,8 +32,7 @@ export interface CreateStorageProfileCommandInput extends CreateStorageProfileRe export interface CreateStorageProfileCommandOutput extends CreateStorageProfileResponse, __MetadataBearer {} /** - *Creates a storage profile that specifies the operating system, file type, and file - * location of resources used on a farm.
+ *Creates a storage profile that specifies the operating system, file type, and file location of resources used on a farm.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -77,15 +76,13 @@ export interface CreateStorageProfileCommandOutput extends CreateStorageProfileR *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/CreateWorkerCommand.ts b/clients/client-deadline/src/commands/CreateWorkerCommand.ts index 82ae7140cce2..e358131c7595 100644 --- a/clients/client-deadline/src/commands/CreateWorkerCommand.ts +++ b/clients/client-deadline/src/commands/CreateWorkerCommand.ts @@ -28,10 +28,7 @@ export interface CreateWorkerCommandInput extends CreateWorkerRequest {} export interface CreateWorkerCommandOutput extends CreateWorkerResponse, __MetadataBearer {} /** - *Creates a worker. A worker tells your instance how much processing power (vCPU), and - * memory (GiB) you’ll need to assemble the digital assets held within a particular instance. - * You can specify certain instance types to use, or let the worker know which instances types - * to exclude.
+ *Creates a worker. A worker tells your instance how much processing power (vCPU), and memory (GiB) you’ll need to assemble the digital assets held within a particular instance. You can specify certain instance types to use, or let the worker know which instances types to exclude.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -88,8 +84,7 @@ export interface CreateWorkerCommandOutput extends CreateWorkerResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteBudgetCommand.ts b/clients/client-deadline/src/commands/DeleteBudgetCommand.ts index a8ecfd56bd4d..50f2405919cf 100644 --- a/clients/client-deadline/src/commands/DeleteBudgetCommand.ts +++ b/clients/client-deadline/src/commands/DeleteBudgetCommand.ts @@ -64,8 +64,7 @@ export interface DeleteBudgetCommandOutput extends DeleteBudgetResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteFarmCommand.ts b/clients/client-deadline/src/commands/DeleteFarmCommand.ts index 4333421cdf57..c66ff01e0d20 100644 --- a/clients/client-deadline/src/commands/DeleteFarmCommand.ts +++ b/clients/client-deadline/src/commands/DeleteFarmCommand.ts @@ -63,8 +63,7 @@ export interface DeleteFarmCommandOutput extends DeleteFarmResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteFleetCommand.ts b/clients/client-deadline/src/commands/DeleteFleetCommand.ts index 0f2f6adb3d4c..82caa1317301 100644 --- a/clients/client-deadline/src/commands/DeleteFleetCommand.ts +++ b/clients/client-deadline/src/commands/DeleteFleetCommand.ts @@ -56,8 +56,7 @@ export interface DeleteFleetCommandOutput extends DeleteFleetResponse, __Metadat *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -69,8 +68,7 @@ export interface DeleteFleetCommandOutput extends DeleteFleetResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteLicenseEndpointCommand.ts b/clients/client-deadline/src/commands/DeleteLicenseEndpointCommand.ts index 713ee424daf4..0f67dd0fc0d5 100644 --- a/clients/client-deadline/src/commands/DeleteLicenseEndpointCommand.ts +++ b/clients/client-deadline/src/commands/DeleteLicenseEndpointCommand.ts @@ -54,8 +54,7 @@ export interface DeleteLicenseEndpointCommandOutput extends DeleteLicenseEndpoin *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -67,8 +66,7 @@ export interface DeleteLicenseEndpointCommandOutput extends DeleteLicenseEndpoin *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteLimitCommand.ts b/clients/client-deadline/src/commands/DeleteLimitCommand.ts index 62abe170664e..c1c31fb5844b 100644 --- a/clients/client-deadline/src/commands/DeleteLimitCommand.ts +++ b/clients/client-deadline/src/commands/DeleteLimitCommand.ts @@ -28,9 +28,7 @@ export interface DeleteLimitCommandInput extends DeleteLimitRequest {} export interface DeleteLimitCommandOutput extends DeleteLimitResponse, __MetadataBearer {} /** - *Removes a limit from the specified farm. Before you delete a limit you must use the
- * DeleteQueueLimitAssociation operation to remove the association with any
- * queues.
Removes a limit from the specified farm. Before you delete a limit you must use the DeleteQueueLimitAssociation operation to remove the association with any queues.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteMeteredProductCommand.ts b/clients/client-deadline/src/commands/DeleteMeteredProductCommand.ts index 276f5336436d..e52f1b9235da 100644 --- a/clients/client-deadline/src/commands/DeleteMeteredProductCommand.ts +++ b/clients/client-deadline/src/commands/DeleteMeteredProductCommand.ts @@ -64,8 +64,7 @@ export interface DeleteMeteredProductCommandOutput extends DeleteMeteredProductR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteMonitorCommand.ts b/clients/client-deadline/src/commands/DeleteMonitorCommand.ts index 9c95abbd8d61..66274459bab2 100644 --- a/clients/client-deadline/src/commands/DeleteMonitorCommand.ts +++ b/clients/client-deadline/src/commands/DeleteMonitorCommand.ts @@ -28,8 +28,7 @@ export interface DeleteMonitorCommandInput extends DeleteMonitorRequest {} export interface DeleteMonitorCommandOutput extends DeleteMonitorResponse, __MetadataBearer {} /** - *Removes a Deadline Cloud monitor. After you delete a monitor, you can create a new one and - * attach farms to the monitor.
+ *Removes a Deadline Cloud monitor. After you delete a monitor, you can create a new one and attach farms to the monitor.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -64,8 +63,7 @@ export interface DeleteMonitorCommandOutput extends DeleteMonitorResponse, __Met *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteQueueCommand.ts b/clients/client-deadline/src/commands/DeleteQueueCommand.ts index 34fe0d281bd2..6370b094f9d7 100644 --- a/clients/client-deadline/src/commands/DeleteQueueCommand.ts +++ b/clients/client-deadline/src/commands/DeleteQueueCommand.ts @@ -28,11 +28,7 @@ export interface DeleteQueueCommandInput extends DeleteQueueRequest {} export interface DeleteQueueCommandOutput extends DeleteQueueResponse, __MetadataBearer {} /** - *Deletes a queue.
- *You can't recover the jobs in a queue if you delete the queue. Deleting the queue - * also deletes the jobs in that queue.
- *Deletes a queue.
You can't recover the jobs in a queue if you delete the queue. Deleting the queue also deletes the jobs in that queue.
You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -72,8 +67,7 @@ export interface DeleteQueueCommandOutput extends DeleteQueueResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteQueueEnvironmentCommand.ts b/clients/client-deadline/src/commands/DeleteQueueEnvironmentCommand.ts index 23c75d02c0fb..1874f129a9c9 100644 --- a/clients/client-deadline/src/commands/DeleteQueueEnvironmentCommand.ts +++ b/clients/client-deadline/src/commands/DeleteQueueEnvironmentCommand.ts @@ -62,8 +62,7 @@ export interface DeleteQueueEnvironmentCommandOutput extends DeleteQueueEnvironm *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteQueueFleetAssociationCommand.ts b/clients/client-deadline/src/commands/DeleteQueueFleetAssociationCommand.ts index a0a23145a72b..da7b1bf2927d 100644 --- a/clients/client-deadline/src/commands/DeleteQueueFleetAssociationCommand.ts +++ b/clients/client-deadline/src/commands/DeleteQueueFleetAssociationCommand.ts @@ -61,8 +61,7 @@ export interface DeleteQueueFleetAssociationCommandOutput *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -74,8 +73,7 @@ export interface DeleteQueueFleetAssociationCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteQueueLimitAssociationCommand.ts b/clients/client-deadline/src/commands/DeleteQueueLimitAssociationCommand.ts index 56c9461a6335..e2db0ea778b3 100644 --- a/clients/client-deadline/src/commands/DeleteQueueLimitAssociationCommand.ts +++ b/clients/client-deadline/src/commands/DeleteQueueLimitAssociationCommand.ts @@ -33,12 +33,7 @@ export interface DeleteQueueLimitAssociationCommandOutput __MetadataBearer {} /** - *Removes the association between a queue and a limit. You must use the
- * UpdateQueueLimitAssociation operation to set the status to
- * STOP_LIMIT_USAGE_AND_COMPLETE_TASKS or
- * STOP_LIMIT_USAGE_AND_CANCEL_TASKS. The status does not change immediately.
- * Use the GetQueueLimitAssociation operation to see if the status changed to
- * STOPPED before deleting the association.
Removes the association between a queue and a limit. You must use the UpdateQueueLimitAssociation operation to set the status to STOP_LIMIT_USAGE_AND_COMPLETE_TASKS or STOP_LIMIT_USAGE_AND_CANCEL_TASKS. The status does not change immediately. Use the GetQueueLimitAssociation operation to see if the status changed to STOPPED before deleting the association.
You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -79,8 +73,7 @@ export interface DeleteQueueLimitAssociationCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteStorageProfileCommand.ts b/clients/client-deadline/src/commands/DeleteStorageProfileCommand.ts index df69b09d5956..3f3b7f577cd5 100644 --- a/clients/client-deadline/src/commands/DeleteStorageProfileCommand.ts +++ b/clients/client-deadline/src/commands/DeleteStorageProfileCommand.ts @@ -61,8 +61,7 @@ export interface DeleteStorageProfileCommandOutput extends DeleteStorageProfileR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DeleteWorkerCommand.ts b/clients/client-deadline/src/commands/DeleteWorkerCommand.ts index 3f1772d86783..8b0dfe95408a 100644 --- a/clients/client-deadline/src/commands/DeleteWorkerCommand.ts +++ b/clients/client-deadline/src/commands/DeleteWorkerCommand.ts @@ -56,8 +56,7 @@ export interface DeleteWorkerCommandOutput extends DeleteWorkerResponse, __Metad *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -69,8 +68,7 @@ export interface DeleteWorkerCommandOutput extends DeleteWorkerResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DisassociateMemberFromFarmCommand.ts b/clients/client-deadline/src/commands/DisassociateMemberFromFarmCommand.ts index a03e8063bc45..ac46656eb7d7 100644 --- a/clients/client-deadline/src/commands/DisassociateMemberFromFarmCommand.ts +++ b/clients/client-deadline/src/commands/DisassociateMemberFromFarmCommand.ts @@ -64,8 +64,7 @@ export interface DisassociateMemberFromFarmCommandOutput extends DisassociateMem *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DisassociateMemberFromFleetCommand.ts b/clients/client-deadline/src/commands/DisassociateMemberFromFleetCommand.ts index a341e7ff62e3..c3642c24fb03 100644 --- a/clients/client-deadline/src/commands/DisassociateMemberFromFleetCommand.ts +++ b/clients/client-deadline/src/commands/DisassociateMemberFromFleetCommand.ts @@ -61,8 +61,7 @@ export interface DisassociateMemberFromFleetCommandOutput *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -74,8 +73,7 @@ export interface DisassociateMemberFromFleetCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DisassociateMemberFromJobCommand.ts b/clients/client-deadline/src/commands/DisassociateMemberFromJobCommand.ts index 2d12d9b3d3b9..b04fe9f74923 100644 --- a/clients/client-deadline/src/commands/DisassociateMemberFromJobCommand.ts +++ b/clients/client-deadline/src/commands/DisassociateMemberFromJobCommand.ts @@ -66,8 +66,7 @@ export interface DisassociateMemberFromJobCommandOutput extends DisassociateMemb *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/DisassociateMemberFromQueueCommand.ts b/clients/client-deadline/src/commands/DisassociateMemberFromQueueCommand.ts index 76f6b303d576..857199deba89 100644 --- a/clients/client-deadline/src/commands/DisassociateMemberFromQueueCommand.ts +++ b/clients/client-deadline/src/commands/DisassociateMemberFromQueueCommand.ts @@ -61,8 +61,7 @@ export interface DisassociateMemberFromQueueCommandOutput *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -74,8 +73,7 @@ export interface DisassociateMemberFromQueueCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetBudgetCommand.ts b/clients/client-deadline/src/commands/GetBudgetCommand.ts index 449f29b99c75..1977dcd72643 100644 --- a/clients/client-deadline/src/commands/GetBudgetCommand.ts +++ b/clients/client-deadline/src/commands/GetBudgetCommand.ts @@ -94,8 +94,7 @@ export interface GetBudgetCommandOutput extends GetBudgetResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetFarmCommand.ts b/clients/client-deadline/src/commands/GetFarmCommand.ts index 1ea243fb109e..3101c4f4d711 100644 --- a/clients/client-deadline/src/commands/GetFarmCommand.ts +++ b/clients/client-deadline/src/commands/GetFarmCommand.ts @@ -72,8 +72,7 @@ export interface GetFarmCommandOutput extends GetFarmResponse, __MetadataBearer *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetFleetCommand.ts b/clients/client-deadline/src/commands/GetFleetCommand.ts index 6cae854ea58a..dfa85cbeb9a9 100644 --- a/clients/client-deadline/src/commands/GetFleetCommand.ts +++ b/clients/client-deadline/src/commands/GetFleetCommand.ts @@ -152,6 +152,10 @@ export interface GetFleetCommandOutput extends GetFleetResponse, __MetadataBeare * // }, * // }, * // }, + * // hostConfiguration: { // HostConfiguration + * // scriptBody: "STRING_VALUE", // required + * // scriptTimeoutSeconds: Number("int"), + * // }, * // capabilities: { // FleetCapabilities * // amounts: [ // FleetAmountCapabilities * // { @@ -197,8 +201,7 @@ export interface GetFleetCommandOutput extends GetFleetResponse, __MetadataBeare *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetJobCommand.ts b/clients/client-deadline/src/commands/GetJobCommand.ts index b5edb558fff6..aadf7a827955 100644 --- a/clients/client-deadline/src/commands/GetJobCommand.ts +++ b/clients/client-deadline/src/commands/GetJobCommand.ts @@ -111,8 +111,7 @@ export interface GetJobCommandOutput extends GetJobResponse, __MetadataBearer {} *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetLicenseEndpointCommand.ts b/clients/client-deadline/src/commands/GetLicenseEndpointCommand.ts index 2c554e06c24b..cb0029878370 100644 --- a/clients/client-deadline/src/commands/GetLicenseEndpointCommand.ts +++ b/clients/client-deadline/src/commands/GetLicenseEndpointCommand.ts @@ -75,8 +75,7 @@ export interface GetLicenseEndpointCommandOutput extends GetLicenseEndpointRespo *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetLimitCommand.ts b/clients/client-deadline/src/commands/GetLimitCommand.ts index fb9a00d59d7d..74696c212ce5 100644 --- a/clients/client-deadline/src/commands/GetLimitCommand.ts +++ b/clients/client-deadline/src/commands/GetLimitCommand.ts @@ -76,8 +76,7 @@ export interface GetLimitCommandOutput extends GetLimitResponse, __MetadataBeare *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetMonitorCommand.ts b/clients/client-deadline/src/commands/GetMonitorCommand.ts index 2f7c21f0e72f..d310c82306b5 100644 --- a/clients/client-deadline/src/commands/GetMonitorCommand.ts +++ b/clients/client-deadline/src/commands/GetMonitorCommand.ts @@ -75,8 +75,7 @@ export interface GetMonitorCommandOutput extends GetMonitorResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetQueueCommand.ts b/clients/client-deadline/src/commands/GetQueueCommand.ts index d63489364c35..a38ac680d7cc 100644 --- a/clients/client-deadline/src/commands/GetQueueCommand.ts +++ b/clients/client-deadline/src/commands/GetQueueCommand.ts @@ -98,8 +98,7 @@ export interface GetQueueCommandOutput extends GetQueueResponse, __MetadataBeare *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetQueueEnvironmentCommand.ts b/clients/client-deadline/src/commands/GetQueueEnvironmentCommand.ts index 3e771b042752..89ceacd9c9bb 100644 --- a/clients/client-deadline/src/commands/GetQueueEnvironmentCommand.ts +++ b/clients/client-deadline/src/commands/GetQueueEnvironmentCommand.ts @@ -79,8 +79,7 @@ export interface GetQueueEnvironmentCommandOutput extends GetQueueEnvironmentRes *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetQueueFleetAssociationCommand.ts b/clients/client-deadline/src/commands/GetQueueFleetAssociationCommand.ts index 6191951f7a35..2885e2aea808 100644 --- a/clients/client-deadline/src/commands/GetQueueFleetAssociationCommand.ts +++ b/clients/client-deadline/src/commands/GetQueueFleetAssociationCommand.ts @@ -73,8 +73,7 @@ export interface GetQueueFleetAssociationCommandOutput extends GetQueueFleetAsso *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetQueueLimitAssociationCommand.ts b/clients/client-deadline/src/commands/GetQueueLimitAssociationCommand.ts index 1bf70d749d6a..8f2496388c13 100644 --- a/clients/client-deadline/src/commands/GetQueueLimitAssociationCommand.ts +++ b/clients/client-deadline/src/commands/GetQueueLimitAssociationCommand.ts @@ -73,8 +73,7 @@ export interface GetQueueLimitAssociationCommandOutput extends GetQueueLimitAsso *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetSessionActionCommand.ts b/clients/client-deadline/src/commands/GetSessionActionCommand.ts index 0297db0aa3f0..2129732fad3d 100644 --- a/clients/client-deadline/src/commands/GetSessionActionCommand.ts +++ b/clients/client-deadline/src/commands/GetSessionActionCommand.ts @@ -109,8 +109,7 @@ export interface GetSessionActionCommandOutput extends GetSessionActionResponse, *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetSessionCommand.ts b/clients/client-deadline/src/commands/GetSessionCommand.ts index 523d3359382f..62558ba54a77 100644 --- a/clients/client-deadline/src/commands/GetSessionCommand.ts +++ b/clients/client-deadline/src/commands/GetSessionCommand.ts @@ -109,8 +109,7 @@ export interface GetSessionCommandOutput extends GetSessionResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetSessionsStatisticsAggregationCommand.ts b/clients/client-deadline/src/commands/GetSessionsStatisticsAggregationCommand.ts index 53b8ea989694..bcb4fe5e7e67 100644 --- a/clients/client-deadline/src/commands/GetSessionsStatisticsAggregationCommand.ts +++ b/clients/client-deadline/src/commands/GetSessionsStatisticsAggregationCommand.ts @@ -33,10 +33,7 @@ export interface GetSessionsStatisticsAggregationCommandOutput __MetadataBearer {} /** - *Gets a set of statistics for queues or farms. Before you can call the
- * GetSessionStatisticsAggregation operation, you must first call the
- * StartSessionsStatisticsAggregation operation. Statistics are available for
- * 1 hour after you call the StartSessionsStatisticsAggregation operation.
Gets a set of statistics for queues or farms. Before you can call the GetSessionStatisticsAggregation operation, you must first call the StartSessionsStatisticsAggregation operation. Statistics are available for 1 hour after you call the StartSessionsStatisticsAggregation operation.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetStepCommand.ts b/clients/client-deadline/src/commands/GetStepCommand.ts index 604881f9ced3..8f189acd5370 100644 --- a/clients/client-deadline/src/commands/GetStepCommand.ts +++ b/clients/client-deadline/src/commands/GetStepCommand.ts @@ -119,8 +119,7 @@ export interface GetStepCommandOutput extends GetStepResponse, __MetadataBearer *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetStorageProfileCommand.ts b/clients/client-deadline/src/commands/GetStorageProfileCommand.ts index 1adf2f1f433b..79e4687e65b9 100644 --- a/clients/client-deadline/src/commands/GetStorageProfileCommand.ts +++ b/clients/client-deadline/src/commands/GetStorageProfileCommand.ts @@ -83,8 +83,7 @@ export interface GetStorageProfileCommandOutput extends GetStorageProfileRespons *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetStorageProfileForQueueCommand.ts b/clients/client-deadline/src/commands/GetStorageProfileForQueueCommand.ts index 2fd3b082e12d..c2df5f42fe16 100644 --- a/clients/client-deadline/src/commands/GetStorageProfileForQueueCommand.ts +++ b/clients/client-deadline/src/commands/GetStorageProfileForQueueCommand.ts @@ -80,8 +80,7 @@ export interface GetStorageProfileForQueueCommandOutput extends GetStorageProfil *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetTaskCommand.ts b/clients/client-deadline/src/commands/GetTaskCommand.ts index 2a5bf7cd5528..37b6dc772b6c 100644 --- a/clients/client-deadline/src/commands/GetTaskCommand.ts +++ b/clients/client-deadline/src/commands/GetTaskCommand.ts @@ -87,8 +87,7 @@ export interface GetTaskCommandOutput extends GetTaskResponse, __MetadataBearer *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/GetWorkerCommand.ts b/clients/client-deadline/src/commands/GetWorkerCommand.ts index 9ee640c2a6cd..cad336bca373 100644 --- a/clients/client-deadline/src/commands/GetWorkerCommand.ts +++ b/clients/client-deadline/src/commands/GetWorkerCommand.ts @@ -97,8 +97,7 @@ export interface GetWorkerCommandOutput extends GetWorkerResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListBudgetsCommand.ts b/clients/client-deadline/src/commands/ListBudgetsCommand.ts index 54be4b16f7e1..a7b9bcedae35 100644 --- a/clients/client-deadline/src/commands/ListBudgetsCommand.ts +++ b/clients/client-deadline/src/commands/ListBudgetsCommand.ts @@ -87,8 +87,7 @@ export interface ListBudgetsCommandOutput extends ListBudgetsResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListFarmMembersCommand.ts b/clients/client-deadline/src/commands/ListFarmMembersCommand.ts index b8efb3aa86eb..a82c313191ae 100644 --- a/clients/client-deadline/src/commands/ListFarmMembersCommand.ts +++ b/clients/client-deadline/src/commands/ListFarmMembersCommand.ts @@ -76,8 +76,7 @@ export interface ListFarmMembersCommandOutput extends ListFarmMembersResponse, _ *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListFarmsCommand.ts b/clients/client-deadline/src/commands/ListFarmsCommand.ts index 8b938f6f7abc..fec1cb4334ea 100644 --- a/clients/client-deadline/src/commands/ListFarmsCommand.ts +++ b/clients/client-deadline/src/commands/ListFarmsCommand.ts @@ -75,8 +75,7 @@ export interface ListFarmsCommandOutput extends ListFarmsResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListFleetMembersCommand.ts b/clients/client-deadline/src/commands/ListFleetMembersCommand.ts index 24f3dd5920dd..09478773104d 100644 --- a/clients/client-deadline/src/commands/ListFleetMembersCommand.ts +++ b/clients/client-deadline/src/commands/ListFleetMembersCommand.ts @@ -78,8 +78,7 @@ export interface ListFleetMembersCommandOutput extends ListFleetMembersResponse, *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListFleetsCommand.ts b/clients/client-deadline/src/commands/ListFleetsCommand.ts index a8ee5725cfd4..f9d475dece17 100644 --- a/clients/client-deadline/src/commands/ListFleetsCommand.ts +++ b/clients/client-deadline/src/commands/ListFleetsCommand.ts @@ -187,8 +187,7 @@ export interface ListFleetsCommandOutput extends ListFleetsResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListJobMembersCommand.ts b/clients/client-deadline/src/commands/ListJobMembersCommand.ts index eed34c1c01aa..bee5db34aafa 100644 --- a/clients/client-deadline/src/commands/ListJobMembersCommand.ts +++ b/clients/client-deadline/src/commands/ListJobMembersCommand.ts @@ -80,8 +80,7 @@ export interface ListJobMembersCommandOutput extends ListJobMembersResponse, __M *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListJobParameterDefinitionsCommand.ts b/clients/client-deadline/src/commands/ListJobParameterDefinitionsCommand.ts index 82d0dbe75e6b..3dac6766a6a0 100644 --- a/clients/client-deadline/src/commands/ListJobParameterDefinitionsCommand.ts +++ b/clients/client-deadline/src/commands/ListJobParameterDefinitionsCommand.ts @@ -77,8 +77,7 @@ export interface ListJobParameterDefinitionsCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListJobsCommand.ts b/clients/client-deadline/src/commands/ListJobsCommand.ts index d89ae3189a75..d50a07a4d7ba 100644 --- a/clients/client-deadline/src/commands/ListJobsCommand.ts +++ b/clients/client-deadline/src/commands/ListJobsCommand.ts @@ -93,8 +93,7 @@ export interface ListJobsCommandOutput extends ListJobsResponse, __MetadataBeare *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListLicenseEndpointsCommand.ts b/clients/client-deadline/src/commands/ListLicenseEndpointsCommand.ts index f71e177e9785..7973640587dc 100644 --- a/clients/client-deadline/src/commands/ListLicenseEndpointsCommand.ts +++ b/clients/client-deadline/src/commands/ListLicenseEndpointsCommand.ts @@ -74,8 +74,7 @@ export interface ListLicenseEndpointsCommandOutput extends ListLicenseEndpointsR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListLimitsCommand.ts b/clients/client-deadline/src/commands/ListLimitsCommand.ts index 601fd5e1ee29..16e81ab0449b 100644 --- a/clients/client-deadline/src/commands/ListLimitsCommand.ts +++ b/clients/client-deadline/src/commands/ListLimitsCommand.ts @@ -81,8 +81,7 @@ export interface ListLimitsCommandOutput extends ListLimitsResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListMeteredProductsCommand.ts b/clients/client-deadline/src/commands/ListMeteredProductsCommand.ts index d9b8805ff5c3..fcbaa4ed8c8d 100644 --- a/clients/client-deadline/src/commands/ListMeteredProductsCommand.ts +++ b/clients/client-deadline/src/commands/ListMeteredProductsCommand.ts @@ -75,8 +75,7 @@ export interface ListMeteredProductsCommandOutput extends ListMeteredProductsRes *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListMonitorsCommand.ts b/clients/client-deadline/src/commands/ListMonitorsCommand.ts index aecdd5aa3f27..91ae901dd4f9 100644 --- a/clients/client-deadline/src/commands/ListMonitorsCommand.ts +++ b/clients/client-deadline/src/commands/ListMonitorsCommand.ts @@ -78,8 +78,7 @@ export interface ListMonitorsCommandOutput extends ListMonitorsResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListQueueEnvironmentsCommand.ts b/clients/client-deadline/src/commands/ListQueueEnvironmentsCommand.ts index 33422b2d8357..b110ce676d01 100644 --- a/clients/client-deadline/src/commands/ListQueueEnvironmentsCommand.ts +++ b/clients/client-deadline/src/commands/ListQueueEnvironmentsCommand.ts @@ -75,8 +75,7 @@ export interface ListQueueEnvironmentsCommandOutput extends ListQueueEnvironment *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListQueueMembersCommand.ts b/clients/client-deadline/src/commands/ListQueueMembersCommand.ts index 4c98629ad4b2..8f56f17e2b43 100644 --- a/clients/client-deadline/src/commands/ListQueueMembersCommand.ts +++ b/clients/client-deadline/src/commands/ListQueueMembersCommand.ts @@ -78,8 +78,7 @@ export interface ListQueueMembersCommandOutput extends ListQueueMembersResponse, *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListQueuesCommand.ts b/clients/client-deadline/src/commands/ListQueuesCommand.ts index 73186e6ef613..78428fbf5775 100644 --- a/clients/client-deadline/src/commands/ListQueuesCommand.ts +++ b/clients/client-deadline/src/commands/ListQueuesCommand.ts @@ -83,8 +83,7 @@ export interface ListQueuesCommandOutput extends ListQueuesResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListSessionActionsCommand.ts b/clients/client-deadline/src/commands/ListSessionActionsCommand.ts index fe7a0a372273..03c52eae1b56 100644 --- a/clients/client-deadline/src/commands/ListSessionActionsCommand.ts +++ b/clients/client-deadline/src/commands/ListSessionActionsCommand.ts @@ -96,8 +96,7 @@ export interface ListSessionActionsCommandOutput extends ListSessionActionsRespo *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListSessionsCommand.ts b/clients/client-deadline/src/commands/ListSessionsCommand.ts index 77160db84243..d13a2c10f627 100644 --- a/clients/client-deadline/src/commands/ListSessionsCommand.ts +++ b/clients/client-deadline/src/commands/ListSessionsCommand.ts @@ -82,8 +82,7 @@ export interface ListSessionsCommandOutput extends ListSessionsResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListSessionsForWorkerCommand.ts b/clients/client-deadline/src/commands/ListSessionsForWorkerCommand.ts index a9676d4340b0..41c8ded45128 100644 --- a/clients/client-deadline/src/commands/ListSessionsForWorkerCommand.ts +++ b/clients/client-deadline/src/commands/ListSessionsForWorkerCommand.ts @@ -80,8 +80,7 @@ export interface ListSessionsForWorkerCommandOutput extends ListSessionsForWorke *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListStepConsumersCommand.ts b/clients/client-deadline/src/commands/ListStepConsumersCommand.ts index 2edb26610524..56886ae5bd76 100644 --- a/clients/client-deadline/src/commands/ListStepConsumersCommand.ts +++ b/clients/client-deadline/src/commands/ListStepConsumersCommand.ts @@ -76,8 +76,7 @@ export interface ListStepConsumersCommandOutput extends ListStepConsumersRespons *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListStepDependenciesCommand.ts b/clients/client-deadline/src/commands/ListStepDependenciesCommand.ts index 4745d2a6009a..a0e00fdf67f6 100644 --- a/clients/client-deadline/src/commands/ListStepDependenciesCommand.ts +++ b/clients/client-deadline/src/commands/ListStepDependenciesCommand.ts @@ -76,8 +76,7 @@ export interface ListStepDependenciesCommandOutput extends ListStepDependenciesR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListStepsCommand.ts b/clients/client-deadline/src/commands/ListStepsCommand.ts index bc071f494b0a..80a3d6cd9df9 100644 --- a/clients/client-deadline/src/commands/ListStepsCommand.ts +++ b/clients/client-deadline/src/commands/ListStepsCommand.ts @@ -94,8 +94,7 @@ export interface ListStepsCommandOutput extends ListStepsResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListStorageProfilesCommand.ts b/clients/client-deadline/src/commands/ListStorageProfilesCommand.ts index 8533974372ad..e675f672cf41 100644 --- a/clients/client-deadline/src/commands/ListStorageProfilesCommand.ts +++ b/clients/client-deadline/src/commands/ListStorageProfilesCommand.ts @@ -74,8 +74,7 @@ export interface ListStorageProfilesCommandOutput extends ListStorageProfilesRes *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListStorageProfilesForQueueCommand.ts b/clients/client-deadline/src/commands/ListStorageProfilesForQueueCommand.ts index e4b0603fa7f1..bf081445de68 100644 --- a/clients/client-deadline/src/commands/ListStorageProfilesForQueueCommand.ts +++ b/clients/client-deadline/src/commands/ListStorageProfilesForQueueCommand.ts @@ -80,8 +80,7 @@ export interface ListStorageProfilesForQueueCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListTagsForResourceCommand.ts b/clients/client-deadline/src/commands/ListTagsForResourceCommand.ts index 4bb7c3e1f64b..0d3613eefe58 100644 --- a/clients/client-deadline/src/commands/ListTagsForResourceCommand.ts +++ b/clients/client-deadline/src/commands/ListTagsForResourceCommand.ts @@ -67,8 +67,7 @@ export interface ListTagsForResourceCommandOutput extends ListTagsForResourceRes *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListTasksCommand.ts b/clients/client-deadline/src/commands/ListTasksCommand.ts index e6c86f54f7e4..f66a9bd12d15 100644 --- a/clients/client-deadline/src/commands/ListTasksCommand.ts +++ b/clients/client-deadline/src/commands/ListTasksCommand.ts @@ -94,8 +94,7 @@ export interface ListTasksCommandOutput extends ListTasksResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/ListWorkersCommand.ts b/clients/client-deadline/src/commands/ListWorkersCommand.ts index 6ba0c25c0e65..d45c4b641af2 100644 --- a/clients/client-deadline/src/commands/ListWorkersCommand.ts +++ b/clients/client-deadline/src/commands/ListWorkersCommand.ts @@ -103,8 +103,7 @@ export interface ListWorkersCommandOutput extends ListWorkersResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/PutMeteredProductCommand.ts b/clients/client-deadline/src/commands/PutMeteredProductCommand.ts index ac65b601eced..8ce11f3a3b6e 100644 --- a/clients/client-deadline/src/commands/PutMeteredProductCommand.ts +++ b/clients/client-deadline/src/commands/PutMeteredProductCommand.ts @@ -64,8 +64,7 @@ export interface PutMeteredProductCommandOutput extends PutMeteredProductRespons *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/SearchJobsCommand.ts b/clients/client-deadline/src/commands/SearchJobsCommand.ts index 5a34e5f02118..25c4b419e08a 100644 --- a/clients/client-deadline/src/commands/SearchJobsCommand.ts +++ b/clients/client-deadline/src/commands/SearchJobsCommand.ts @@ -170,8 +170,7 @@ export interface SearchJobsCommandOutput extends SearchJobsResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/SearchStepsCommand.ts b/clients/client-deadline/src/commands/SearchStepsCommand.ts index 3cf382f716e7..c7090d1d8f07 100644 --- a/clients/client-deadline/src/commands/SearchStepsCommand.ts +++ b/clients/client-deadline/src/commands/SearchStepsCommand.ts @@ -167,8 +167,7 @@ export interface SearchStepsCommandOutput extends SearchStepsResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/SearchTasksCommand.ts b/clients/client-deadline/src/commands/SearchTasksCommand.ts index 513e1640d12b..68ecb08ba09d 100644 --- a/clients/client-deadline/src/commands/SearchTasksCommand.ts +++ b/clients/client-deadline/src/commands/SearchTasksCommand.ts @@ -161,8 +161,7 @@ export interface SearchTasksCommandOutput extends SearchTasksResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/SearchWorkersCommand.ts b/clients/client-deadline/src/commands/SearchWorkersCommand.ts index 80f336500f13..14c9dcd09880 100644 --- a/clients/client-deadline/src/commands/SearchWorkersCommand.ts +++ b/clients/client-deadline/src/commands/SearchWorkersCommand.ts @@ -163,8 +163,7 @@ export interface SearchWorkersCommandOutput extends SearchWorkersResponse, __Met *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/StartSessionsStatisticsAggregationCommand.ts b/clients/client-deadline/src/commands/StartSessionsStatisticsAggregationCommand.ts index f70ba28d6a28..ed215264ca7c 100644 --- a/clients/client-deadline/src/commands/StartSessionsStatisticsAggregationCommand.ts +++ b/clients/client-deadline/src/commands/StartSessionsStatisticsAggregationCommand.ts @@ -36,13 +36,7 @@ export interface StartSessionsStatisticsAggregationCommandOutput __MetadataBearer {} /** - *Starts an asynchronous request for getting aggregated statistics about queues and farms.
- * Get the statistics using the GetSessionsStatisticsAggregation operation. You
- * can only have one running aggregation for your Deadline Cloud farm. Call the
- * GetSessionsStatisticsAggregation operation and check the
- * status field to see if an aggregation is running. Statistics are available
- * for 1 hour after you call the StartSessionsStatisticsAggregation
- * operation.
Starts an asynchronous request for getting aggregated statistics about queues and farms. Get the statistics using the GetSessionsStatisticsAggregation operation. You can only have one running aggregation for your Deadline Cloud farm. Call the GetSessionsStatisticsAggregation operation and check the status field to see if an aggregation is running. Statistics are available for 1 hour after you call the StartSessionsStatisticsAggregation operation.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/TagResourceCommand.ts b/clients/client-deadline/src/commands/TagResourceCommand.ts index 7d1b82349126..f69623def12d 100644 --- a/clients/client-deadline/src/commands/TagResourceCommand.ts +++ b/clients/client-deadline/src/commands/TagResourceCommand.ts @@ -57,8 +57,7 @@ export interface TagResourceCommandOutput extends TagResourceResponse, __Metadat *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -70,8 +69,7 @@ export interface TagResourceCommandOutput extends TagResourceResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UntagResourceCommand.ts b/clients/client-deadline/src/commands/UntagResourceCommand.ts index 58f93be71823..ad6a093c5ebc 100644 --- a/clients/client-deadline/src/commands/UntagResourceCommand.ts +++ b/clients/client-deadline/src/commands/UntagResourceCommand.ts @@ -57,8 +57,7 @@ export interface UntagResourceCommandOutput extends UntagResourceResponse, __Met *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -70,8 +69,7 @@ export interface UntagResourceCommandOutput extends UntagResourceResponse, __Met *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateBudgetCommand.ts b/clients/client-deadline/src/commands/UpdateBudgetCommand.ts index 952c5e1e7ada..5b706b5dca62 100644 --- a/clients/client-deadline/src/commands/UpdateBudgetCommand.ts +++ b/clients/client-deadline/src/commands/UpdateBudgetCommand.ts @@ -88,8 +88,7 @@ export interface UpdateBudgetCommandOutput extends UpdateBudgetResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateFarmCommand.ts b/clients/client-deadline/src/commands/UpdateFarmCommand.ts index 2bd0f551d9fe..2a87a8c2dbf7 100644 --- a/clients/client-deadline/src/commands/UpdateFarmCommand.ts +++ b/clients/client-deadline/src/commands/UpdateFarmCommand.ts @@ -65,8 +65,7 @@ export interface UpdateFarmCommandOutput extends UpdateFarmResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateFleetCommand.ts b/clients/client-deadline/src/commands/UpdateFleetCommand.ts index 46f6c88efe8e..40e81505ed20 100644 --- a/clients/client-deadline/src/commands/UpdateFleetCommand.ts +++ b/clients/client-deadline/src/commands/UpdateFleetCommand.ts @@ -144,6 +144,10 @@ export interface UpdateFleetCommandOutput extends UpdateFleetResponse, __Metadat * }, * }, * }, + * hostConfiguration: { // HostConfiguration + * scriptBody: "STRING_VALUE", // required + * scriptTimeoutSeconds: Number("int"), + * }, * }; * const command = new UpdateFleetCommand(input); * const response = await client.send(command); @@ -167,15 +171,13 @@ export interface UpdateFleetCommandOutput extends UpdateFleetResponse, __Metadat *The requested resource can't be found.
* * @throws {@link ServiceQuotaExceededException} (client fault) - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* * @throws {@link ThrottlingException} (client fault) *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateJobCommand.ts b/clients/client-deadline/src/commands/UpdateJobCommand.ts index 285440784251..d8df9aeb23f3 100644 --- a/clients/client-deadline/src/commands/UpdateJobCommand.ts +++ b/clients/client-deadline/src/commands/UpdateJobCommand.ts @@ -28,13 +28,7 @@ export interface UpdateJobCommandInput extends UpdateJobRequest {} export interface UpdateJobCommandOutput extends UpdateJobResponse, __MetadataBearer {} /** - *Updates a job.
- *When you change the status of the job to ARCHIVED, the job can't be
- * scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be - * recovered.
- *Updates a job.
When you change the status of the job to ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be recovered.
You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -82,8 +75,7 @@ export interface UpdateJobCommandOutput extends UpdateJobResponse, __MetadataBea *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateLimitCommand.ts b/clients/client-deadline/src/commands/UpdateLimitCommand.ts index 10d4283a1fa4..157589de7cb0 100644 --- a/clients/client-deadline/src/commands/UpdateLimitCommand.ts +++ b/clients/client-deadline/src/commands/UpdateLimitCommand.ts @@ -67,8 +67,7 @@ export interface UpdateLimitCommandOutput extends UpdateLimitResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateMonitorCommand.ts b/clients/client-deadline/src/commands/UpdateMonitorCommand.ts index bede954b67af..f02f3ac73b71 100644 --- a/clients/client-deadline/src/commands/UpdateMonitorCommand.ts +++ b/clients/client-deadline/src/commands/UpdateMonitorCommand.ts @@ -28,8 +28,7 @@ export interface UpdateMonitorCommandInput extends UpdateMonitorRequest {} export interface UpdateMonitorCommandOutput extends UpdateMonitorResponse, __MetadataBearer {} /** - *Modifies the settings for a Deadline Cloud monitor. You can modify one or all of the settings
- * when you call UpdateMonitor.
Modifies the settings for a Deadline Cloud monitor. You can modify one or all of the settings when you call UpdateMonitor.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateQueueCommand.ts b/clients/client-deadline/src/commands/UpdateQueueCommand.ts index fcbb37158af2..aff75a469bb4 100644 --- a/clients/client-deadline/src/commands/UpdateQueueCommand.ts +++ b/clients/client-deadline/src/commands/UpdateQueueCommand.ts @@ -96,8 +96,7 @@ export interface UpdateQueueCommandOutput extends UpdateQueueResponse, __Metadat *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateQueueEnvironmentCommand.ts b/clients/client-deadline/src/commands/UpdateQueueEnvironmentCommand.ts index b4eb2f98d5de..225b9375e7cd 100644 --- a/clients/client-deadline/src/commands/UpdateQueueEnvironmentCommand.ts +++ b/clients/client-deadline/src/commands/UpdateQueueEnvironmentCommand.ts @@ -73,8 +73,7 @@ export interface UpdateQueueEnvironmentCommandOutput extends UpdateQueueEnvironm *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateQueueFleetAssociationCommand.ts b/clients/client-deadline/src/commands/UpdateQueueFleetAssociationCommand.ts index 8a232729e626..8ea101046372 100644 --- a/clients/client-deadline/src/commands/UpdateQueueFleetAssociationCommand.ts +++ b/clients/client-deadline/src/commands/UpdateQueueFleetAssociationCommand.ts @@ -71,8 +71,7 @@ export interface UpdateQueueFleetAssociationCommandOutput *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateQueueLimitAssociationCommand.ts b/clients/client-deadline/src/commands/UpdateQueueLimitAssociationCommand.ts index e0a596bda2fb..9df645dba3ec 100644 --- a/clients/client-deadline/src/commands/UpdateQueueLimitAssociationCommand.ts +++ b/clients/client-deadline/src/commands/UpdateQueueLimitAssociationCommand.ts @@ -33,9 +33,7 @@ export interface UpdateQueueLimitAssociationCommandOutput __MetadataBearer {} /** - *Updates the status of the queue. If you set the status to one of the
- * STOP_LIMIT_USAGE* values, there will be a delay before the status
- * transitions to the STOPPED state.
Updates the status of the queue. If you set the status to one of the STOP_LIMIT_USAGE* values, there will be a delay before the status transitions to the STOPPED state.
Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateSessionCommand.ts b/clients/client-deadline/src/commands/UpdateSessionCommand.ts index 4d7dfe03cf43..33deb930056e 100644 --- a/clients/client-deadline/src/commands/UpdateSessionCommand.ts +++ b/clients/client-deadline/src/commands/UpdateSessionCommand.ts @@ -59,8 +59,7 @@ export interface UpdateSessionCommandOutput extends UpdateSessionResponse, __Met *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -72,8 +71,7 @@ export interface UpdateSessionCommandOutput extends UpdateSessionResponse, __Met *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateStepCommand.ts b/clients/client-deadline/src/commands/UpdateStepCommand.ts index 770ad1b897c8..dcc453852846 100644 --- a/clients/client-deadline/src/commands/UpdateStepCommand.ts +++ b/clients/client-deadline/src/commands/UpdateStepCommand.ts @@ -59,8 +59,7 @@ export interface UpdateStepCommandOutput extends UpdateStepResponse, __MetadataB *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -72,8 +71,7 @@ export interface UpdateStepCommandOutput extends UpdateStepResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateStorageProfileCommand.ts b/clients/client-deadline/src/commands/UpdateStorageProfileCommand.ts index 54dcc900f642..c1c45b68be54 100644 --- a/clients/client-deadline/src/commands/UpdateStorageProfileCommand.ts +++ b/clients/client-deadline/src/commands/UpdateStorageProfileCommand.ts @@ -85,8 +85,7 @@ export interface UpdateStorageProfileCommandOutput extends UpdateStorageProfileR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateTaskCommand.ts b/clients/client-deadline/src/commands/UpdateTaskCommand.ts index f38c717ed8d8..b168e3ee0a4c 100644 --- a/clients/client-deadline/src/commands/UpdateTaskCommand.ts +++ b/clients/client-deadline/src/commands/UpdateTaskCommand.ts @@ -60,8 +60,7 @@ export interface UpdateTaskCommandOutput extends UpdateTaskResponse, __MetadataB *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -73,8 +72,7 @@ export interface UpdateTaskCommandOutput extends UpdateTaskResponse, __MetadataB *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/commands/UpdateWorkerCommand.ts b/clients/client-deadline/src/commands/UpdateWorkerCommand.ts index ce772b932176..1bdb682b5a7f 100644 --- a/clients/client-deadline/src/commands/UpdateWorkerCommand.ts +++ b/clients/client-deadline/src/commands/UpdateWorkerCommand.ts @@ -6,7 +6,7 @@ import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { DeadlineClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../DeadlineClient"; import { commonParams } from "../endpoint/EndpointParameters"; -import { UpdateWorkerRequest, UpdateWorkerResponse } from "../models/models_0"; +import { UpdateWorkerRequest, UpdateWorkerResponse, UpdateWorkerResponseFilterSensitiveLog } from "../models/models_0"; import { de_UpdateWorkerCommand, se_UpdateWorkerCommand } from "../protocols/Aws_restJson1"; /** @@ -81,6 +81,10 @@ export interface UpdateWorkerCommandOutput extends UpdateWorkerResponse, __Metad * // }, * // error: "STRING_VALUE", * // }, + * // hostConfiguration: { // HostConfiguration + * // scriptBody: "STRING_VALUE", // required + * // scriptTimeoutSeconds: Number("int"), + * // }, * // }; * * ``` @@ -95,8 +99,7 @@ export interface UpdateWorkerCommandOutput extends UpdateWorkerResponse, __Metad *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -108,8 +111,7 @@ export interface UpdateWorkerCommandOutput extends UpdateWorkerResponse, __Metad *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
@@ -134,7 +136,7 @@ export class UpdateWorkerCommand extends $Command }) .s("Deadline", "UpdateWorker", {}) .n("DeadlineClient", "UpdateWorkerCommand") - .f(void 0, void 0) + .f(void 0, UpdateWorkerResponseFilterSensitiveLog) .ser(se_UpdateWorkerCommand) .de(de_UpdateWorkerCommand) .build() { diff --git a/clients/client-deadline/src/commands/UpdateWorkerScheduleCommand.ts b/clients/client-deadline/src/commands/UpdateWorkerScheduleCommand.ts index 55b549a9a366..29b31eff14b0 100644 --- a/clients/client-deadline/src/commands/UpdateWorkerScheduleCommand.ts +++ b/clients/client-deadline/src/commands/UpdateWorkerScheduleCommand.ts @@ -124,8 +124,7 @@ export interface UpdateWorkerScheduleCommandOutput extends UpdateWorkerScheduleR *You don't have permission to perform the action.
* * @throws {@link ConflictException} (client fault) - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* * @throws {@link InternalServerErrorException} (server fault) *Deadline Cloud can't process your request right now. Try again later.
@@ -137,8 +136,7 @@ export interface UpdateWorkerScheduleCommandOutput extends UpdateWorkerScheduleR *Your request exceeded a request rate quota.
* * @throws {@link ValidationException} (client fault) - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* * @throws {@link DeadlineServiceException} *Base exception class for all service exceptions from Deadline service.
diff --git a/clients/client-deadline/src/index.ts b/clients/client-deadline/src/index.ts index f070ca096bd6..ee79d28626ba 100644 --- a/clients/client-deadline/src/index.ts +++ b/clients/client-deadline/src/index.ts @@ -1,14 +1,7 @@ // smithy-typescript generated code /* eslint-disable */ /** - *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your - * projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions - * specific to their job function.
- *With Deadline Cloud, content production teams can deploy resources for their workforce - * securely in the cloud, reducing the costs of added physical infrastructure. Keep your - * content production operations secure, while allowing your contributors to access the tools - * they need, such as scalable high-speed storage, licenses, and cost management - * services.
+ *The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions specific to their job function.
With Deadline Cloud, content production teams can deploy resources for their workforce securely in the cloud, reducing the costs of added physical infrastructure. Keep your content production operations secure, while allowing your contributors to access the tools they need, such as scalable high-speed storage, licenses, and cost management services.
* * @packageDocumentation */ diff --git a/clients/client-deadline/src/models/models_0.ts b/clients/client-deadline/src/models/models_0.ts index 0238aeb74450..2802df391d23 100644 --- a/clients/client-deadline/src/models/models_0.ts +++ b/clients/client-deadline/src/models/models_0.ts @@ -6,8 +6,7 @@ import { DocumentType as __DocumentType } from "@smithy/types"; import { DeadlineServiceException as __BaseException } from "./DeadlineServiceException"; /** - *Defines the maximum and minimum number of GPU accelerators required for a worker - * instance..
+ *Defines the maximum and minimum number of GPU accelerators required for a worker instance..
* @public */ export interface AcceleratorCountRange { @@ -46,73 +45,25 @@ export type AcceleratorName = (typeof AcceleratorName)[keyof typeof AcceleratorN */ export interface AcceleratorSelection { /** - *The name of the chip used by the GPU accelerator.
- *If you specify l4 as the name of the accelerator, you must specify
- * latest or grid:r550 as the runtime.
The available GPU accelerators are:
- *
- * t4 - NVIDIA T4 Tensor Core GPU
- * a10g - NVIDIA A10G Tensor Core GPU
- * l4 - NVIDIA L4 Tensor Core GPU
- * l40s - NVIDIA L40S Tensor Core GPU
The name of the chip used by the GPU accelerator.
If you specify l4 as the name of the accelerator, you must specify latest or grid:r550 as the runtime.
The available GPU accelerators are:
t4 - NVIDIA T4 Tensor Core GPU
a10g - NVIDIA A10G Tensor Core GPU
l4 - NVIDIA L4 Tensor Core GPU
l40s - NVIDIA L40S Tensor Core GPU
Specifies the runtime driver to use for the GPU accelerator. You must use the same - * runtime for all GPUs.
- *You can choose from the following runtimes:
- *
- * latest - Use the latest runtime available for the chip. If you
- * specify latest and a new version of the runtime is released, the new
- * version of the runtime is used.
- * grid:r550 - NVIDIA vGPU software 17
- *
- * grid:r535 - NVIDIA vGPU software 16
- *
If you don't specify a runtime, Deadline Cloud uses latest as the default. However,
- * if you have multiple accelerators and specify latest for some and leave others
- * blank, Deadline Cloud raises an exception.
Specifies the runtime driver to use for the GPU accelerator. You must use the same runtime for all GPUs.
You can choose from the following runtimes:
latest - Use the latest runtime available for the chip. If you specify latest and a new version of the runtime is released, the new version of the runtime is used.
grid:r550 - NVIDIA vGPU software 17
grid:r535 - NVIDIA vGPU software 16
If you don't specify a runtime, Deadline Cloud uses latest as the default. However, if you have multiple accelerators and specify latest for some and leave others blank, Deadline Cloud raises an exception.
Provides information about the GPU accelerators used for jobs processed by a - * fleet.
+ *Provides information about the GPU accelerators used for jobs processed by a fleet.
* @public */ export interface AcceleratorCapabilities { /** - *A list of accelerator capabilities requested for this fleet. Only Amazon Elastic Compute Cloud instances - * that provide these capabilities will be used. For example, if you specify both L4 and T4 - * chips, Deadline Cloud will use Amazon EC2 instances that have either the L4 or the T4 chip - * installed.
+ *A list of accelerator capabilities requested for this fleet. Only Amazon Elastic Compute Cloud instances that provide these capabilities will be used. For example, if you specify both L4 and T4 chips, Deadline Cloud will use Amazon EC2 instances that have either the L4 or the T4 chip installed.
* @public */ selections: AcceleratorSelection[] | undefined; @@ -125,8 +76,7 @@ export interface AcceleratorCapabilities { } /** - *Defines the maximum and minimum amount of memory, in MiB, to use for the - * accelerator.
+ *Defines the maximum and minimum amount of memory, in MiB, to use for the accelerator.
* @public */ export interface AcceleratorTotalMemoryMiBRange { @@ -669,6 +619,7 @@ export class ResourceNotFoundException extends __BaseException { * @enum */ export const ServiceQuotaExceededExceptionReason = { + DEPENDENCY_LIMIT_EXCEEDED: "DEPENDENCY_LIMIT_EXCEEDED", KMS_KEY_LIMIT_EXCEEDED: "KMS_KEY_LIMIT_EXCEEDED", SERVICE_QUOTA_EXCEEDED_EXCEPTION: "SERVICE_QUOTA_EXCEEDED_EXCEPTION", } as const; @@ -680,8 +631,7 @@ export type ServiceQuotaExceededExceptionReason = (typeof ServiceQuotaExceededExceptionReason)[keyof typeof ServiceQuotaExceededExceptionReason]; /** - *You exceeded your service quota. Service quotas, also referred to as limits, are the - * maximum number of service resources or operations for your Amazon Web Services account.
+ *You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
* @public */ export class ServiceQuotaExceededException extends __BaseException { @@ -828,8 +778,7 @@ export const ValidationExceptionReason = { export type ValidationExceptionReason = (typeof ValidationExceptionReason)[keyof typeof ValidationExceptionReason]; /** - *The request isn't valid. This can occur if your request contains malformed JSON or - * unsupported characters.
+ *The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
* @public */ export class ValidationException extends __BaseException { @@ -1123,8 +1072,7 @@ export const ConflictExceptionReason = { export type ConflictExceptionReason = (typeof ConflictExceptionReason)[keyof typeof ConflictExceptionReason]; /** - *Your request has conflicting operations. This can occur if you're trying to perform more - * than one operation on the same resource at the same time.
+ *Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
* @public */ export class ConflictException extends __BaseException { @@ -1540,15 +1488,13 @@ export namespace JobEntityIdentifiersUnion { */ export interface BatchGetJobEntityRequest { /** - *The farm ID of the worker that's fetching job details. The worker must have an - * assignment on a job to fetch job details.
+ *The farm ID of the worker that's fetching job details. The worker must have an assignment on a job to fetch job details.
* @public */ farmId: string | undefined; /** - *The fleet ID of the worker that's fetching job details. The worker must have an - * assignment on a job to fetch job details.
+ *The fleet ID of the worker that's fetching job details. The worker must have an assignment on a job to fetch job details.
* @public */ fleetId: string | undefined; @@ -1700,8 +1646,7 @@ export interface JobRunAsUser { windows?: WindowsUser | undefined; /** - *Specifies whether the job should run using the queue's system user or if the job should - * run using the worker agent system user.
+ *Specifies whether the job should run using the queue's system user or if the job should run using the worker agent system user.
* @public */ runAs: RunAs | undefined; @@ -2269,10 +2214,7 @@ export interface BudgetActionToAdd { thresholdPercentage: number | undefined; /** - *A description for the budget action to add.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *A description for the budget action to add.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the budget.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The budget action description.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The budget action description.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the budget.
- *
- * ACTIVE–Get a budget being evaluated.
- * INACTIVE–Get an inactive budget. This can include expired,
- * canceled, or deleted statuses.
The status of the budget.
ACTIVE–Get a budget being evaluated.
INACTIVE–Get an inactive budget. This can include expired, canceled, or deleted statuses.
The display name of the budget.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the budget.
- *
- * ACTIVE–The budget is being evaluated.
- * INACTIVE–The budget is inactive. This can include Expired,
- * Canceled, or deleted Deleted statuses.
The status of the budget.
ACTIVE–The budget is being evaluated.
INACTIVE–The budget is inactive. This can include Expired, Canceled, or deleted Deleted statuses.
The display name of the budget summary to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the budget summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget summary.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the budget summary.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the budget to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the budget to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the budget to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Updates the status of the budget.
- *
- * ACTIVE–The budget is being evaluated.
- * INACTIVE–The budget is inactive. This can include Expired,
- * Canceled, or deleted Deleted statuses.
Updates the status of the budget.
ACTIVE–The budget is being evaluated.
INACTIVE–The budget is inactive. This can include Expired, Canceled, or deleted Deleted statuses.
The budget actions to add. Budget actions specify what happens when the budget runs - * out.
+ *The budget actions to add. Budget actions specify what happens when the budget runs out.
* @public */ actionsToAdd?: BudgetActionToAdd[] | undefined; @@ -2959,8 +2840,7 @@ export interface CopyJobTemplateRequest { queueId: string | undefined; /** - *The Amazon S3 bucket name and key where you would like to add a copy of the job - * template.
+ *The Amazon S3 bucket name and key where you would like to add a copy of the job template.
* @public */ targetS3Location: S3Location | undefined; @@ -3016,19 +2896,13 @@ export interface CreateFarmRequest { clientToken?: string | undefined; /** - *The display name of the farm.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Specifies whether tags associated with a fleet are attached to workers when the worker - * is launched.
- *When the tagPropagationMode is set to
- * PROPAGATE_TAGS_TO_WORKERS_AT_LAUNCH any tag associated with a fleet is
- * attached to workers when they launch. If the tags for a fleet change, the tags associated
- * with running workers do not change.
If you don't specify tagPropagationMode, the default is
- * NO_PROPAGATION.
Specifies whether tags associated with a fleet are attached to workers when the worker is launched.
When the tagPropagationMode is set to PROPAGATE_TAGS_TO_WORKERS_AT_LAUNCH any tag associated with a fleet is attached to workers when they launch. If the tags for a fleet change, the tags associated with running workers do not change.
If you don't specify tagPropagationMode, the default is NO_PROPAGATION.
Describes the GPU accelerator capabilities required for worker host instances in this - * fleet.
+ *Describes the GPU accelerator capabilities required for worker host instances in this fleet.
* @public */ acceleratorCapabilities?: AcceleratorCapabilities | undefined; @@ -3467,6 +3333,24 @@ export namespace FleetConfiguration { }; } +/** + *Provides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
To remove a script from a fleet, use the UpdateFleet operation with the hostConfiguration scriptBody parameter set to an empty string ("").
The text of the script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet. The script runs after a worker enters the STARTING state and before the worker processes tasks.
For more information about using the script, see Run scripts as an administrator to configure workers in the Deadline Cloud Developer Guide.
The script runs as an administrative user (sudo root on Linux, as an Administrator on Windows).
The maximum time that the host configuration can run. If the timeout expires, the worker enters the NOT RESPONDING state and shuts down. You are charged for the time that the worker is running the host configuration script.
You should configure your fleet for a maximum of one worker while testing your host configuration script to avoid starting additional workers.
The default is 300 seconds (5 minutes).
+ * @public + */ + scriptTimeoutSeconds?: number | undefined; +} + /** * @public */ @@ -3484,19 +3368,13 @@ export interface CreateFleetRequest { farmId: string | undefined; /** - *The display name of the fleet.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of workers for the fleet.
+ *The maximum number of workers for the fleet.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
The configuration settings for the fleet. Customer managed fleets are self-managed. - * Service managed Amazon EC2 fleets are managed by Deadline Cloud.
+ *The configuration settings for the fleet. Customer managed fleets are self-managed. Service managed Amazon EC2 fleets are managed by Deadline Cloud.
* @public */ configuration: FleetConfiguration | undefined; @@ -3531,6 +3408,12 @@ export interface CreateFleetRequest { * @public */ tags?: RecordProvides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
+ * @public + */ + hostConfiguration?: HostConfiguration | undefined; } /** @@ -3594,8 +3477,7 @@ export interface CreateJobRequest { templateType?: JobTemplateType | undefined; /** - *The priority of the job. The highest priority (first scheduled) is 100. When two jobs - * have the same priority, the oldest job is scheduled first.
+ *The priority of the job. The highest priority (first scheduled) is 100. When two jobs have the same priority, the oldest job is scheduled first.
* @public */ priority: number | undefined; @@ -3607,8 +3489,7 @@ export interface CreateJobRequest { parameters?: RecordThe attachments for the job. Attach files required for the job to run to a render - * job.
+ *The attachments for the job. Attach files required for the job to run to a render job.
* @public */ attachments?: Attachments | undefined; @@ -3620,8 +3501,7 @@ export interface CreateJobRequest { storageProfileId?: string | undefined; /** - *The initial job status when it is created. Jobs that are created with a
- * SUSPENDED status will not run until manually requeued.
The initial job status when it is created. Jobs that are created with a SUSPENDED status will not run until manually requeued.
The maximum number of worker hosts that can concurrently process a job. When the
- * maxWorkerCount is reached, no more workers will be assigned to process the
- * job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no
- * maximum number of workers.
If you don't specify the maxWorkerCount, Deadline Cloud won't throttle
- * the number of workers used to process the job.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, Deadline Cloud won't throttle the number of workers used to process the job.
The display name of the limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of
- * the hostRequirements in a step of a job template to declare the limit
- * requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are - * in use, steps that require the limit won't be scheduled until the resource is - * available.
- *The maxCount must not be 0. If the value is -1, there is no restriction on
- * the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxCount must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
A description of the limit. A description helps you identify the purpose of the - * limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *A description of the limit. A description helps you identify the purpose of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
A unique identifier for the limit. Use this identifier in other operations, such as
- * CreateQueueLimitAssociation and DeleteLimit.
A unique identifier for the limit. Use this identifier in other operations, such as CreateQueueLimitAssociation and DeleteLimit.
The name that you give the monitor that is displayed in the Deadline Cloud console.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The name that you give the monitor that is displayed in the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain to use when creating the monitor URL. The full URL of the monitor is - * subdomain.Region.deadlinecloud.amazonaws.com.
+ *The subdomain to use when creating the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
* @public */ subdomain: string | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that the monitor uses to connect to Deadline Cloud. Every user - * that signs in to the monitor using IAM Identity Center uses this role to access Deadline Cloud - * resources.
+ *The Amazon Resource Name (ARN) of the IAM role that the monitor uses to connect to Deadline Cloud. Every user that signs in to the monitor using IAM Identity Center uses this role to access Deadline Cloud resources.
* @public */ roleArn: string | undefined; @@ -3870,19 +3724,13 @@ export interface CreateQueueRequest { farmId: string | undefined; /** - *The display name of the queue.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The job attachment settings for the queue. These are the Amazon S3 bucket name and the Amazon S3 - * prefix.
+ *The job attachment settings for the queue. These are the Amazon S3 bucket name and the Amazon S3 prefix.
* @public */ jobAttachmentSettings?: JobAttachmentSettings | undefined; @@ -3979,9 +3826,7 @@ export interface CreateQueueEnvironmentRequest { queueId: string | undefined; /** - *Sets the priority of the environments in the queue from 0 to 10,000, where 0 is the - * highest priority (activated first and deactivated last). If two environments share the same - * priority value, the environment created first takes higher priority.
+ *Sets the priority of the environments in the queue from 0 to 10,000, where 0 is the highest priority (activated first and deactivated last). If two environments share the same priority value, the environment created first takes higher priority.
* @public */ priority: number | undefined; @@ -4137,10 +3982,7 @@ export interface CreateStorageProfileRequest { farmId: string | undefined; /** - *The display name of the storage profile.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the storage profile.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The unique identifier of the farm that contains the queue and limit to - * disassociate.
+ *The unique identifier of the farm that contains the queue and limit to disassociate.
* @public */ farmId: string | undefined; @@ -4539,19 +4380,13 @@ export interface GetFleetResponse { farmId: string | undefined; /** - *The display name of the fleet.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The Auto Scaling status of the fleet. Either GROWING, STEADY, or
- * SHRINKING.
The Auto Scaling status of the fleet. Either GROWING, STEADY, or SHRINKING.
Outlines what the fleet is capable of for minimums, maximums, and naming, in addition to - * attribute names and values.
+ *The script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
+ * @public + */ + hostConfiguration?: HostConfiguration | undefined; + + /** + *Outlines what the fleet is capable of for minimums, maximums, and naming, in addition to attribute names and values.
* @public */ capabilities?: FleetCapabilities | undefined; @@ -4742,10 +4581,7 @@ export interface ListFleetsRequest { principalId?: string | undefined; /** - *The display names of a list of fleets.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display names of a list of fleets.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the fleet summary to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the fleet summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the fleet to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the fleet to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the fleet to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of workers in the fleet.
+ *The maximum number of workers in the fleet.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
Provides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
+ * @public + */ + hostConfiguration?: HostConfiguration | undefined; } /** @@ -5477,11 +5310,16 @@ export interface UpdateWorkerResponse { * @public */ log?: LogConfiguration | undefined; + + /** + *The script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
+ * @public + */ + hostConfiguration?: HostConfiguration | undefined; } /** - *The updated session action information as it relates to completion and progress of the - * session.
+ *The updated session action information as it relates to completion and progress of the session.
* @public */ export interface UpdatedSessionActionInfo { @@ -5492,8 +5330,7 @@ export interface UpdatedSessionActionInfo { completedStatus?: CompletedStatus | undefined; /** - *The process exit code. The default Deadline Cloud worker agent converts unsigned - * 32-bit exit codes to signed 32-bit exit codes.
+ *The process exit code. The default Deadline Cloud worker agent converts unsigned 32-bit exit codes to signed 32-bit exit codes.
* @public */ processExitCode?: number | undefined; @@ -5622,19 +5459,13 @@ export interface GetFarmResponse { farmId: string | undefined; /** - *The display name of the farm.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of
- * the hostRequirements in a step of a job template to declare the limit
- * requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are - * in use, steps that require the limit won't be scheduled until the resource is - * available.
- *The maxValue must not be 0. If the value is -1, there is no restriction on
- * the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxValue must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
The number of resources from the limit that are being used by jobs. The result is - * delayed and may not be the count at the time that you called the operation.
+ *The number of resources from the limit that are being used by jobs. The result is delayed and may not be the count at the time that you called the operation.
* @public */ currentCount: number | undefined; /** - *The description of the limit that helps identify what the limit is used for.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the limit that helps identify what the limit is used for.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the storage profile.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the storage profile.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the farm.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The name of the limit used in lists to identify the limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The name of the limit used in lists to identify the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of
- * the hostRequirements in a step of a job template to declare the limit
- * requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are - * in use, steps that require the limit won't be scheduled until the resource is - * available.
- *The maxValue must not be 0. If the value is -1, there is no restriction on
- * the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxValue must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
The number of resources from the limit that are being used by jobs. The result is - * delayed and may not be the count at the time that you called the operation.
+ *The number of resources from the limit that are being used by jobs. The result is delayed and may not be the count at the time that you called the operation.
* @public */ currentCount: number | undefined; @@ -6162,10 +5964,7 @@ export interface StorageProfileSummary { storageProfileId: string | undefined; /** - *The display name of the storage profile summary to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the storage profile summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the queue.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the queue.
- *
- * ACTIVE–The queue is active.
- * SCHEDULING–The queue is scheduling.
- * SCHEDULING_BLOCKED–The queue scheduling is blocked. See the
- * provided reason.
The status of the queue.
ACTIVE–The queue is active.
SCHEDULING–The queue is scheduling.
SCHEDULING_BLOCKED–The queue scheduling is blocked. See the provided reason.
The display name of the storage profile connected to a queue.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the storage profile connected to a queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the job.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the job.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of worker hosts that can concurrently process a job. When the
- * maxWorkerCount is reached, no more workers will be assigned to process the
- * job, even if the fleets assigned to the job's queue has available workers.
If you don't set the maxWorkerCount when you create a job, this value is
- * not returned in the response.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
If you don't set the maxWorkerCount when you create a job, this value is not returned in the response.
The process exit code. The default Deadline Cloud worker agent converts unsigned - * 32-bit exit codes to signed 32-bit exit codes.
+ *The process exit code. The default Deadline Cloud worker agent converts unsigned 32-bit exit codes to signed 32-bit exit codes.
* @public */ processExitCode?: number | undefined; @@ -7217,8 +6984,7 @@ export interface GetSessionActionResponse { definition: SessionActionDefinition | undefined; /** - *The limits and their amounts acquired during a session action. If no limits were - * acquired during the session, this field isn't returned.
+ *The limits and their amounts acquired during a session action. If no limits were acquired during the session, this field isn't returned.
* @public */ acquiredLimits?: AcquiredLimit[] | undefined; @@ -7542,10 +7308,7 @@ export interface GetStepResponse { parameterSpace?: ParameterSpace | undefined; /** - *The description of the step.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the step.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The task run status for the job.
- *
- * PENDING–pending and waiting for resources.
- * READY–ready to be processed.
- * ASSIGNED–assigned and will run next on a worker.
- * SCHEDULED–scheduled to be run on a worker.
- * INTERRUPTING–being interrupted.
- * RUNNING–running on a worker.
- * SUSPENDED–the task is suspended.
- * CANCELED–the task has been canceled.
- * FAILED–the task has failed.
- * SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The maximum number of worker hosts that can concurrently process a job. When the
- * maxWorkerCount is reached, no more workers will be assigned to process the
- * job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no
- * maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The Linux timestamp of the last date and time that the session action was - * updated.
+ *The Linux timestamp of the last date and time that the session action was updated.
* @public */ workerUpdatedAt?: Date | undefined; @@ -8649,49 +8364,7 @@ export interface StepSummary { lifecycleStatusMessage?: string | undefined; /** - *The task run status for the job.
- *
- * PENDING–pending and waiting for resources.
- * READY–ready to process.
- * ASSIGNED–assigned and will run next on a worker.
- * SCHEDULED–scheduled to run on a worker.
- * INTERRUPTING–being interrupted.
- * RUNNING–running on a worker.
- * SUSPENDED–the task is suspended.
- * CANCELED–the task has been canceled.
- * FAILED–the task has failed.
- * SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to process.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The details of a task.
- * @public - */ -export interface TaskSummary { - /** - *The task ID.
- * @public - */ - taskId: string | undefined; - - /** - *The date and time the resource was created.
- * @public - */ - createdAt: Date | undefined; - - /** - *The user or system that created this resource.
- * @public - */ - createdBy: string | undefined; - - /** - *The run status of the task.
- * @public - */ - runStatus: TaskRunStatus | undefined; - - /** - *The run status on which the started.
- * @public - */ - targetRunStatus?: TaskTargetRunStatus | undefined; - - /** - *The number of times that the task failed and was retried.
- * @public - */ - failureRetryCount?: number | undefined; - - /** - *The task parameters.
- * @public - */ - parameters?: RecordThe date and time the resource started running.
- * @public - */ - startedAt?: Date | undefined; - - /** - *The date and time the resource ended running.
- * @public - */ - endedAt?: Date | undefined; - - /** - *The date and time the resource was updated.
- * @public - */ - updatedAt?: Date | undefined; - - /** - *The user or system that updated this resource.
- * @public - */ - updatedBy?: string | undefined; - - /** - *The latest session action for the task.
- * @public - */ - latestSessionActionId?: string | undefined; -} - /** * @internal */ @@ -9138,6 +8733,14 @@ export const CreateFarmRequestFilterSensitiveLog = (obj: CreateFarmRequest): any ...(obj.description && { description: SENSITIVE_STRING }), }); +/** + * @internal + */ +export const HostConfigurationFilterSensitiveLog = (obj: HostConfiguration): any => ({ + ...obj, + ...(obj.scriptBody && { scriptBody: SENSITIVE_STRING }), +}); + /** * @internal */ @@ -9145,6 +8748,7 @@ export const CreateFleetRequestFilterSensitiveLog = (obj: CreateFleetRequest): a ...obj, ...(obj.description && { description: SENSITIVE_STRING }), ...(obj.configuration && { configuration: obj.configuration }), + ...(obj.hostConfiguration && { hostConfiguration: HostConfigurationFilterSensitiveLog(obj.hostConfiguration) }), }); /** @@ -9203,6 +8807,7 @@ export const GetFleetResponseFilterSensitiveLog = (obj: GetFleetResponse): any = ...obj, ...(obj.description && { description: SENSITIVE_STRING }), ...(obj.configuration && { configuration: obj.configuration }), + ...(obj.hostConfiguration && { hostConfiguration: HostConfigurationFilterSensitiveLog(obj.hostConfiguration) }), }); /** @@ -9212,6 +8817,15 @@ export const UpdateFleetRequestFilterSensitiveLog = (obj: UpdateFleetRequest): a ...obj, ...(obj.description && { description: SENSITIVE_STRING }), ...(obj.configuration && { configuration: obj.configuration }), + ...(obj.hostConfiguration && { hostConfiguration: HostConfigurationFilterSensitiveLog(obj.hostConfiguration) }), +}); + +/** + * @internal + */ +export const UpdateWorkerResponseFilterSensitiveLog = (obj: UpdateWorkerResponse): any => ({ + ...obj, + ...(obj.hostConfiguration && { hostConfiguration: HostConfigurationFilterSensitiveLog(obj.hostConfiguration) }), }); /** @@ -9353,11 +8967,3 @@ export const GetTaskResponseFilterSensitiveLog = (obj: GetTaskResponse): any => ...obj, ...(obj.parameters && { parameters: SENSITIVE_STRING }), }); - -/** - * @internal - */ -export const TaskSummaryFilterSensitiveLog = (obj: TaskSummary): any => ({ - ...obj, - ...(obj.parameters && { parameters: SENSITIVE_STRING }), -}); diff --git a/clients/client-deadline/src/models/models_1.ts b/clients/client-deadline/src/models/models_1.ts index ac969ffc0ad7..042265a77b1e 100644 --- a/clients/client-deadline/src/models/models_1.ts +++ b/clients/client-deadline/src/models/models_1.ts @@ -25,12 +25,88 @@ import { StorageProfileSummary, TaskParameterValue, TaskRunStatus, - TaskSummary, - TaskSummaryFilterSensitiveLog, TaskTargetRunStatus, WorkerStatus, } from "./models_0"; +/** + *The details of a task.
+ * @public + */ +export interface TaskSummary { + /** + *The task ID.
+ * @public + */ + taskId: string | undefined; + + /** + *The date and time the resource was created.
+ * @public + */ + createdAt: Date | undefined; + + /** + *The user or system that created this resource.
+ * @public + */ + createdBy: string | undefined; + + /** + *The run status of the task.
+ * @public + */ + runStatus: TaskRunStatus | undefined; + + /** + *The run status on which the started.
+ * @public + */ + targetRunStatus?: TaskTargetRunStatus | undefined; + + /** + *The number of times that the task failed and was retried.
+ * @public + */ + failureRetryCount?: number | undefined; + + /** + *The task parameters.
+ * @public + */ + parameters?: RecordThe date and time the resource started running.
+ * @public + */ + startedAt?: Date | undefined; + + /** + *The date and time the resource ended running.
+ * @public + */ + endedAt?: Date | undefined; + + /** + *The date and time the resource was updated.
+ * @public + */ + updatedAt?: Date | undefined; + + /** + *The user or system that updated this resource.
+ * @public + */ + updatedBy?: string | undefined; + + /** + *The latest session action for the task.
+ * @public + */ + latestSessionActionId?: string | undefined; +} + /** * @public */ @@ -96,24 +172,13 @@ export interface UpdateJobRequest { maxRetriesPerTask?: number | undefined; /** - *The status of a job in its lifecycle. When you change the status of the job to
- * ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be - * recovered.
- *The status of a job in its lifecycle. When you change the status of the job to ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be recovered.
The maximum number of worker hosts that can concurrently process a job. When the
- * maxWorkerCount is reached, no more workers will be assigned to process the
- * job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no
- * maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of workers that can process tasks in the job.
+ *The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of workers that can process tasks in the job.
* @public */ maxWorkerCount?: number | undefined; @@ -461,22 +526,7 @@ export interface ListQueuesRequest { principalId?: string | undefined; /** - *The status of the queues listed.
- *
- * ACTIVE–The queues are active.
- * SCHEDULING–The queues are scheduling.
- * SCHEDULING_BLOCKED–The queue scheduling is blocked for these
- * queues.
The status of the queues listed.
ACTIVE–The queues are active.
SCHEDULING–The queues are scheduling.
SCHEDULING_BLOCKED–The queue scheduling is blocked for these queues.
The display name of the queue summary to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the queue summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the queue to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the queue to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the queue to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The job attachment settings to update for the - * queue.
+ *The job attachment settings to update for the queue.
* @public */ jobAttachmentSettings?: JobAttachmentSettings | undefined; @@ -784,19 +824,13 @@ export interface UpdateFarmRequest { farmId: string | undefined; /** - *The display name of the farm to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the farm to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The description of the farm to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The new display name of the limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The new display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The new description of the limit.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The new description of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of resources constrained by this limit. When all of the resources are - * in use, steps that require the limit won't be scheduled until the resource is - * available.
- *If more than the new maximum number is currently in use, running jobs finish but no new - * jobs are started until the number of resources in use is below the new maximum - * number.
- *The maxCount must not be 0. If the value is -1, there is no restriction on
- * the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
If more than the new maximum number is currently in use, running jobs finish but no new jobs are started until the number of resources in use is below the new maximum number.
The maxCount must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
The display name of the storage profile to update.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The display name of the storage profile to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The identifier of the farm to include in the statistics. This should be the same as the
- * farm ID used in the call to the StartSessionsStatisticsAggregation
- * operation.
The identifier of the farm to include in the statistics. This should be the same as the farm ID used in the call to the StartSessionsStatisticsAggregation operation.
The identifier returned by the StartSessionsStatisticsAggregation operation
- * that identifies the aggregated statistics.
The identifier returned by the StartSessionsStatisticsAggregation operation that identifies the aggregated statistics.
How the statistics should appear in USD. Options include: minimum, maximum, average or - * sum.
+ *How the statistics should appear in USD. Options include: minimum, maximum, average or sum.
* @public */ costInUsd: Stats | undefined; @@ -1284,14 +1298,7 @@ export interface GetSessionsStatisticsAggregationResponse { nextToken?: string | undefined; /** - *The status of the aggregated results. An aggregation may fail or time out if the results
- * are too large. If this happens, you can call the
- * StartSessionsStatisticsAggregation operation after you reduce the
- * aggregation time frame, reduce the number of queues or fleets in the aggregation, or
- * increase the period length.
If you call the StartSessionsStatisticsAggregation operation when the
- * status is IN_PROGRESS, you will receive a
- * ThrottlingException.
The status of the aggregated results. An aggregation may fail or time out if the results are too large. If this happens, you can call the StartSessionsStatisticsAggregation operation after you reduce the aggregation time frame, reduce the number of queues or fleets in the aggregation, or increase the period length.
If you call the StartSessionsStatisticsAggregation operation when the status is IN_PROGRESS, you will receive a ThrottlingException.
The status of task scheduling in the queue-fleet association.
- *
- * ACTIVE–Association is active.
- * STOP_SCHEDULING_AND_COMPLETE_TASKS–Association has stopped
- * scheduling new tasks and is completing current tasks.
- * STOP_SCHEDULING_AND_CANCEL_TASKS–Association has stopped
- * scheduling new tasks and is canceling current tasks.
- * STOPPED–Association has been stopped.
The status of task scheduling in the queue-fleet association.
ACTIVE–Association is active.
STOP_SCHEDULING_AND_COMPLETE_TASKS–Association has stopped scheduling new tasks and is completing current tasks.
STOP_SCHEDULING_AND_CANCEL_TASKS–Association has stopped scheduling new tasks and is canceling current tasks.
STOPPED–Association has been stopped.
Specifies that the operation should return only the queue limit associations for the
- * specified queue. If you specify both the queueId and the limitId,
- * only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the specified queue. If you specify both the queueId and the limitId, only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the
- * specified limit. If you specify both the queueId and the limitId,
- * only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the specified limit. If you specify both the queueId and the limitId, only the specified limit is returned if it exists.
The status of task scheduling in the queue-limit association.
- *
- * ACTIVE - Association is active.
- * STOP_LIMIT_USAGE_AND_COMPLETE_TASKS - Association has stopped
- * scheduling new tasks and is completing current tasks.
- * STOP_LIMIT_USAGE_AND_CANCEL_TASKS - Association has stopped
- * scheduling new tasks and is canceling current tasks.
- * STOPPED - Association has been stopped.
The status of task scheduling in the queue-limit association.
ACTIVE - Association is active.
STOP_LIMIT_USAGE_AND_COMPLETE_TASKS - Association has stopped scheduling new tasks and is completing current tasks.
STOP_LIMIT_USAGE_AND_CANCEL_TASKS - Association has stopped scheduling new tasks and is canceling current tasks.
STOPPED - Association has been stopped.
A list of associations between limits and queues in the farm specified in the - * request.
+ *A list of associations between limits and queues in the farm specified in the request.
* @public */ queueLimitAssociations: QueueLimitAssociationSummary[] | undefined; @@ -1877,9 +1839,7 @@ export interface ListTagsForResourceResponse { */ export interface DeleteMonitorRequest { /** - *The unique identifier of the monitor to delete. This ID is returned by the
- * CreateMonitor operation, and is included in the response to the
- * GetMonitor operation.
The unique identifier of the monitor to delete. This ID is returned by the CreateMonitor operation, and is included in the response to the GetMonitor operation.
The unique identifier for the monitor. This ID is returned by the
- * CreateMonitor operation.
The unique identifier for the monitor. This ID is returned by the CreateMonitor operation.
The name used to identify the monitor on the Deadline Cloud console.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The name used to identify the monitor on the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain used for the monitor URL. The full URL of the monitor is - * subdomain.Region.deadlinecloud.amazonaws.com.
+ *The subdomain used for the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
* @public */ subdomain: string | undefined; /** - *The complete URL of the monitor. The full URL of the monitor is - * subdomain.Region.deadlinecloud.amazonaws.com.
+ *The complete URL of the monitor. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
* @public */ url: string | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to - * access Deadline Cloud resources.
+ *The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to access Deadline Cloud resources.
* @public */ roleArn: string | undefined; @@ -2008,31 +1961,25 @@ export interface MonitorSummary { monitorId: string | undefined; /** - *The name of the monitor that displays on the Deadline Cloud console.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The name of the monitor that displays on the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain used for the monitor URL. The full URL of the monitor is - * subdomain.Region.deadlinecloud.amazonaws.com.
+ *The subdomain used for the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
* @public */ subdomain: string | undefined; /** - *The complete URL of the monitor. The full URL of the monitor is - * subdomain.Region.deadlinecloud.amazonaws.com.
+ *The complete URL of the monitor. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
* @public */ url: string | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to - * access Deadline Cloud resources.
+ *The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to access Deadline Cloud resources.
* @public */ roleArn: string | undefined; @@ -2085,8 +2032,7 @@ export interface ListMonitorsResponse { nextToken?: string | undefined; /** - *A list of MonitorSummary objects that describe your monitors in the
- * Deadline Cloud.
A list of MonitorSummary objects that describe your monitors in the Deadline Cloud.
The new value to use for the monitor's display name.
- *This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
- *The new value to use for the monitor's display name.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Specifies how Deadline Cloud matches your search term in the results. If you don't
- * specify a matchType the default is FUZZY_MATCH.
- * FUZZY_MATCH - Matches if a portion of the search term is found in the
- * result.
- * CONTAINS - Matches if the exact search term is contained in the
- * result.
Specifies how Deadline Cloud matches your search term in the results. If you don't specify a matchType the default is FUZZY_MATCH.
FUZZY_MATCH - Matches if a portion of the search term is found in the result.
CONTAINS - Matches if the exact search term is contained in the result.
The task run status for the job.
- *
- * PENDING–pending and waiting for resources.
- * READY–ready to be processed.
- * ASSIGNED–assigned and will run next on a worker.
- * SCHEDULED–scheduled to be run on a worker.
- * INTERRUPTING–being interrupted.
- * RUNNING–running on a worker.
- * SUSPENDED–the task is suspended.
- * CANCELED–the task has been canceled.
- * FAILED–the task has failed.
- * SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The maximum number of worker hosts that can concurrently process a job. When the
- * maxWorkerCount is reached, no more workers will be assigned to process the
- * job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no
- * maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The task run status for the job.
- *
- * PENDING–pending and waiting for resources.
- * READY–ready to be processed.
- * ASSIGNED–assigned and will run next on a worker.
- * SCHEDULED–scheduled to be run on a worker.
- * INTERRUPTING–being interrupted.
- * RUNNING–running on a worker.
- * SUSPENDED–the task is suspended.
- * CANCELED–the task has been canceled.
- * FAILED–the task has failed.
- * SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
Specifies the fleet IDs or queue IDs to return statistics. You can specify only fleet - * IDs or queue IDS, not both.
+ *Specifies the fleet IDs or queue IDs to return statistics. You can specify only fleet IDs or queue IDS, not both.
* @public */ export type SessionsStatisticsResources = @@ -2919,8 +2759,7 @@ export type SessionsStatisticsResources = */ export namespace SessionsStatisticsResources { /** - *One to 10 queue IDs that specify the queues to return statistics for. If you specify the
- * queueIds field, you can't specify the fleetIds field.
One to 10 queue IDs that specify the queues to return statistics for. If you specify the queueIds field, you can't specify the fleetIds field.
One to 10 fleet IDs that specify the fleets to return statistics for. If you specify the
- * fleetIds field, you can't specify the queueIds field.
One to 10 fleet IDs that specify the fleets to return statistics for. If you specify the fleetIds field, you can't specify the queueIds field.
The identifier of the farm that contains queues or fleets to return statistics - * for.
+ *The identifier of the farm that contains queues or fleets to return statistics for.
* @public */ farmId: string | undefined; @@ -3037,9 +2874,7 @@ export interface StartSessionsStatisticsAggregationRequest { */ export interface StartSessionsStatisticsAggregationResponse { /** - *A unique identifier for the aggregated statistics. Use this identifier with the
- * GetAggregatedStatisticsForSessions operation to return the
- * statistics.
A unique identifier for the aggregated statistics. Use this identifier with the GetAggregatedStatisticsForSessions operation to return the statistics.
Sets the status of the limit. You can mark the limit active, or you can stop usage of - * the limit and either complete existing tasks or cancel any existing tasks immediately. - *
+ *Sets the status of the limit. You can mark the limit active, or you can stop usage of the limit and either complete existing tasks or cancel any existing tasks immediately.
* @public */ status: UpdateQueueLimitAssociationStatus | undefined; @@ -3304,10 +3137,7 @@ export namespace SearchFilterExpression { } /** - *The filter expression, AND or OR, to use
- * when searching among a group of search strings in a resource.
- *
- * You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use
- * when searching among a group of search strings in a resource.
- *
- * You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use
- * when searching among a group of search strings in a resource.
- *
- * You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use
- * when searching among a group of search strings in a resource.
- *
- * You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use
- * when searching among a group of search strings in a resource.
- *
- * You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The Amazon EC2 API follows an eventual consistency model. This means that the result of an + * API command you run that creates or modifies resources might not be immediately + * available to all subsequent commands you run. For guidance on how to manage eventual + * consistency, see Eventual consistency in the + * Amazon EC2 API in the Amazon EC2 Developer + * Guide.
*The order of the elements in the response, including those within nested * structures, might vary. Applications should not assume the elements appear in a diff --git a/clients/client-ec2/src/commands/DescribeInstancesCommand.ts b/clients/client-ec2/src/commands/DescribeInstancesCommand.ts index e564686c7101..12ecd6493619 100644 --- a/clients/client-ec2/src/commands/DescribeInstancesCommand.ts +++ b/clients/client-ec2/src/commands/DescribeInstancesCommand.ts @@ -44,6 +44,12 @@ export interface DescribeInstancesCommandOutput extends DescribeInstancesResult, * not specify any instance IDs at all, the call fails. If you describe instances and * specify only instance IDs that are in an unaffected zone, the call works * normally.
+ *The Amazon EC2 API follows an eventual consistency model. This means that the result of an + * API command you run that creates or modifies resources might not be immediately + * available to all subsequent commands you run. For guidance on how to manage eventual + * consistency, see Eventual consistency in the + * Amazon EC2 API in the Amazon EC2 Developer + * Guide.
*We strongly recommend using only paginated requests. Unpaginated requests are * susceptible to throttling and timeouts.
diff --git a/clients/client-ec2/src/commands/DescribeNetworkInsightsAnalysesCommand.ts b/clients/client-ec2/src/commands/DescribeNetworkInsightsAnalysesCommand.ts index 3f6d0f692436..4de568972363 100644 --- a/clients/client-ec2/src/commands/DescribeNetworkInsightsAnalysesCommand.ts +++ b/clients/client-ec2/src/commands/DescribeNetworkInsightsAnalysesCommand.ts @@ -254,6 +254,9 @@ export interface DescribeNetworkInsightsAnalysesCommandOutput * // AvailabilityZones: [ * // "STRING_VALUE", * // ], + * // AvailabilityZoneIds: [ + * // "STRING_VALUE", + * // ], * // Cidrs: [ * // "STRING_VALUE", * // ], @@ -274,6 +277,7 @@ export interface DescribeNetworkInsightsAnalysesCommandOutput * // LoadBalancerTarget: { // AnalysisLoadBalancerTarget * // Address: "STRING_VALUE", * // AvailabilityZone: "STRING_VALUE", + * // AvailabilityZoneId: "STRING_VALUE", * // Instance: "The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; + /** *Information about the instance.
* @public @@ -1878,6 +1884,12 @@ export interface Explanation { */ AvailabilityZones?: string[] | undefined; + /** + *The IDs of the Availability Zones.
+ * @public + */ + AvailabilityZoneIds?: string[] | undefined; + /** *The CIDR ranges.
* @public @@ -3515,6 +3527,12 @@ export interface AllocateHostsRequest { */ AssetIds?: string[] | undefined; + /** + *The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; + /** *Indicates whether the host accepts any untargeted instance launches that match its * instance type configuration, or if it only accepts Host tenancy instance launches that @@ -3558,7 +3576,7 @@ export interface AllocateHostsRequest { *
The Availability Zone in which to allocate the Dedicated Host.
* @public */ - AvailabilityZone: string | undefined; + AvailabilityZone?: string | undefined; } /** diff --git a/clients/client-ec2/src/models/models_3.ts b/clients/client-ec2/src/models/models_3.ts index e579b84d9c02..36fe06e36c90 100644 --- a/clients/client-ec2/src/models/models_3.ts +++ b/clients/client-ec2/src/models/models_3.ts @@ -6241,6 +6241,12 @@ export interface CapacityReservationInfo { * @public */ Tenancy?: CapacityReservationTenancy | undefined; + + /** + *The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; } /** diff --git a/clients/client-ec2/src/models/models_5.ts b/clients/client-ec2/src/models/models_5.ts index 37262db952e7..6cefaf4a8614 100644 --- a/clients/client-ec2/src/models/models_5.ts +++ b/clients/client-ec2/src/models/models_5.ts @@ -2566,6 +2566,11 @@ export interface DescribeReservedInstancesRequest { * *
+ * availability-zone-id - The ID of the Availability Zone where the Reserved
+ * Instance can be used.
* duration - The duration of the Reserved Instance (one year or three
* years), in seconds (31536000 | 94608000).
The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; + /** *The ID of the Reserved Instance.
* @public @@ -2948,6 +2959,11 @@ export interface DescribeReservedInstancesModificationsRequest { * *
+ * modification-result.target-configuration.availability-zone-id - The ID of the
+ * Availability Zone for the new Reserved Instances.
* modification-result.target-configuration.instance-count - The number of new
* Reserved Instances.
The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; } /** @@ -3145,6 +3167,8 @@ export interface DescribeReservedInstancesModificationsResult { export interface DescribeReservedInstancesOfferingsRequest { /** *The Availability Zone in which the Reserved Instance can be used.
+ *Either AvailabilityZone or AvailabilityZoneId can be specified,
+ * but not both.
The ID of the Availability Zone.
+ *Either AvailabilityZone or AvailabilityZoneId can be specified,
+ * but not both.
Checks whether you have the required permissions for the action, without actually making * the request, and provides an error response. If you have the required permissions, the error @@ -3223,6 +3255,11 @@ export interface DescribeReservedInstancesOfferingsRequest { * *
+ * availability-zone-id - The ID of the Availability Zone where the Reserved
+ * Instance can be used.
* duration - The duration of the Reserved Instance (for example, one year or
* three years), in seconds (31536000 | 94608000).
The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; + /** *The ID of the Reserved Instance offering. This is the offering ID used in GetReservedInstancesExchangeQuote to confirm that an exchange can be * made.
@@ -10402,6 +10445,12 @@ export interface VolumeStatusItem { * @public */ AttachmentStatuses?: VolumeStatusAttachmentStatus[] | undefined; + + /** + *The ID of the Availability Zone.
+ * @public + */ + AvailabilityZoneId?: string | undefined; } /** diff --git a/clients/client-ec2/src/protocols/Aws_ec2.ts b/clients/client-ec2/src/protocols/Aws_ec2.ts index c86eaba15893..7fed522acd71 100644 --- a/clients/client-ec2/src/protocols/Aws_ec2.ts +++ b/clients/client-ec2/src/protocols/Aws_ec2.ts @@ -30098,6 +30098,9 @@ const se_AllocateHostsRequest = (input: AllocateHostsRequest, context: __SerdeCo entries[loc] = value; }); } + if (input[_AZI] != null) { + entries[_AZI] = input[_AZI]; + } if (input[_AP] != null) { entries[_AP] = input[_AP]; } @@ -40765,6 +40768,9 @@ const se_DescribeReservedInstancesOfferingsRequest = ( entries[loc] = value; }); } + if (input[_AZI] != null) { + entries[_AZI] = input[_AZI]; + } if (input[_DRr] != null) { entries[_DRr] = input[_DRr]; } @@ -55086,6 +55092,9 @@ const se_ReservedInstancesConfiguration = (input: ReservedInstancesConfiguration if (input[_Sc] != null) { entries[_Sc] = input[_Sc]; } + if (input[_AZI] != null) { + entries[_AZI] = input[_AZI]; + } return entries; }; @@ -59707,6 +59716,9 @@ const de_AnalysisLoadBalancerTarget = (output: any, context: __SerdeContext): An if (output[_aZ] != null) { contents[_AZ] = __expectString(output[_aZ]); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } if (output[_in] != null) { contents[_Ins] = de_AnalysisComponent(output[_in], context); } @@ -61648,6 +61660,9 @@ const de_CapacityReservationInfo = (output: any, context: __SerdeContext): Capac if (output[_t] != null) { contents[_Te] = __expectString(output[_t]); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } return contents; }; @@ -70054,6 +70069,11 @@ const de_Explanation = (output: any, context: __SerdeContext): Explanation => { } else if (output[_aZS] != null && output[_aZS][_i] != null) { contents[_AZv] = de_ValueStringList(__getArrayIfSingleItem(output[_aZS][_i]), context); } + if (output.availabilityZoneIdSet === "") { + contents[_AZIv] = []; + } else if (output[_aZIS] != null && output[_aZIS][_i] != null) { + contents[_AZIv] = de_ValueStringList(__getArrayIfSingleItem(output[_aZIS][_i]), context); + } if (output.cidrSet === "") { contents[_Ci] = []; } else if (output[_cS] != null && output[_cS][_i] != null) { @@ -82117,6 +82137,9 @@ const de_ReservedInstances = (output: any, context: __SerdeContext): ReservedIns } else if (output[_tS] != null && output[_tS][_i] != null) { contents[_Ta] = de_TagList(__getArrayIfSingleItem(output[_tS][_i]), context); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } if (output[_rII] != null) { contents[_RIIe] = __expectString(output[_rII]); } @@ -82173,6 +82196,9 @@ const de_ReservedInstancesConfiguration = (output: any, context: __SerdeContext) if (output[_sc] != null) { contents[_Sc] = __expectString(output[_sc]); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } return contents; }; @@ -82370,6 +82396,9 @@ const de_ReservedInstancesOffering = (output: any, context: __SerdeContext): Res if (output[_sc] != null) { contents[_Sc] = __expectString(output[_sc]); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } if (output[_rIOI] != null) { contents[_RIOIe] = __expectString(output[_rIOI]); } @@ -89166,6 +89195,9 @@ const de_VolumeStatusItem = (output: any, context: __SerdeContext): VolumeStatus } else if (output[_aStt] != null && output[_aStt][_i] != null) { contents[_AStt] = de_VolumeStatusAttachmentStatusList(__getArrayIfSingleItem(output[_aStt][_i]), context); } + if (output[_aZI] != null) { + contents[_AZI] = __expectString(output[_aZI]); + } return contents; }; @@ -90341,6 +90373,7 @@ const _AWSAKI = "AWSAccessKeyId"; const _AZ = "AvailabilityZone"; const _AZG = "AvailabilityZoneGroup"; const _AZI = "AvailabilityZoneId"; +const _AZIv = "AvailabilityZoneIds"; const _AZv = "AvailabilityZones"; const _Ac = "Accept"; const _Acc = "Accelerators"; @@ -93069,6 +93102,7 @@ const _aVS = "attributeValueSet"; const _aZ = "availabilityZone"; const _aZG = "availabilityZoneGroup"; const _aZI = "availabilityZoneId"; +const _aZIS = "availabilityZoneIdSet"; const _aZIv = "availabilityZoneInfo"; const _aZS = "availabilityZoneSet"; const _ac = "acl"; diff --git a/clients/client-ecr-public/CHANGELOG.md b/clients/client-ecr-public/CHANGELOG.md index 6f2622ebb624..066c142ff976 100644 --- a/clients/client-ecr-public/CHANGELOG.md +++ b/clients/client-ecr-public/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ecr-public + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ecr-public diff --git a/clients/client-ecr-public/package.json b/clients/client-ecr-public/package.json index 0a57ab8c8e3d..b8a010760e1c 100644 --- a/clients/client-ecr-public/package.json +++ b/clients/client-ecr-public/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ecr-public", "description": "AWS SDK for JavaScript Ecr Public Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ecr-public", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-ecr/CHANGELOG.md b/clients/client-ecr/CHANGELOG.md index 58658b934301..665e21a614e0 100644 --- a/clients/client-ecr/CHANGELOG.md +++ b/clients/client-ecr/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ecr + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ecr diff --git a/clients/client-ecr/package.json b/clients/client-ecr/package.json index 07d07c8086ff..ea1998a12f31 100644 --- a/clients/client-ecr/package.json +++ b/clients/client-ecr/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ecr", "description": "AWS SDK for JavaScript Ecr Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ecr", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-ecs/CHANGELOG.md b/clients/client-ecs/CHANGELOG.md index 22683c5a5707..2933e04b2bd2 100644 --- a/clients/client-ecs/CHANGELOG.md +++ b/clients/client-ecs/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ecs + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ecs diff --git a/clients/client-ecs/package.json b/clients/client-ecs/package.json index 6da0ef32cc8e..d47b9c2834b0 100644 --- a/clients/client-ecs/package.json +++ b/clients/client-ecs/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ecs", "description": "AWS SDK for JavaScript Ecs Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ecs", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-efs/CHANGELOG.md b/clients/client-efs/CHANGELOG.md index 7dc57821901a..f247de367c3e 100644 --- a/clients/client-efs/CHANGELOG.md +++ b/clients/client-efs/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-efs + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-efs diff --git a/clients/client-efs/package.json b/clients/client-efs/package.json index 268bf583027a..3fbc130a1f24 100644 --- a/clients/client-efs/package.json +++ b/clients/client-efs/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-efs", "description": "AWS SDK for JavaScript Efs Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-efs", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-eks-auth/CHANGELOG.md b/clients/client-eks-auth/CHANGELOG.md index a20683b9b486..cb388a687a70 100644 --- a/clients/client-eks-auth/CHANGELOG.md +++ b/clients/client-eks-auth/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-eks-auth + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-eks-auth diff --git a/clients/client-eks-auth/package.json b/clients/client-eks-auth/package.json index 7633b3874643..055414d7b156 100644 --- a/clients/client-eks-auth/package.json +++ b/clients/client-eks-auth/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-eks-auth", "description": "AWS SDK for JavaScript Eks Auth Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-eks-auth", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-eks/CHANGELOG.md b/clients/client-eks/CHANGELOG.md index b9071cd8895a..e67ed24c2757 100644 --- a/clients/client-eks/CHANGELOG.md +++ b/clients/client-eks/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-eks + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-eks diff --git a/clients/client-eks/package.json b/clients/client-eks/package.json index 45bf5fe108d5..08ef5c1a6701 100644 --- a/clients/client-eks/package.json +++ b/clients/client-eks/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-eks", "description": "AWS SDK for JavaScript Eks Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-eks", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elastic-beanstalk/CHANGELOG.md b/clients/client-elastic-beanstalk/CHANGELOG.md index ee2290f8b734..3466b7678768 100644 --- a/clients/client-elastic-beanstalk/CHANGELOG.md +++ b/clients/client-elastic-beanstalk/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elastic-beanstalk + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elastic-beanstalk diff --git a/clients/client-elastic-beanstalk/package.json b/clients/client-elastic-beanstalk/package.json index 8535e324af14..20128e9ed49a 100644 --- a/clients/client-elastic-beanstalk/package.json +++ b/clients/client-elastic-beanstalk/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elastic-beanstalk", "description": "AWS SDK for JavaScript Elastic Beanstalk Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elastic-beanstalk", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elastic-load-balancing-v2/CHANGELOG.md b/clients/client-elastic-load-balancing-v2/CHANGELOG.md index 941d3c5a4a24..dfa3b8a454c4 100644 --- a/clients/client-elastic-load-balancing-v2/CHANGELOG.md +++ b/clients/client-elastic-load-balancing-v2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elastic-load-balancing-v2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elastic-load-balancing-v2 diff --git a/clients/client-elastic-load-balancing-v2/package.json b/clients/client-elastic-load-balancing-v2/package.json index 76229715815e..ad62ed565ee9 100644 --- a/clients/client-elastic-load-balancing-v2/package.json +++ b/clients/client-elastic-load-balancing-v2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elastic-load-balancing-v2", "description": "AWS SDK for JavaScript Elastic Load Balancing V2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elastic-load-balancing-v2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elastic-load-balancing/CHANGELOG.md b/clients/client-elastic-load-balancing/CHANGELOG.md index e68263a56c98..d12abadc279d 100644 --- a/clients/client-elastic-load-balancing/CHANGELOG.md +++ b/clients/client-elastic-load-balancing/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elastic-load-balancing + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elastic-load-balancing diff --git a/clients/client-elastic-load-balancing/package.json b/clients/client-elastic-load-balancing/package.json index 5cf9aced13e9..609d0289087a 100644 --- a/clients/client-elastic-load-balancing/package.json +++ b/clients/client-elastic-load-balancing/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elastic-load-balancing", "description": "AWS SDK for JavaScript Elastic Load Balancing Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elastic-load-balancing", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elastic-transcoder/CHANGELOG.md b/clients/client-elastic-transcoder/CHANGELOG.md index 918e9c10ce2a..0770f2cc6891 100644 --- a/clients/client-elastic-transcoder/CHANGELOG.md +++ b/clients/client-elastic-transcoder/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elastic-transcoder + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elastic-transcoder diff --git a/clients/client-elastic-transcoder/package.json b/clients/client-elastic-transcoder/package.json index f753875bdddc..7580256a1c54 100644 --- a/clients/client-elastic-transcoder/package.json +++ b/clients/client-elastic-transcoder/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elastic-transcoder", "description": "AWS SDK for JavaScript Elastic Transcoder Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elastic-transcoder", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elasticache/CHANGELOG.md b/clients/client-elasticache/CHANGELOG.md index 8b77328b39b0..28e7af626798 100644 --- a/clients/client-elasticache/CHANGELOG.md +++ b/clients/client-elasticache/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elasticache + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elasticache diff --git a/clients/client-elasticache/package.json b/clients/client-elasticache/package.json index c943b1c5e124..c249fdda101a 100644 --- a/clients/client-elasticache/package.json +++ b/clients/client-elasticache/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elasticache", "description": "AWS SDK for JavaScript Elasticache Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elasticache", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-elasticsearch-service/CHANGELOG.md b/clients/client-elasticsearch-service/CHANGELOG.md index eaf37264198c..472f3f77da7c 100644 --- a/clients/client-elasticsearch-service/CHANGELOG.md +++ b/clients/client-elasticsearch-service/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-elasticsearch-service + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-elasticsearch-service diff --git a/clients/client-elasticsearch-service/package.json b/clients/client-elasticsearch-service/package.json index 872ad078f5f6..79953348aa71 100644 --- a/clients/client-elasticsearch-service/package.json +++ b/clients/client-elasticsearch-service/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-elasticsearch-service", "description": "AWS SDK for JavaScript Elasticsearch Service Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-elasticsearch-service", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-emr-containers/CHANGELOG.md b/clients/client-emr-containers/CHANGELOG.md index 5a586d8fb3c9..59d56af29c7c 100644 --- a/clients/client-emr-containers/CHANGELOG.md +++ b/clients/client-emr-containers/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-emr-containers + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-emr-containers diff --git a/clients/client-emr-containers/package.json b/clients/client-emr-containers/package.json index 74c914633a84..2f5ed827eb16 100644 --- a/clients/client-emr-containers/package.json +++ b/clients/client-emr-containers/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-emr-containers", "description": "AWS SDK for JavaScript Emr Containers Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-emr-containers", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-emr-serverless/CHANGELOG.md b/clients/client-emr-serverless/CHANGELOG.md index fa5e2adb7094..e46c8438c61c 100644 --- a/clients/client-emr-serverless/CHANGELOG.md +++ b/clients/client-emr-serverless/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-emr-serverless + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-emr-serverless diff --git a/clients/client-emr-serverless/package.json b/clients/client-emr-serverless/package.json index 20af1afb5ade..deaba5d8e07a 100644 --- a/clients/client-emr-serverless/package.json +++ b/clients/client-emr-serverless/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-emr-serverless", "description": "AWS SDK for JavaScript Emr Serverless Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-emr-serverless", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-emr/CHANGELOG.md b/clients/client-emr/CHANGELOG.md index bb9edc497f1d..97c6fdad7da5 100644 --- a/clients/client-emr/CHANGELOG.md +++ b/clients/client-emr/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-emr + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-emr diff --git a/clients/client-emr/package.json b/clients/client-emr/package.json index f0717ffab5c6..e6f65fc59882 100644 --- a/clients/client-emr/package.json +++ b/clients/client-emr/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-emr", "description": "AWS SDK for JavaScript Emr Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-emr", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-entityresolution/CHANGELOG.md b/clients/client-entityresolution/CHANGELOG.md index 87e30c45a41d..362b74e75f49 100644 --- a/clients/client-entityresolution/CHANGELOG.md +++ b/clients/client-entityresolution/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-entityresolution + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-entityresolution diff --git a/clients/client-entityresolution/package.json b/clients/client-entityresolution/package.json index 5ffb4f9980c7..dc7111e9cb51 100644 --- a/clients/client-entityresolution/package.json +++ b/clients/client-entityresolution/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-entityresolution", "description": "AWS SDK for JavaScript Entityresolution Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-entityresolution", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-eventbridge/CHANGELOG.md b/clients/client-eventbridge/CHANGELOG.md index 699f8cabf466..f9485dcf94a6 100644 --- a/clients/client-eventbridge/CHANGELOG.md +++ b/clients/client-eventbridge/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-eventbridge + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-eventbridge diff --git a/clients/client-eventbridge/package.json b/clients/client-eventbridge/package.json index e371ea5013d9..0d8d89ec12b5 100644 --- a/clients/client-eventbridge/package.json +++ b/clients/client-eventbridge/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-eventbridge", "description": "AWS SDK for JavaScript Eventbridge Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-eventbridge", @@ -34,28 +34,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-evidently/CHANGELOG.md b/clients/client-evidently/CHANGELOG.md index 2e6323436a42..e6c6cc996b8c 100644 --- a/clients/client-evidently/CHANGELOG.md +++ b/clients/client-evidently/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-evidently + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-evidently diff --git a/clients/client-evidently/package.json b/clients/client-evidently/package.json index b0869d3c1cb2..45184834ea5f 100644 --- a/clients/client-evidently/package.json +++ b/clients/client-evidently/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-evidently", "description": "AWS SDK for JavaScript Evidently Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-evidently", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-finspace-data/CHANGELOG.md b/clients/client-finspace-data/CHANGELOG.md index 3a32e6851af3..31d580b605bd 100644 --- a/clients/client-finspace-data/CHANGELOG.md +++ b/clients/client-finspace-data/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-finspace-data + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-finspace-data diff --git a/clients/client-finspace-data/package.json b/clients/client-finspace-data/package.json index 0b6e0182820f..6ec49e1f357c 100644 --- a/clients/client-finspace-data/package.json +++ b/clients/client-finspace-data/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-finspace-data", "description": "AWS SDK for JavaScript Finspace Data Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-finspace-data", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-finspace/CHANGELOG.md b/clients/client-finspace/CHANGELOG.md index dbcfbcf21dcd..1d2bdd7346df 100644 --- a/clients/client-finspace/CHANGELOG.md +++ b/clients/client-finspace/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-finspace + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-finspace diff --git a/clients/client-finspace/package.json b/clients/client-finspace/package.json index e8fd40e2621d..e9843197920e 100644 --- a/clients/client-finspace/package.json +++ b/clients/client-finspace/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-finspace", "description": "AWS SDK for JavaScript Finspace Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-finspace", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-firehose/CHANGELOG.md b/clients/client-firehose/CHANGELOG.md index fba9e57438f4..81320db14037 100644 --- a/clients/client-firehose/CHANGELOG.md +++ b/clients/client-firehose/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-firehose + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-firehose diff --git a/clients/client-firehose/package.json b/clients/client-firehose/package.json index 0da3540764ce..7b8467730979 100644 --- a/clients/client-firehose/package.json +++ b/clients/client-firehose/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-firehose", "description": "AWS SDK for JavaScript Firehose Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-firehose", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-fis/CHANGELOG.md b/clients/client-fis/CHANGELOG.md index 56996d9937c6..fc1c4fe9ccd6 100644 --- a/clients/client-fis/CHANGELOG.md +++ b/clients/client-fis/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-fis + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-fis diff --git a/clients/client-fis/package.json b/clients/client-fis/package.json index 4949e5a3aa98..a95fd33ed0b3 100644 --- a/clients/client-fis/package.json +++ b/clients/client-fis/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-fis", "description": "AWS SDK for JavaScript Fis Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-fis", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-fms/CHANGELOG.md b/clients/client-fms/CHANGELOG.md index da0e581dc7f1..d6feb5ca8455 100644 --- a/clients/client-fms/CHANGELOG.md +++ b/clients/client-fms/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-fms + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-fms diff --git a/clients/client-fms/package.json b/clients/client-fms/package.json index 617a76bd2290..62bda7e293c6 100644 --- a/clients/client-fms/package.json +++ b/clients/client-fms/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-fms", "description": "AWS SDK for JavaScript Fms Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-fms", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-forecast/CHANGELOG.md b/clients/client-forecast/CHANGELOG.md index e75554b69907..4bc56e94e89d 100644 --- a/clients/client-forecast/CHANGELOG.md +++ b/clients/client-forecast/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-forecast + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-forecast diff --git a/clients/client-forecast/package.json b/clients/client-forecast/package.json index d29811f57767..6d07a78d477b 100644 --- a/clients/client-forecast/package.json +++ b/clients/client-forecast/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-forecast", "description": "AWS SDK for JavaScript Forecast Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-forecast", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-forecastquery/CHANGELOG.md b/clients/client-forecastquery/CHANGELOG.md index 3dc85ed682d4..ca64ee0affff 100644 --- a/clients/client-forecastquery/CHANGELOG.md +++ b/clients/client-forecastquery/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-forecastquery + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-forecastquery diff --git a/clients/client-forecastquery/package.json b/clients/client-forecastquery/package.json index d80b268a8481..19be6276e3ad 100644 --- a/clients/client-forecastquery/package.json +++ b/clients/client-forecastquery/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-forecastquery", "description": "AWS SDK for JavaScript Forecastquery Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-forecastquery", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-frauddetector/CHANGELOG.md b/clients/client-frauddetector/CHANGELOG.md index 29457fc2085b..e1603a03153a 100644 --- a/clients/client-frauddetector/CHANGELOG.md +++ b/clients/client-frauddetector/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-frauddetector + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-frauddetector diff --git a/clients/client-frauddetector/package.json b/clients/client-frauddetector/package.json index 3c7ed2134cf0..08e693c492db 100644 --- a/clients/client-frauddetector/package.json +++ b/clients/client-frauddetector/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-frauddetector", "description": "AWS SDK for JavaScript Frauddetector Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-frauddetector", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-freetier/CHANGELOG.md b/clients/client-freetier/CHANGELOG.md index 7e3d7307dd79..16e16a0d5a7c 100644 --- a/clients/client-freetier/CHANGELOG.md +++ b/clients/client-freetier/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-freetier + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-freetier diff --git a/clients/client-freetier/package.json b/clients/client-freetier/package.json index 3ab201fe568a..dbcf7cd659f7 100644 --- a/clients/client-freetier/package.json +++ b/clients/client-freetier/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-freetier", "description": "AWS SDK for JavaScript Freetier Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-freetier", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-fsx/CHANGELOG.md b/clients/client-fsx/CHANGELOG.md index 2f6b81927b7a..48578a45c792 100644 --- a/clients/client-fsx/CHANGELOG.md +++ b/clients/client-fsx/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-fsx + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-fsx diff --git a/clients/client-fsx/package.json b/clients/client-fsx/package.json index 7f6c9dc84bd3..d78fcac20528 100644 --- a/clients/client-fsx/package.json +++ b/clients/client-fsx/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-fsx", "description": "AWS SDK for JavaScript Fsx Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-fsx", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-gamelift/CHANGELOG.md b/clients/client-gamelift/CHANGELOG.md index fe887a7161b5..ee297c9a6942 100644 --- a/clients/client-gamelift/CHANGELOG.md +++ b/clients/client-gamelift/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-gamelift + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-gamelift diff --git a/clients/client-gamelift/package.json b/clients/client-gamelift/package.json index 138c68b6dbc9..5fb911ebcfcd 100644 --- a/clients/client-gamelift/package.json +++ b/clients/client-gamelift/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-gamelift", "description": "AWS SDK for JavaScript Gamelift Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-gamelift", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-gameliftstreams/CHANGELOG.md b/clients/client-gameliftstreams/CHANGELOG.md index 5a781ec3e3a1..032ed194fcf2 100644 --- a/clients/client-gameliftstreams/CHANGELOG.md +++ b/clients/client-gameliftstreams/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-gameliftstreams + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-gameliftstreams diff --git a/clients/client-gameliftstreams/package.json b/clients/client-gameliftstreams/package.json index dd3f5ee625e0..d2d7c9276c13 100644 --- a/clients/client-gameliftstreams/package.json +++ b/clients/client-gameliftstreams/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-gameliftstreams", "description": "AWS SDK for JavaScript Gameliftstreams Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-geo-maps/CHANGELOG.md b/clients/client-geo-maps/CHANGELOG.md index b48960b130f6..1b91f3f48095 100644 --- a/clients/client-geo-maps/CHANGELOG.md +++ b/clients/client-geo-maps/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-geo-maps + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-geo-maps diff --git a/clients/client-geo-maps/package.json b/clients/client-geo-maps/package.json index b65787f1de7e..f662bae1fc6c 100644 --- a/clients/client-geo-maps/package.json +++ b/clients/client-geo-maps/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-geo-maps", "description": "AWS SDK for JavaScript Geo Maps Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-geo-places/CHANGELOG.md b/clients/client-geo-places/CHANGELOG.md index d9237ffbef2e..23d6080c8be2 100644 --- a/clients/client-geo-places/CHANGELOG.md +++ b/clients/client-geo-places/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-geo-places + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-geo-places diff --git a/clients/client-geo-places/package.json b/clients/client-geo-places/package.json index b3735434bebc..9046ae261b60 100644 --- a/clients/client-geo-places/package.json +++ b/clients/client-geo-places/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-geo-places", "description": "AWS SDK for JavaScript Geo Places Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-geo-routes/CHANGELOG.md b/clients/client-geo-routes/CHANGELOG.md index cdd97f1ad054..ab545eab30ff 100644 --- a/clients/client-geo-routes/CHANGELOG.md +++ b/clients/client-geo-routes/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-geo-routes + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-geo-routes diff --git a/clients/client-geo-routes/package.json b/clients/client-geo-routes/package.json index d4a2519aebc1..cfcf62f9e743 100644 --- a/clients/client-geo-routes/package.json +++ b/clients/client-geo-routes/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-geo-routes", "description": "AWS SDK for JavaScript Geo Routes Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-glacier/CHANGELOG.md b/clients/client-glacier/CHANGELOG.md index e2a1872431f8..957173bcf29f 100644 --- a/clients/client-glacier/CHANGELOG.md +++ b/clients/client-glacier/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-glacier + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-glacier diff --git a/clients/client-glacier/package.json b/clients/client-glacier/package.json index 4b4a2e301103..f6d1a0dcf901 100644 --- a/clients/client-glacier/package.json +++ b/clients/client-glacier/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-glacier", "description": "AWS SDK for JavaScript Glacier Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-glacier", @@ -34,28 +34,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-global-accelerator/CHANGELOG.md b/clients/client-global-accelerator/CHANGELOG.md index 08e34accfd02..ba273b492972 100644 --- a/clients/client-global-accelerator/CHANGELOG.md +++ b/clients/client-global-accelerator/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-global-accelerator + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-global-accelerator diff --git a/clients/client-global-accelerator/package.json b/clients/client-global-accelerator/package.json index c17d92ef7db0..3ba981d66d39 100644 --- a/clients/client-global-accelerator/package.json +++ b/clients/client-global-accelerator/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-global-accelerator", "description": "AWS SDK for JavaScript Global Accelerator Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-global-accelerator", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-glue/CHANGELOG.md b/clients/client-glue/CHANGELOG.md index 65634eafe72f..32a476ed92fc 100644 --- a/clients/client-glue/CHANGELOG.md +++ b/clients/client-glue/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-glue + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) diff --git a/clients/client-glue/package.json b/clients/client-glue/package.json index 9e17e20f21b7..d02252e6f771 100644 --- a/clients/client-glue/package.json +++ b/clients/client-glue/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-glue", "description": "AWS SDK for JavaScript Glue Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-glue", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-grafana/CHANGELOG.md b/clients/client-grafana/CHANGELOG.md index 6a47a643d9ad..7c323182d006 100644 --- a/clients/client-grafana/CHANGELOG.md +++ b/clients/client-grafana/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-grafana + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-grafana diff --git a/clients/client-grafana/package.json b/clients/client-grafana/package.json index 60d3e3b1af8d..821bfd2d8b41 100644 --- a/clients/client-grafana/package.json +++ b/clients/client-grafana/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-grafana", "description": "AWS SDK for JavaScript Grafana Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-grafana", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-greengrass/CHANGELOG.md b/clients/client-greengrass/CHANGELOG.md index e4cbeb75f53e..0a937404fb94 100644 --- a/clients/client-greengrass/CHANGELOG.md +++ b/clients/client-greengrass/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-greengrass + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-greengrass diff --git a/clients/client-greengrass/package.json b/clients/client-greengrass/package.json index da4cafb0e8a0..d95dd96c1500 100644 --- a/clients/client-greengrass/package.json +++ b/clients/client-greengrass/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-greengrass", "description": "AWS SDK for JavaScript Greengrass Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-greengrass", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-greengrassv2/CHANGELOG.md b/clients/client-greengrassv2/CHANGELOG.md index 0383bda6e79e..37249c429114 100644 --- a/clients/client-greengrassv2/CHANGELOG.md +++ b/clients/client-greengrassv2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-greengrassv2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-greengrassv2 diff --git a/clients/client-greengrassv2/package.json b/clients/client-greengrassv2/package.json index 83958352dc9f..dc7961d64583 100644 --- a/clients/client-greengrassv2/package.json +++ b/clients/client-greengrassv2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-greengrassv2", "description": "AWS SDK for JavaScript Greengrassv2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-greengrassv2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-groundstation/CHANGELOG.md b/clients/client-groundstation/CHANGELOG.md index 5e376454dc00..c5f21cf2d416 100644 --- a/clients/client-groundstation/CHANGELOG.md +++ b/clients/client-groundstation/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-groundstation + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-groundstation diff --git a/clients/client-groundstation/package.json b/clients/client-groundstation/package.json index 7e442ed7655a..c926f207f4c1 100644 --- a/clients/client-groundstation/package.json +++ b/clients/client-groundstation/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-groundstation", "description": "AWS SDK for JavaScript Groundstation Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-groundstation", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-guardduty/CHANGELOG.md b/clients/client-guardduty/CHANGELOG.md index e737423c7841..203a0a14a1a8 100644 --- a/clients/client-guardduty/CHANGELOG.md +++ b/clients/client-guardduty/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-guardduty + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-guardduty diff --git a/clients/client-guardduty/package.json b/clients/client-guardduty/package.json index e0b7621a0f91..ce36e75a60b6 100644 --- a/clients/client-guardduty/package.json +++ b/clients/client-guardduty/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-guardduty", "description": "AWS SDK for JavaScript Guardduty Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-guardduty", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-health/CHANGELOG.md b/clients/client-health/CHANGELOG.md index c3dff6c56188..68678bde974d 100644 --- a/clients/client-health/CHANGELOG.md +++ b/clients/client-health/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-health + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-health diff --git a/clients/client-health/package.json b/clients/client-health/package.json index d3851d900c95..41203b270180 100644 --- a/clients/client-health/package.json +++ b/clients/client-health/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-health", "description": "AWS SDK for JavaScript Health Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-health", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-healthlake/CHANGELOG.md b/clients/client-healthlake/CHANGELOG.md index 6aeb8fd00b9d..7e8e0d7888ee 100644 --- a/clients/client-healthlake/CHANGELOG.md +++ b/clients/client-healthlake/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-healthlake + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-healthlake diff --git a/clients/client-healthlake/package.json b/clients/client-healthlake/package.json index e8f057a6811e..102e62c0f0e8 100644 --- a/clients/client-healthlake/package.json +++ b/clients/client-healthlake/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-healthlake", "description": "AWS SDK for JavaScript Healthlake Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-healthlake", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iam/CHANGELOG.md b/clients/client-iam/CHANGELOG.md index 52d34f1af9e3..325077176a15 100644 --- a/clients/client-iam/CHANGELOG.md +++ b/clients/client-iam/CHANGELOG.md @@ -3,6 +3,17 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + + +### Features + +* **client-iam:** Updating the endpoint list for the Identity and access management (IAM) service ([854b130](https://github.com/aws/aws-sdk-js-v3/commit/854b130d81b2970401f4793b0fef0204a26569af)) + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iam diff --git a/clients/client-iam/package.json b/clients/client-iam/package.json index ca8ecb920d7f..fe9711d1bbd7 100644 --- a/clients/client-iam/package.json +++ b/clients/client-iam/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iam", "description": "AWS SDK for JavaScript Iam Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iam", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iam/src/endpoint/ruleset.ts b/clients/client-iam/src/endpoint/ruleset.ts index fb8b849491fb..c806d4d169ab 100644 --- a/clients/client-iam/src/endpoint/ruleset.ts +++ b/clients/client-iam/src/endpoint/ruleset.ts @@ -48,5 +48,5 @@ D={[I]:"getAttr",[J]:[{[K]:g},"supportsFIPS"]}, E={[I]:c,[J]:[true,{[I]:"getAttr",[J]:[{[K]:g},"supportsDualStack"]}]}, F={[N]:[{[O]:i,[P]:"{PartitionResult#implicitGlobalRegion}"}]}, G=[{[K]:"Region"}]; -const _data={version:"1.0",parameters:{UseDualStack:j,UseFIPS:j,Endpoint:k,Region:k},rules:[{conditions:[{[I]:b,[J]:[l]}],rules:[{conditions:[m],error:"Invalid Configuration: FIPS and custom endpoint are not supported",type:d},{rules:[{conditions:[n],error:"Invalid Configuration: Dualstack and custom endpoint are not supported",type:d},{endpoint:{url:l,[L]:o,[M]:o},type:e}],type:f}],type:f},{rules:[{conditions:[{[I]:b,[J]:G}],rules:[{conditions:[{[I]:"aws.partition",[J]:G,assign:g}],rules:[{conditions:[p,r,n],endpoint:{url:"https://iam.global.api.aws",[L]:s,[M]:o},type:e},{conditions:[p,m,n],endpoint:{url:"https://iam-fips.global.api.aws",[L]:s,[M]:o},type:e},{conditions:[t,r,n],endpoint:{url:"https://iam.global.api.amazonwebservices.com.cn",[L]:u,[M]:o},type:e},{conditions:[t,r,v],endpoint:{url:"https://iam.cn-north-1.amazonaws.com.cn",[L]:u,[M]:o},type:e},{conditions:[w,r,n],endpoint:x,type:e},{conditions:[w,m,n],endpoint:x,type:e},{conditions:[w,r,v],endpoint:y,type:e},{conditions:[w,m,v],endpoint:y,type:e},{conditions:[z,r,v],endpoint:{url:"https://iam.us-iso-east-1.c2s.ic.gov",[L]:A,[M]:o},type:e},{conditions:[z,m,v],endpoint:{url:"https://iam-fips.us-iso-east-1.c2s.ic.gov",[L]:A,[M]:o},type:e},{conditions:[B,r,v],endpoint:{url:"https://iam.us-isob-east-1.sc2s.sgov.gov",[L]:C,[M]:o},type:e},{conditions:[B,m,v],endpoint:{url:"https://iam-fips.us-isob-east-1.sc2s.sgov.gov",[L]:C,[M]:o},type:e},{conditions:[{[I]:h,[J]:[q,"aws-iso-e"]},r,v],endpoint:{url:"https://iam.eu-isoe-west-1.cloud.adc-e.uk",[L]:{[N]:[{[O]:i,[P]:"eu-isoe-west-1"}]},[M]:o},type:e},{conditions:[{[I]:h,[J]:[q,"aws-iso-f"]},r,v],endpoint:{url:"https://iam.us-isof-south-1.csp.hci.ic.gov",[L]:{[N]:[{[O]:i,[P]:"us-isof-south-1"}]},[M]:o},type:e},{conditions:[m,n],rules:[{conditions:[{[I]:c,[J]:[a,D]},E],rules:[{endpoint:{url:"https://iam-fips.{PartitionResult#dualStackDnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"FIPS and DualStack are enabled, but this partition does not support one or both",type:d}],type:f},{conditions:[m,v],rules:[{conditions:[{[I]:c,[J]:[D,a]}],rules:[{endpoint:{url:"https://iam-fips.{PartitionResult#dnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"FIPS is enabled but this partition does not support FIPS",type:d}],type:f},{conditions:[r,n],rules:[{conditions:[E],rules:[{endpoint:{url:"https://iam.{PartitionResult#dualStackDnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"DualStack is enabled but this partition does not support DualStack",type:d}],type:f},{endpoint:{url:"https://iam.{PartitionResult#dnsSuffix}",[L]:F,[M]:o},type:e}],type:f}],type:f},{error:"Invalid Configuration: Missing Region",type:d}],type:f}]}; +const _data={version:"1.0",parameters:{UseDualStack:j,UseFIPS:j,Endpoint:k,Region:k},rules:[{conditions:[{[I]:b,[J]:[l]}],rules:[{conditions:[m],error:"Invalid Configuration: FIPS and custom endpoint are not supported",type:d},{rules:[{conditions:[n],error:"Invalid Configuration: Dualstack and custom endpoint are not supported",type:d},{endpoint:{url:l,[L]:o,[M]:o},type:e}],type:f}],type:f},{rules:[{conditions:[{[I]:b,[J]:G}],rules:[{conditions:[{[I]:"aws.partition",[J]:G,assign:g}],rules:[{conditions:[p,r,n],endpoint:{url:"https://iam.global.api.aws",[L]:s,[M]:o},type:e},{conditions:[p,m,n],endpoint:{url:"https://iam-fips.global.api.aws",[L]:s,[M]:o},type:e},{conditions:[t,r,n],endpoint:{url:"https://iam.global.api.amazonwebservices.com.cn",[L]:u,[M]:o},type:e},{conditions:[t,r,v],endpoint:{url:"https://iam.cn-north-1.amazonaws.com.cn",[L]:u,[M]:o},type:e},{conditions:[w,r,n],endpoint:x,type:e},{conditions:[w,m,n],endpoint:x,type:e},{conditions:[w,r,v],endpoint:y,type:e},{conditions:[w,m,v],endpoint:y,type:e},{conditions:[z,r,v],endpoint:{url:"https://iam.us-iso-east-1.c2s.ic.gov",[L]:A,[M]:o},type:e},{conditions:[z,m,v],endpoint:{url:"https://iam-fips.us-iso-east-1.c2s.ic.gov",[L]:A,[M]:o},type:e},{conditions:[B,r,v],endpoint:{url:"https://iam.us-isob-east-1.sc2s.sgov.gov",[L]:C,[M]:o},type:e},{conditions:[B,m,v],endpoint:{url:"https://iam-fips.us-isob-east-1.sc2s.sgov.gov",[L]:C,[M]:o},type:e},{conditions:[{[I]:h,[J]:[q,"aws-iso-e"]},r,v],endpoint:{url:"https://iam.eu-isoe-west-1.cloud.adc-e.uk",[L]:{[N]:[{[O]:i,[P]:"eu-isoe-west-1"}]},[M]:o},type:e},{conditions:[{[I]:h,[J]:[q,"aws-iso-f"]},r,v],endpoint:{url:"https://iam.us-isof-south-1.csp.hci.ic.gov",[L]:{[N]:[{[O]:i,[P]:"us-isof-south-1"}]},[M]:o},type:e},{conditions:[{[I]:h,[J]:[q,"aws-eusc"]},r,v],endpoint:{url:"https://iam.eusc-de-east-1.amazonaws.eu",[L]:{[N]:[{[O]:i,[P]:"eusc-de-east-1"}]},[M]:o},type:e},{conditions:[m,n],rules:[{conditions:[{[I]:c,[J]:[a,D]},E],rules:[{endpoint:{url:"https://iam-fips.{PartitionResult#dualStackDnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"FIPS and DualStack are enabled, but this partition does not support one or both",type:d}],type:f},{conditions:[m,v],rules:[{conditions:[{[I]:c,[J]:[D,a]}],rules:[{endpoint:{url:"https://iam-fips.{PartitionResult#dnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"FIPS is enabled but this partition does not support FIPS",type:d}],type:f},{conditions:[r,n],rules:[{conditions:[E],rules:[{endpoint:{url:"https://iam.{PartitionResult#dualStackDnsSuffix}",[L]:F,[M]:o},type:e}],type:f},{error:"DualStack is enabled but this partition does not support DualStack",type:d}],type:f},{endpoint:{url:"https://iam.{PartitionResult#dnsSuffix}",[L]:F,[M]:o},type:e}],type:f}],type:f},{error:"Invalid Configuration: Missing Region",type:d}],type:f}]}; export const ruleSet: RuleSetObject = _data; diff --git a/clients/client-identitystore/CHANGELOG.md b/clients/client-identitystore/CHANGELOG.md index 6af838f5d645..cc38babde9fb 100644 --- a/clients/client-identitystore/CHANGELOG.md +++ b/clients/client-identitystore/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-identitystore + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-identitystore diff --git a/clients/client-identitystore/package.json b/clients/client-identitystore/package.json index e3fc868e422b..050544a58ed3 100644 --- a/clients/client-identitystore/package.json +++ b/clients/client-identitystore/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-identitystore", "description": "AWS SDK for JavaScript Identitystore Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-identitystore", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-imagebuilder/CHANGELOG.md b/clients/client-imagebuilder/CHANGELOG.md index 34d4869d1529..5afd66350eda 100644 --- a/clients/client-imagebuilder/CHANGELOG.md +++ b/clients/client-imagebuilder/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-imagebuilder + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-imagebuilder diff --git a/clients/client-imagebuilder/package.json b/clients/client-imagebuilder/package.json index 8d637f442071..60015c2d2bcb 100644 --- a/clients/client-imagebuilder/package.json +++ b/clients/client-imagebuilder/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-imagebuilder", "description": "AWS SDK for JavaScript Imagebuilder Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-imagebuilder", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-inspector-scan/CHANGELOG.md b/clients/client-inspector-scan/CHANGELOG.md index 13aa6be0d149..691f482bd55f 100644 --- a/clients/client-inspector-scan/CHANGELOG.md +++ b/clients/client-inspector-scan/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-inspector-scan + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-inspector-scan diff --git a/clients/client-inspector-scan/package.json b/clients/client-inspector-scan/package.json index 42b54ee20e0d..f5ea185dcb7e 100644 --- a/clients/client-inspector-scan/package.json +++ b/clients/client-inspector-scan/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-inspector-scan", "description": "AWS SDK for JavaScript Inspector Scan Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-inspector-scan", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-inspector/CHANGELOG.md b/clients/client-inspector/CHANGELOG.md index ce3cbd38cd48..ddea5a8c3275 100644 --- a/clients/client-inspector/CHANGELOG.md +++ b/clients/client-inspector/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-inspector + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-inspector diff --git a/clients/client-inspector/package.json b/clients/client-inspector/package.json index 8745d3843193..592cfe5c6889 100644 --- a/clients/client-inspector/package.json +++ b/clients/client-inspector/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-inspector", "description": "AWS SDK for JavaScript Inspector Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-inspector", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-inspector2/CHANGELOG.md b/clients/client-inspector2/CHANGELOG.md index fe492287b34a..78fa6b0f7582 100644 --- a/clients/client-inspector2/CHANGELOG.md +++ b/clients/client-inspector2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-inspector2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-inspector2 diff --git a/clients/client-inspector2/package.json b/clients/client-inspector2/package.json index da296ccdd88a..34e8a695f579 100644 --- a/clients/client-inspector2/package.json +++ b/clients/client-inspector2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-inspector2", "description": "AWS SDK for JavaScript Inspector2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-inspector2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-internetmonitor/CHANGELOG.md b/clients/client-internetmonitor/CHANGELOG.md index fb82a1429012..2895347be276 100644 --- a/clients/client-internetmonitor/CHANGELOG.md +++ b/clients/client-internetmonitor/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-internetmonitor + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-internetmonitor diff --git a/clients/client-internetmonitor/package.json b/clients/client-internetmonitor/package.json index ffa3d261a360..655e6c3910f0 100644 --- a/clients/client-internetmonitor/package.json +++ b/clients/client-internetmonitor/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-internetmonitor", "description": "AWS SDK for JavaScript Internetmonitor Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-internetmonitor", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-invoicing/CHANGELOG.md b/clients/client-invoicing/CHANGELOG.md index abad18d24911..7c9a11dee20f 100644 --- a/clients/client-invoicing/CHANGELOG.md +++ b/clients/client-invoicing/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-invoicing + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-invoicing diff --git a/clients/client-invoicing/package.json b/clients/client-invoicing/package.json index 7978e6b1084b..2f2971268eb5 100644 --- a/clients/client-invoicing/package.json +++ b/clients/client-invoicing/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-invoicing", "description": "AWS SDK for JavaScript Invoicing Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iot-data-plane/CHANGELOG.md b/clients/client-iot-data-plane/CHANGELOG.md index f414c36d7b09..e8796aedfac4 100644 --- a/clients/client-iot-data-plane/CHANGELOG.md +++ b/clients/client-iot-data-plane/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-data-plane + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-data-plane diff --git a/clients/client-iot-data-plane/package.json b/clients/client-iot-data-plane/package.json index 0d519fb4cb2b..cd38c5b8205e 100644 --- a/clients/client-iot-data-plane/package.json +++ b/clients/client-iot-data-plane/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-data-plane", "description": "AWS SDK for JavaScript Iot Data Plane Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot-data-plane", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-iot-events-data/CHANGELOG.md b/clients/client-iot-events-data/CHANGELOG.md index 4963e7032c7a..8059cf89b1b9 100644 --- a/clients/client-iot-events-data/CHANGELOG.md +++ b/clients/client-iot-events-data/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-events-data + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-events-data diff --git a/clients/client-iot-events-data/package.json b/clients/client-iot-events-data/package.json index 94b738d07ad0..c4112a64eef2 100644 --- a/clients/client-iot-events-data/package.json +++ b/clients/client-iot-events-data/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-events-data", "description": "AWS SDK for JavaScript Iot Events Data Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot-events-data", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iot-events/CHANGELOG.md b/clients/client-iot-events/CHANGELOG.md index 5471fb12fba6..a62b9f90ef77 100644 --- a/clients/client-iot-events/CHANGELOG.md +++ b/clients/client-iot-events/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-events + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-events diff --git a/clients/client-iot-events/package.json b/clients/client-iot-events/package.json index 64cab0304bbc..fd355734db6f 100644 --- a/clients/client-iot-events/package.json +++ b/clients/client-iot-events/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-events", "description": "AWS SDK for JavaScript Iot Events Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot-events", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iot-jobs-data-plane/CHANGELOG.md b/clients/client-iot-jobs-data-plane/CHANGELOG.md index 64f4dcdc1e41..df4e31e8d90f 100644 --- a/clients/client-iot-jobs-data-plane/CHANGELOG.md +++ b/clients/client-iot-jobs-data-plane/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-jobs-data-plane + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-jobs-data-plane diff --git a/clients/client-iot-jobs-data-plane/package.json b/clients/client-iot-jobs-data-plane/package.json index b83208daf532..4cec96a9e9d8 100644 --- a/clients/client-iot-jobs-data-plane/package.json +++ b/clients/client-iot-jobs-data-plane/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-jobs-data-plane", "description": "AWS SDK for JavaScript Iot Jobs Data Plane Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot-jobs-data-plane", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iot-managed-integrations/CHANGELOG.md b/clients/client-iot-managed-integrations/CHANGELOG.md index ad8e3d35f304..f1fdf312c2e0 100644 --- a/clients/client-iot-managed-integrations/CHANGELOG.md +++ b/clients/client-iot-managed-integrations/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-managed-integrations + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-managed-integrations diff --git a/clients/client-iot-managed-integrations/package.json b/clients/client-iot-managed-integrations/package.json index 1538852746d3..84957295147c 100644 --- a/clients/client-iot-managed-integrations/package.json +++ b/clients/client-iot-managed-integrations/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-managed-integrations", "description": "AWS SDK for JavaScript Iot Managed Integrations Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iot-wireless/CHANGELOG.md b/clients/client-iot-wireless/CHANGELOG.md index 697c0bb399c0..fdb190d89f07 100644 --- a/clients/client-iot-wireless/CHANGELOG.md +++ b/clients/client-iot-wireless/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot-wireless + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot-wireless diff --git a/clients/client-iot-wireless/package.json b/clients/client-iot-wireless/package.json index 165f07238313..0ce413b4f7d6 100644 --- a/clients/client-iot-wireless/package.json +++ b/clients/client-iot-wireless/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot-wireless", "description": "AWS SDK for JavaScript Iot Wireless Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot-wireless", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-iot/CHANGELOG.md b/clients/client-iot/CHANGELOG.md index 73e6f810fba8..613a4eda032f 100644 --- a/clients/client-iot/CHANGELOG.md +++ b/clients/client-iot/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iot + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iot diff --git a/clients/client-iot/package.json b/clients/client-iot/package.json index 6b9a7a29485b..f1feea839c7a 100644 --- a/clients/client-iot/package.json +++ b/clients/client-iot/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iot", "description": "AWS SDK for JavaScript Iot Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iot", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotanalytics/CHANGELOG.md b/clients/client-iotanalytics/CHANGELOG.md index e52a2426ec42..f014b6c27fb9 100644 --- a/clients/client-iotanalytics/CHANGELOG.md +++ b/clients/client-iotanalytics/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotanalytics + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotanalytics diff --git a/clients/client-iotanalytics/package.json b/clients/client-iotanalytics/package.json index fd15565716a7..052a2489a504 100644 --- a/clients/client-iotanalytics/package.json +++ b/clients/client-iotanalytics/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotanalytics", "description": "AWS SDK for JavaScript Iotanalytics Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotanalytics", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotdeviceadvisor/CHANGELOG.md b/clients/client-iotdeviceadvisor/CHANGELOG.md index 516b0da20e7a..4c0b580477c5 100644 --- a/clients/client-iotdeviceadvisor/CHANGELOG.md +++ b/clients/client-iotdeviceadvisor/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotdeviceadvisor + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotdeviceadvisor diff --git a/clients/client-iotdeviceadvisor/package.json b/clients/client-iotdeviceadvisor/package.json index 4b57c4216abc..1d67a48ea889 100644 --- a/clients/client-iotdeviceadvisor/package.json +++ b/clients/client-iotdeviceadvisor/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotdeviceadvisor", "description": "AWS SDK for JavaScript Iotdeviceadvisor Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotdeviceadvisor", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotfleethub/CHANGELOG.md b/clients/client-iotfleethub/CHANGELOG.md index fb78c8fa7a72..5805a524a8a6 100644 --- a/clients/client-iotfleethub/CHANGELOG.md +++ b/clients/client-iotfleethub/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotfleethub + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotfleethub diff --git a/clients/client-iotfleethub/package.json b/clients/client-iotfleethub/package.json index cc4401fb825a..1b1863971a6b 100644 --- a/clients/client-iotfleethub/package.json +++ b/clients/client-iotfleethub/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotfleethub", "description": "AWS SDK for JavaScript Iotfleethub Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotfleethub", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotfleetwise/CHANGELOG.md b/clients/client-iotfleetwise/CHANGELOG.md index 5ecdccb23074..7f87f82d0026 100644 --- a/clients/client-iotfleetwise/CHANGELOG.md +++ b/clients/client-iotfleetwise/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotfleetwise + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotfleetwise diff --git a/clients/client-iotfleetwise/package.json b/clients/client-iotfleetwise/package.json index 9b0a0ebf263d..f90b730f1dc1 100644 --- a/clients/client-iotfleetwise/package.json +++ b/clients/client-iotfleetwise/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotfleetwise", "description": "AWS SDK for JavaScript Iotfleetwise Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotfleetwise", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotsecuretunneling/CHANGELOG.md b/clients/client-iotsecuretunneling/CHANGELOG.md index a2e208b7b329..2d567665072f 100644 --- a/clients/client-iotsecuretunneling/CHANGELOG.md +++ b/clients/client-iotsecuretunneling/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotsecuretunneling + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotsecuretunneling diff --git a/clients/client-iotsecuretunneling/package.json b/clients/client-iotsecuretunneling/package.json index 3e0ed606644f..9b4aa154cf57 100644 --- a/clients/client-iotsecuretunneling/package.json +++ b/clients/client-iotsecuretunneling/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotsecuretunneling", "description": "AWS SDK for JavaScript Iotsecuretunneling Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotsecuretunneling", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotsitewise/CHANGELOG.md b/clients/client-iotsitewise/CHANGELOG.md index 629bdaa8b5e6..2257b35cb7a6 100644 --- a/clients/client-iotsitewise/CHANGELOG.md +++ b/clients/client-iotsitewise/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotsitewise + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotsitewise diff --git a/clients/client-iotsitewise/package.json b/clients/client-iotsitewise/package.json index a1fc0162fcf6..aa9529b8e993 100644 --- a/clients/client-iotsitewise/package.json +++ b/clients/client-iotsitewise/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotsitewise", "description": "AWS SDK for JavaScript Iotsitewise Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotsitewise", @@ -31,7 +31,7 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/eventstream-serde-browser": "^4.0.2", "@smithy/eventstream-serde-config-resolver": "^4.1.0", @@ -40,22 +40,22 @@ "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iotthingsgraph/CHANGELOG.md b/clients/client-iotthingsgraph/CHANGELOG.md index 6df253ac2dba..ac428bab09a9 100644 --- a/clients/client-iotthingsgraph/CHANGELOG.md +++ b/clients/client-iotthingsgraph/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iotthingsgraph + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iotthingsgraph diff --git a/clients/client-iotthingsgraph/package.json b/clients/client-iotthingsgraph/package.json index fad4f3790e6d..4121a5a715ac 100644 --- a/clients/client-iotthingsgraph/package.json +++ b/clients/client-iotthingsgraph/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iotthingsgraph", "description": "AWS SDK for JavaScript Iotthingsgraph Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iotthingsgraph", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-iottwinmaker/CHANGELOG.md b/clients/client-iottwinmaker/CHANGELOG.md index b8176ad77a5f..e0740abfc5c8 100644 --- a/clients/client-iottwinmaker/CHANGELOG.md +++ b/clients/client-iottwinmaker/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-iottwinmaker + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-iottwinmaker diff --git a/clients/client-iottwinmaker/package.json b/clients/client-iottwinmaker/package.json index 606b8f97ad45..d55b3a53beb7 100644 --- a/clients/client-iottwinmaker/package.json +++ b/clients/client-iottwinmaker/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-iottwinmaker", "description": "AWS SDK for JavaScript Iottwinmaker Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-iottwinmaker", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-ivs-realtime/CHANGELOG.md b/clients/client-ivs-realtime/CHANGELOG.md index 723030b786cd..4f37c01e6265 100644 --- a/clients/client-ivs-realtime/CHANGELOG.md +++ b/clients/client-ivs-realtime/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ivs-realtime + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ivs-realtime diff --git a/clients/client-ivs-realtime/package.json b/clients/client-ivs-realtime/package.json index 613c00621f45..9d5314c4a901 100644 --- a/clients/client-ivs-realtime/package.json +++ b/clients/client-ivs-realtime/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ivs-realtime", "description": "AWS SDK for JavaScript Ivs Realtime Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ivs-realtime", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-ivs/CHANGELOG.md b/clients/client-ivs/CHANGELOG.md index a784f8671a23..bd070fad2aeb 100644 --- a/clients/client-ivs/CHANGELOG.md +++ b/clients/client-ivs/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ivs + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ivs diff --git a/clients/client-ivs/package.json b/clients/client-ivs/package.json index 7ad48d50d5a7..8b5bb1056e1f 100644 --- a/clients/client-ivs/package.json +++ b/clients/client-ivs/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ivs", "description": "AWS SDK for JavaScript Ivs Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ivs", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-ivschat/CHANGELOG.md b/clients/client-ivschat/CHANGELOG.md index 2acca91a26f4..c61e8a62aed2 100644 --- a/clients/client-ivschat/CHANGELOG.md +++ b/clients/client-ivschat/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-ivschat + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-ivschat diff --git a/clients/client-ivschat/package.json b/clients/client-ivschat/package.json index 228c03158980..6f9d473c5246 100644 --- a/clients/client-ivschat/package.json +++ b/clients/client-ivschat/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-ivschat", "description": "AWS SDK for JavaScript Ivschat Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-ivschat", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kafka/CHANGELOG.md b/clients/client-kafka/CHANGELOG.md index 07b89d1376db..eb9578940c60 100644 --- a/clients/client-kafka/CHANGELOG.md +++ b/clients/client-kafka/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kafka + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kafka diff --git a/clients/client-kafka/package.json b/clients/client-kafka/package.json index 7cf21e9b0944..136448980bee 100644 --- a/clients/client-kafka/package.json +++ b/clients/client-kafka/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kafka", "description": "AWS SDK for JavaScript Kafka Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kafka", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kafkaconnect/CHANGELOG.md b/clients/client-kafkaconnect/CHANGELOG.md index 1ba77c9f250a..ce817c2e3a8f 100644 --- a/clients/client-kafkaconnect/CHANGELOG.md +++ b/clients/client-kafkaconnect/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kafkaconnect + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kafkaconnect diff --git a/clients/client-kafkaconnect/package.json b/clients/client-kafkaconnect/package.json index fae23546a868..15381d3dffe2 100644 --- a/clients/client-kafkaconnect/package.json +++ b/clients/client-kafkaconnect/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kafkaconnect", "description": "AWS SDK for JavaScript Kafkaconnect Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kafkaconnect", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kendra-ranking/CHANGELOG.md b/clients/client-kendra-ranking/CHANGELOG.md index 6de39443fc8e..25079d43217a 100644 --- a/clients/client-kendra-ranking/CHANGELOG.md +++ b/clients/client-kendra-ranking/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kendra-ranking + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kendra-ranking diff --git a/clients/client-kendra-ranking/package.json b/clients/client-kendra-ranking/package.json index 70e7e4936ce7..fc2e22dcf47c 100644 --- a/clients/client-kendra-ranking/package.json +++ b/clients/client-kendra-ranking/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kendra-ranking", "description": "AWS SDK for JavaScript Kendra Ranking Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kendra-ranking", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kendra/CHANGELOG.md b/clients/client-kendra/CHANGELOG.md index 807c54890fd6..70b635a554d9 100644 --- a/clients/client-kendra/CHANGELOG.md +++ b/clients/client-kendra/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kendra + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kendra diff --git a/clients/client-kendra/package.json b/clients/client-kendra/package.json index ddb7c6ab1b5c..9716f4060299 100644 --- a/clients/client-kendra/package.json +++ b/clients/client-kendra/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kendra", "description": "AWS SDK for JavaScript Kendra Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kendra", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-keyspaces/CHANGELOG.md b/clients/client-keyspaces/CHANGELOG.md index 25c429ace461..c402dbca5b35 100644 --- a/clients/client-keyspaces/CHANGELOG.md +++ b/clients/client-keyspaces/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-keyspaces + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-keyspaces diff --git a/clients/client-keyspaces/package.json b/clients/client-keyspaces/package.json index 94fc32894400..6b3c81122e11 100644 --- a/clients/client-keyspaces/package.json +++ b/clients/client-keyspaces/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-keyspaces", "description": "AWS SDK for JavaScript Keyspaces Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-keyspaces", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis-analytics-v2/CHANGELOG.md b/clients/client-kinesis-analytics-v2/CHANGELOG.md index d8cf49c99c47..63affb1f8bb8 100644 --- a/clients/client-kinesis-analytics-v2/CHANGELOG.md +++ b/clients/client-kinesis-analytics-v2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-analytics-v2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-analytics-v2 diff --git a/clients/client-kinesis-analytics-v2/package.json b/clients/client-kinesis-analytics-v2/package.json index 483476f4e9c4..822fd5645066 100644 --- a/clients/client-kinesis-analytics-v2/package.json +++ b/clients/client-kinesis-analytics-v2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-analytics-v2", "description": "AWS SDK for JavaScript Kinesis Analytics V2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-analytics-v2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis-analytics/CHANGELOG.md b/clients/client-kinesis-analytics/CHANGELOG.md index fad1d89bfcf7..d607c6da981a 100644 --- a/clients/client-kinesis-analytics/CHANGELOG.md +++ b/clients/client-kinesis-analytics/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-analytics + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-analytics diff --git a/clients/client-kinesis-analytics/package.json b/clients/client-kinesis-analytics/package.json index b55cbc9c280d..16c56851e938 100644 --- a/clients/client-kinesis-analytics/package.json +++ b/clients/client-kinesis-analytics/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-analytics", "description": "AWS SDK for JavaScript Kinesis Analytics Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-analytics", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis-video-archived-media/CHANGELOG.md b/clients/client-kinesis-video-archived-media/CHANGELOG.md index 84c94996d503..b9d7ab4c7701 100644 --- a/clients/client-kinesis-video-archived-media/CHANGELOG.md +++ b/clients/client-kinesis-video-archived-media/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-video-archived-media + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-video-archived-media diff --git a/clients/client-kinesis-video-archived-media/package.json b/clients/client-kinesis-video-archived-media/package.json index ce607857dde5..4da2bfcd68fd 100644 --- a/clients/client-kinesis-video-archived-media/package.json +++ b/clients/client-kinesis-video-archived-media/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-video-archived-media", "description": "AWS SDK for JavaScript Kinesis Video Archived Media Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-video-archived-media", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-kinesis-video-media/CHANGELOG.md b/clients/client-kinesis-video-media/CHANGELOG.md index 715471d01d59..ba14db91dc09 100644 --- a/clients/client-kinesis-video-media/CHANGELOG.md +++ b/clients/client-kinesis-video-media/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-video-media + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-video-media diff --git a/clients/client-kinesis-video-media/package.json b/clients/client-kinesis-video-media/package.json index f62c6a45fa78..168eb343cc65 100644 --- a/clients/client-kinesis-video-media/package.json +++ b/clients/client-kinesis-video-media/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-video-media", "description": "AWS SDK for JavaScript Kinesis Video Media Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-video-media", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-kinesis-video-signaling/CHANGELOG.md b/clients/client-kinesis-video-signaling/CHANGELOG.md index 5c7a0a49ba31..c8ec90daed54 100644 --- a/clients/client-kinesis-video-signaling/CHANGELOG.md +++ b/clients/client-kinesis-video-signaling/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-video-signaling + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-video-signaling diff --git a/clients/client-kinesis-video-signaling/package.json b/clients/client-kinesis-video-signaling/package.json index 004261e4f04e..e5091505017a 100644 --- a/clients/client-kinesis-video-signaling/package.json +++ b/clients/client-kinesis-video-signaling/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-video-signaling", "description": "AWS SDK for JavaScript Kinesis Video Signaling Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-video-signaling", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis-video-webrtc-storage/CHANGELOG.md b/clients/client-kinesis-video-webrtc-storage/CHANGELOG.md index 674ef4d7551f..5e88eb564f2a 100644 --- a/clients/client-kinesis-video-webrtc-storage/CHANGELOG.md +++ b/clients/client-kinesis-video-webrtc-storage/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-video-webrtc-storage + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-video-webrtc-storage diff --git a/clients/client-kinesis-video-webrtc-storage/package.json b/clients/client-kinesis-video-webrtc-storage/package.json index d1bb04e465fb..7ae0c8f65045 100644 --- a/clients/client-kinesis-video-webrtc-storage/package.json +++ b/clients/client-kinesis-video-webrtc-storage/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-video-webrtc-storage", "description": "AWS SDK for JavaScript Kinesis Video Webrtc Storage Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-video-webrtc-storage", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis-video/CHANGELOG.md b/clients/client-kinesis-video/CHANGELOG.md index a005f9d0a6aa..18f922a3449e 100644 --- a/clients/client-kinesis-video/CHANGELOG.md +++ b/clients/client-kinesis-video/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis-video + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis-video diff --git a/clients/client-kinesis-video/package.json b/clients/client-kinesis-video/package.json index f93d4be61daa..885ed6dcff1b 100644 --- a/clients/client-kinesis-video/package.json +++ b/clients/client-kinesis-video/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis-video", "description": "AWS SDK for JavaScript Kinesis Video Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis-video", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kinesis/CHANGELOG.md b/clients/client-kinesis/CHANGELOG.md index 0175a4585d48..17d5fb8f6439 100644 --- a/clients/client-kinesis/CHANGELOG.md +++ b/clients/client-kinesis/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kinesis + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kinesis diff --git a/clients/client-kinesis/package.json b/clients/client-kinesis/package.json index dd0b66de82c0..a89cdc7c0cf4 100644 --- a/clients/client-kinesis/package.json +++ b/clients/client-kinesis/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kinesis", "description": "AWS SDK for JavaScript Kinesis Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kinesis", @@ -33,7 +33,7 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/eventstream-serde-browser": "^4.0.2", "@smithy/eventstream-serde-config-resolver": "^4.1.0", @@ -42,22 +42,22 @@ "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-kms/CHANGELOG.md b/clients/client-kms/CHANGELOG.md index f72832cfc894..17a48af9249a 100644 --- a/clients/client-kms/CHANGELOG.md +++ b/clients/client-kms/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-kms + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-kms diff --git a/clients/client-kms/package.json b/clients/client-kms/package.json index 27e4b3972b33..eab819c68df2 100644 --- a/clients/client-kms/package.json +++ b/clients/client-kms/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-kms", "description": "AWS SDK for JavaScript Kms Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-kms", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lakeformation/CHANGELOG.md b/clients/client-lakeformation/CHANGELOG.md index 0bb1cbb9f4fb..e99fcfb4333f 100644 --- a/clients/client-lakeformation/CHANGELOG.md +++ b/clients/client-lakeformation/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lakeformation + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lakeformation diff --git a/clients/client-lakeformation/package.json b/clients/client-lakeformation/package.json index 8ec391f5776f..d2b47c978b5a 100644 --- a/clients/client-lakeformation/package.json +++ b/clients/client-lakeformation/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lakeformation", "description": "AWS SDK for JavaScript Lakeformation Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lakeformation", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-lambda/CHANGELOG.md b/clients/client-lambda/CHANGELOG.md index 503f7f87ea1e..ed6b3023fccc 100644 --- a/clients/client-lambda/CHANGELOG.md +++ b/clients/client-lambda/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lambda + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lambda diff --git a/clients/client-lambda/package.json b/clients/client-lambda/package.json index 7344d6b7f75e..e09b2ef16c1f 100644 --- a/clients/client-lambda/package.json +++ b/clients/client-lambda/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lambda", "description": "AWS SDK for JavaScript Lambda Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lambda", @@ -31,7 +31,7 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/eventstream-serde-browser": "^4.0.2", "@smithy/eventstream-serde-config-resolver": "^4.1.0", @@ -40,22 +40,22 @@ "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-launch-wizard/CHANGELOG.md b/clients/client-launch-wizard/CHANGELOG.md index a74057b1221d..7795e7cfc4a4 100644 --- a/clients/client-launch-wizard/CHANGELOG.md +++ b/clients/client-launch-wizard/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-launch-wizard + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-launch-wizard diff --git a/clients/client-launch-wizard/package.json b/clients/client-launch-wizard/package.json index f39c6d24b5f7..1f27eefb24ee 100644 --- a/clients/client-launch-wizard/package.json +++ b/clients/client-launch-wizard/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-launch-wizard", "description": "AWS SDK for JavaScript Launch Wizard Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-launch-wizard", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lex-model-building-service/CHANGELOG.md b/clients/client-lex-model-building-service/CHANGELOG.md index 4c884e359123..c230ce5f097e 100644 --- a/clients/client-lex-model-building-service/CHANGELOG.md +++ b/clients/client-lex-model-building-service/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lex-model-building-service + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lex-model-building-service diff --git a/clients/client-lex-model-building-service/package.json b/clients/client-lex-model-building-service/package.json index 7ae1123c2b83..1df9a0bd1970 100644 --- a/clients/client-lex-model-building-service/package.json +++ b/clients/client-lex-model-building-service/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lex-model-building-service", "description": "AWS SDK for JavaScript Lex Model Building Service Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lex-model-building-service", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lex-models-v2/CHANGELOG.md b/clients/client-lex-models-v2/CHANGELOG.md index d35f6a227358..7002ff7733fe 100644 --- a/clients/client-lex-models-v2/CHANGELOG.md +++ b/clients/client-lex-models-v2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lex-models-v2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lex-models-v2 diff --git a/clients/client-lex-models-v2/package.json b/clients/client-lex-models-v2/package.json index bfb07cb34906..613c7bbed696 100644 --- a/clients/client-lex-models-v2/package.json +++ b/clients/client-lex-models-v2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lex-models-v2", "description": "AWS SDK for JavaScript Lex Models V2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lex-models-v2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lex-runtime-service/CHANGELOG.md b/clients/client-lex-runtime-service/CHANGELOG.md index bc9334687062..4d97db81d760 100644 --- a/clients/client-lex-runtime-service/CHANGELOG.md +++ b/clients/client-lex-runtime-service/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lex-runtime-service + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lex-runtime-service diff --git a/clients/client-lex-runtime-service/package.json b/clients/client-lex-runtime-service/package.json index c367131917d7..e10cef2a92ab 100644 --- a/clients/client-lex-runtime-service/package.json +++ b/clients/client-lex-runtime-service/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lex-runtime-service", "description": "AWS SDK for JavaScript Lex Runtime Service Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lex-runtime-service", @@ -33,28 +33,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-lex-runtime-v2/CHANGELOG.md b/clients/client-lex-runtime-v2/CHANGELOG.md index c000800680bc..b6e9d96e3e2f 100644 --- a/clients/client-lex-runtime-v2/CHANGELOG.md +++ b/clients/client-lex-runtime-v2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lex-runtime-v2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lex-runtime-v2 diff --git a/clients/client-lex-runtime-v2/package.json b/clients/client-lex-runtime-v2/package.json index d4f4f589ec30..2e202480d037 100644 --- a/clients/client-lex-runtime-v2/package.json +++ b/clients/client-lex-runtime-v2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lex-runtime-v2", "description": "AWS SDK for JavaScript Lex Runtime V2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lex-runtime-v2", @@ -33,7 +33,7 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/eventstream-serde-browser": "^4.0.2", "@smithy/eventstream-serde-config-resolver": "^4.1.0", @@ -42,22 +42,22 @@ "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-license-manager-linux-subscriptions/CHANGELOG.md b/clients/client-license-manager-linux-subscriptions/CHANGELOG.md index e3368946c049..801d8ad84ef3 100644 --- a/clients/client-license-manager-linux-subscriptions/CHANGELOG.md +++ b/clients/client-license-manager-linux-subscriptions/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-license-manager-linux-subscriptions + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-license-manager-linux-subscriptions diff --git a/clients/client-license-manager-linux-subscriptions/package.json b/clients/client-license-manager-linux-subscriptions/package.json index 8c19d2000b03..0bb5ed7456bf 100644 --- a/clients/client-license-manager-linux-subscriptions/package.json +++ b/clients/client-license-manager-linux-subscriptions/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-license-manager-linux-subscriptions", "description": "AWS SDK for JavaScript License Manager Linux Subscriptions Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-license-manager-linux-subscriptions", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-license-manager-user-subscriptions/CHANGELOG.md b/clients/client-license-manager-user-subscriptions/CHANGELOG.md index ba6b79381fb9..95334279e871 100644 --- a/clients/client-license-manager-user-subscriptions/CHANGELOG.md +++ b/clients/client-license-manager-user-subscriptions/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-license-manager-user-subscriptions + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-license-manager-user-subscriptions diff --git a/clients/client-license-manager-user-subscriptions/package.json b/clients/client-license-manager-user-subscriptions/package.json index bebf149b7a74..941ff00ee955 100644 --- a/clients/client-license-manager-user-subscriptions/package.json +++ b/clients/client-license-manager-user-subscriptions/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-license-manager-user-subscriptions", "description": "AWS SDK for JavaScript License Manager User Subscriptions Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-license-manager-user-subscriptions", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-license-manager/CHANGELOG.md b/clients/client-license-manager/CHANGELOG.md index b4296eab8241..49b1ec51c99b 100644 --- a/clients/client-license-manager/CHANGELOG.md +++ b/clients/client-license-manager/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-license-manager + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-license-manager diff --git a/clients/client-license-manager/package.json b/clients/client-license-manager/package.json index 6bb990ba4980..c77ff529b733 100644 --- a/clients/client-license-manager/package.json +++ b/clients/client-license-manager/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-license-manager", "description": "AWS SDK for JavaScript License Manager Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-license-manager", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lightsail/CHANGELOG.md b/clients/client-lightsail/CHANGELOG.md index 7b4b01a87831..8aeff37b66f5 100644 --- a/clients/client-lightsail/CHANGELOG.md +++ b/clients/client-lightsail/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lightsail + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lightsail diff --git a/clients/client-lightsail/package.json b/clients/client-lightsail/package.json index e418825e8a02..470460429a4b 100644 --- a/clients/client-lightsail/package.json +++ b/clients/client-lightsail/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lightsail", "description": "AWS SDK for JavaScript Lightsail Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lightsail", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-location/CHANGELOG.md b/clients/client-location/CHANGELOG.md index ba5ca035c198..2e636c8d7b51 100644 --- a/clients/client-location/CHANGELOG.md +++ b/clients/client-location/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-location + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-location diff --git a/clients/client-location/package.json b/clients/client-location/package.json index 5a89384fe0a4..5bca9b38a74e 100644 --- a/clients/client-location/package.json +++ b/clients/client-location/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-location", "description": "AWS SDK for JavaScript Location Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-location", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-lookoutequipment/CHANGELOG.md b/clients/client-lookoutequipment/CHANGELOG.md index a00f2f6a096d..7ea00da7d907 100644 --- a/clients/client-lookoutequipment/CHANGELOG.md +++ b/clients/client-lookoutequipment/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lookoutequipment + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lookoutequipment diff --git a/clients/client-lookoutequipment/package.json b/clients/client-lookoutequipment/package.json index fb1c63cd1dd5..a21661452d9e 100644 --- a/clients/client-lookoutequipment/package.json +++ b/clients/client-lookoutequipment/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lookoutequipment", "description": "AWS SDK for JavaScript Lookoutequipment Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lookoutequipment", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lookoutmetrics/CHANGELOG.md b/clients/client-lookoutmetrics/CHANGELOG.md index 753b57ba6545..93020a7026a7 100644 --- a/clients/client-lookoutmetrics/CHANGELOG.md +++ b/clients/client-lookoutmetrics/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lookoutmetrics + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lookoutmetrics diff --git a/clients/client-lookoutmetrics/package.json b/clients/client-lookoutmetrics/package.json index c2807bab167f..4c6ad9ba0900 100644 --- a/clients/client-lookoutmetrics/package.json +++ b/clients/client-lookoutmetrics/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lookoutmetrics", "description": "AWS SDK for JavaScript Lookoutmetrics Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lookoutmetrics", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-lookoutvision/CHANGELOG.md b/clients/client-lookoutvision/CHANGELOG.md index 2c7b9dfe6378..f6987ae10c91 100644 --- a/clients/client-lookoutvision/CHANGELOG.md +++ b/clients/client-lookoutvision/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-lookoutvision + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-lookoutvision diff --git a/clients/client-lookoutvision/package.json b/clients/client-lookoutvision/package.json index f38c100688b6..b4e8b8c82941 100644 --- a/clients/client-lookoutvision/package.json +++ b/clients/client-lookoutvision/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-lookoutvision", "description": "AWS SDK for JavaScript Lookoutvision Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-lookoutvision", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-m2/CHANGELOG.md b/clients/client-m2/CHANGELOG.md index e01e3a2f36f6..e7e271d967ea 100644 --- a/clients/client-m2/CHANGELOG.md +++ b/clients/client-m2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-m2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-m2 diff --git a/clients/client-m2/package.json b/clients/client-m2/package.json index 157151af7361..ab4d39cb36e1 100644 --- a/clients/client-m2/package.json +++ b/clients/client-m2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-m2", "description": "AWS SDK for JavaScript M2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-m2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-machine-learning/CHANGELOG.md b/clients/client-machine-learning/CHANGELOG.md index a8be88010bf6..e75d0ceb34fb 100644 --- a/clients/client-machine-learning/CHANGELOG.md +++ b/clients/client-machine-learning/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-machine-learning + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-machine-learning diff --git a/clients/client-machine-learning/package.json b/clients/client-machine-learning/package.json index 33ccb6039faf..4a3f68444d83 100644 --- a/clients/client-machine-learning/package.json +++ b/clients/client-machine-learning/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-machine-learning", "description": "AWS SDK for JavaScript Machine Learning Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-machine-learning", @@ -32,28 +32,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-macie2/CHANGELOG.md b/clients/client-macie2/CHANGELOG.md index 5420b233bab6..f5202548df84 100644 --- a/clients/client-macie2/CHANGELOG.md +++ b/clients/client-macie2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-macie2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-macie2 diff --git a/clients/client-macie2/package.json b/clients/client-macie2/package.json index 316e0be53d3f..ee6053dc83d0 100644 --- a/clients/client-macie2/package.json +++ b/clients/client-macie2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-macie2", "description": "AWS SDK for JavaScript Macie2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-macie2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mailmanager/CHANGELOG.md b/clients/client-mailmanager/CHANGELOG.md index 1c21a44ea264..678135efb238 100644 --- a/clients/client-mailmanager/CHANGELOG.md +++ b/clients/client-mailmanager/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mailmanager + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mailmanager diff --git a/clients/client-mailmanager/package.json b/clients/client-mailmanager/package.json index 62ab0ecf900d..bc377ffb0d4d 100644 --- a/clients/client-mailmanager/package.json +++ b/clients/client-mailmanager/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mailmanager", "description": "AWS SDK for JavaScript Mailmanager Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-managedblockchain-query/CHANGELOG.md b/clients/client-managedblockchain-query/CHANGELOG.md index 5ed0e6d2cd96..a4f069904be3 100644 --- a/clients/client-managedblockchain-query/CHANGELOG.md +++ b/clients/client-managedblockchain-query/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-managedblockchain-query + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-managedblockchain-query diff --git a/clients/client-managedblockchain-query/package.json b/clients/client-managedblockchain-query/package.json index 597fc53b26dc..a8f798bb8e29 100644 --- a/clients/client-managedblockchain-query/package.json +++ b/clients/client-managedblockchain-query/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-managedblockchain-query", "description": "AWS SDK for JavaScript Managedblockchain Query Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-managedblockchain-query", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-managedblockchain/CHANGELOG.md b/clients/client-managedblockchain/CHANGELOG.md index 4452f3702857..329e4f64a1e1 100644 --- a/clients/client-managedblockchain/CHANGELOG.md +++ b/clients/client-managedblockchain/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-managedblockchain + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-managedblockchain diff --git a/clients/client-managedblockchain/package.json b/clients/client-managedblockchain/package.json index 0847b8adcb70..ed7ec4d5234f 100644 --- a/clients/client-managedblockchain/package.json +++ b/clients/client-managedblockchain/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-managedblockchain", "description": "AWS SDK for JavaScript Managedblockchain Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-managedblockchain", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-agreement/CHANGELOG.md b/clients/client-marketplace-agreement/CHANGELOG.md index cb693522f689..a7060165fe5b 100644 --- a/clients/client-marketplace-agreement/CHANGELOG.md +++ b/clients/client-marketplace-agreement/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-agreement + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-agreement diff --git a/clients/client-marketplace-agreement/package.json b/clients/client-marketplace-agreement/package.json index 02ea3ed65fb4..3a4cb9485416 100644 --- a/clients/client-marketplace-agreement/package.json +++ b/clients/client-marketplace-agreement/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-agreement", "description": "AWS SDK for JavaScript Marketplace Agreement Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-agreement", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-catalog/CHANGELOG.md b/clients/client-marketplace-catalog/CHANGELOG.md index a656e77068c9..1279636b2229 100644 --- a/clients/client-marketplace-catalog/CHANGELOG.md +++ b/clients/client-marketplace-catalog/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-catalog + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-catalog diff --git a/clients/client-marketplace-catalog/package.json b/clients/client-marketplace-catalog/package.json index eba0b75b96d4..c3d2528cad82 100644 --- a/clients/client-marketplace-catalog/package.json +++ b/clients/client-marketplace-catalog/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-catalog", "description": "AWS SDK for JavaScript Marketplace Catalog Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-catalog", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-commerce-analytics/CHANGELOG.md b/clients/client-marketplace-commerce-analytics/CHANGELOG.md index 00d6b90df42d..a149d496616e 100644 --- a/clients/client-marketplace-commerce-analytics/CHANGELOG.md +++ b/clients/client-marketplace-commerce-analytics/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-commerce-analytics + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-commerce-analytics diff --git a/clients/client-marketplace-commerce-analytics/package.json b/clients/client-marketplace-commerce-analytics/package.json index 3823fb94b3f4..7b8617b707b6 100644 --- a/clients/client-marketplace-commerce-analytics/package.json +++ b/clients/client-marketplace-commerce-analytics/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-commerce-analytics", "description": "AWS SDK for JavaScript Marketplace Commerce Analytics Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-commerce-analytics", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-deployment/CHANGELOG.md b/clients/client-marketplace-deployment/CHANGELOG.md index 907dfa4eca24..4579ba761c43 100644 --- a/clients/client-marketplace-deployment/CHANGELOG.md +++ b/clients/client-marketplace-deployment/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-deployment + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-deployment diff --git a/clients/client-marketplace-deployment/package.json b/clients/client-marketplace-deployment/package.json index 8fc4f1e859e0..c79c418481ef 100644 --- a/clients/client-marketplace-deployment/package.json +++ b/clients/client-marketplace-deployment/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-deployment", "description": "AWS SDK for JavaScript Marketplace Deployment Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-deployment", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-entitlement-service/CHANGELOG.md b/clients/client-marketplace-entitlement-service/CHANGELOG.md index 6254bb017257..549438bec5fd 100644 --- a/clients/client-marketplace-entitlement-service/CHANGELOG.md +++ b/clients/client-marketplace-entitlement-service/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-entitlement-service + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-entitlement-service diff --git a/clients/client-marketplace-entitlement-service/package.json b/clients/client-marketplace-entitlement-service/package.json index 71feeb086234..d789be0bc4f7 100644 --- a/clients/client-marketplace-entitlement-service/package.json +++ b/clients/client-marketplace-entitlement-service/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-entitlement-service", "description": "AWS SDK for JavaScript Marketplace Entitlement Service Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-entitlement-service", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-metering/CHANGELOG.md b/clients/client-marketplace-metering/CHANGELOG.md index 40e14fd21b19..d8aabeaaa1f4 100644 --- a/clients/client-marketplace-metering/CHANGELOG.md +++ b/clients/client-marketplace-metering/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-metering + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-metering diff --git a/clients/client-marketplace-metering/package.json b/clients/client-marketplace-metering/package.json index 29162ce51efb..1c74d3519e9b 100644 --- a/clients/client-marketplace-metering/package.json +++ b/clients/client-marketplace-metering/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-metering", "description": "AWS SDK for JavaScript Marketplace Metering Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-marketplace-metering", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-marketplace-reporting/CHANGELOG.md b/clients/client-marketplace-reporting/CHANGELOG.md index 65159594b391..c4dc85b4b7c6 100644 --- a/clients/client-marketplace-reporting/CHANGELOG.md +++ b/clients/client-marketplace-reporting/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-marketplace-reporting + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-marketplace-reporting diff --git a/clients/client-marketplace-reporting/package.json b/clients/client-marketplace-reporting/package.json index 23ec3c5ede11..9676f19847f3 100644 --- a/clients/client-marketplace-reporting/package.json +++ b/clients/client-marketplace-reporting/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-marketplace-reporting", "description": "AWS SDK for JavaScript Marketplace Reporting Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "tsc -p tsconfig.cjs.json", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediaconnect/CHANGELOG.md b/clients/client-mediaconnect/CHANGELOG.md index ded472eb9b2a..0bc1cf648c88 100644 --- a/clients/client-mediaconnect/CHANGELOG.md +++ b/clients/client-mediaconnect/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediaconnect + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediaconnect diff --git a/clients/client-mediaconnect/package.json b/clients/client-mediaconnect/package.json index aa8b571ac763..95c73193ad40 100644 --- a/clients/client-mediaconnect/package.json +++ b/clients/client-mediaconnect/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediaconnect", "description": "AWS SDK for JavaScript Mediaconnect Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediaconnect", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediaconvert/CHANGELOG.md b/clients/client-mediaconvert/CHANGELOG.md index 3e3724a13be3..c689c2fefe9f 100644 --- a/clients/client-mediaconvert/CHANGELOG.md +++ b/clients/client-mediaconvert/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediaconvert + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediaconvert diff --git a/clients/client-mediaconvert/package.json b/clients/client-mediaconvert/package.json index ec7e360d30cf..8a5d341b3fbe 100644 --- a/clients/client-mediaconvert/package.json +++ b/clients/client-mediaconvert/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediaconvert", "description": "AWS SDK for JavaScript Mediaconvert Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediaconvert", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-medialive/CHANGELOG.md b/clients/client-medialive/CHANGELOG.md index 368a6e4c8e50..1ada8fa39d8d 100644 --- a/clients/client-medialive/CHANGELOG.md +++ b/clients/client-medialive/CHANGELOG.md @@ -3,6 +3,17 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + + +### Features + +* **client-medialive:** Add support to the AV1 rate control mode ([f8e9f56](https://github.com/aws/aws-sdk-js-v3/commit/f8e9f56730fcac2a715e0180e58a9f690614b629)) + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-medialive diff --git a/clients/client-medialive/package.json b/clients/client-medialive/package.json index ec9c9d666a80..7b1e54b74aa2 100644 --- a/clients/client-medialive/package.json +++ b/clients/client-medialive/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-medialive", "description": "AWS SDK for JavaScript Medialive Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-medialive", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-medialive/src/commands/BatchUpdateScheduleCommand.ts b/clients/client-medialive/src/commands/BatchUpdateScheduleCommand.ts index 64d8fafc1644..a90c22b13c73 100644 --- a/clients/client-medialive/src/commands/BatchUpdateScheduleCommand.ts +++ b/clients/client-medialive/src/commands/BatchUpdateScheduleCommand.ts @@ -6,7 +6,8 @@ import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { commonParams } from "../endpoint/EndpointParameters"; import { MediaLiveClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../MediaLiveClient"; -import { BatchUpdateScheduleRequest, BatchUpdateScheduleResponse } from "../models/models_1"; +import { BatchUpdateScheduleRequest } from "../models/models_1"; +import { BatchUpdateScheduleResponse } from "../models/models_2"; import { de_BatchUpdateScheduleCommand, se_BatchUpdateScheduleCommand } from "../protocols/Aws_restJson1"; /** diff --git a/clients/client-medialive/src/commands/CreateChannelCommand.ts b/clients/client-medialive/src/commands/CreateChannelCommand.ts index 77f54085fe58..93a2ff780a20 100644 --- a/clients/client-medialive/src/commands/CreateChannelCommand.ts +++ b/clients/client-medialive/src/commands/CreateChannelCommand.ts @@ -69,6 +69,9 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * Url: "STRING_VALUE", * }, * ], + * LogicalInterfaceNames: [ // __listOf__string + * "STRING_VALUE", + * ], * }, * ], * EncoderSettings: { // EncoderSettings @@ -544,7 +547,7 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * }, * Outputs: [ // __listOfOutput // required * { // Output - * AudioDescriptionNames: [ // __listOf__string + * AudioDescriptionNames: [ * "STRING_VALUE", * ], * CaptionDescriptionNames: [ @@ -1046,6 +1049,8 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * Prefix: "STRING_VALUE", * }, + * Bitrate: Number("int"), + * RateControlMode: "CBR" || "QVBR", * }, * }, * Height: Number("int"), @@ -1276,6 +1281,9 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -1756,7 +1764,7 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -2258,6 +2266,8 @@ export interface CreateChannelCommandOutput extends CreateChannelResponse, __Met * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/DeleteChannelCommand.ts b/clients/client-medialive/src/commands/DeleteChannelCommand.ts index 3cf061deb861..6e741aa45693 100644 --- a/clients/client-medialive/src/commands/DeleteChannelCommand.ts +++ b/clients/client-medialive/src/commands/DeleteChannelCommand.ts @@ -75,6 +75,9 @@ export interface DeleteChannelCommandOutput extends DeleteChannelResponse, __Met * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -555,7 +558,7 @@ export interface DeleteChannelCommandOutput extends DeleteChannelResponse, __Met * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1057,6 +1060,8 @@ export interface DeleteChannelCommandOutput extends DeleteChannelResponse, __Met * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/DescribeChannelCommand.ts b/clients/client-medialive/src/commands/DescribeChannelCommand.ts index 6eec0573a9b5..ae34e6af2407 100644 --- a/clients/client-medialive/src/commands/DescribeChannelCommand.ts +++ b/clients/client-medialive/src/commands/DescribeChannelCommand.ts @@ -75,6 +75,9 @@ export interface DescribeChannelCommandOutput extends DescribeChannelResponse, _ * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -555,7 +558,7 @@ export interface DescribeChannelCommandOutput extends DescribeChannelResponse, _ * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1057,6 +1060,8 @@ export interface DescribeChannelCommandOutput extends DescribeChannelResponse, _ * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/ListChannelsCommand.ts b/clients/client-medialive/src/commands/ListChannelsCommand.ts index fb89701aaa9f..fe34e18b11ed 100644 --- a/clients/client-medialive/src/commands/ListChannelsCommand.ts +++ b/clients/client-medialive/src/commands/ListChannelsCommand.ts @@ -78,6 +78,9 @@ export interface ListChannelsCommandOutput extends ListChannelsResponse, __Metad * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -219,7 +222,7 @@ export interface ListChannelsCommandOutput extends ListChannelsResponse, __Metad * // }, * // }, * // }, - * // LogicalInterfaceNames: [ // __listOf__string + * // LogicalInterfaceNames: [ * // "STRING_VALUE", * // ], * // }, @@ -253,9 +256,7 @@ export interface ListChannelsCommandOutput extends ListChannelsResponse, __Metad * // SecurityGroupIds: [ * // "STRING_VALUE", * // ], - * // SubnetIds: [ - * // "STRING_VALUE", - * // ], + * // SubnetIds: "<__listOf__string>", * // }, * // AnywhereSettings: { // DescribeAnywhereSettings * // ChannelPlacementGroupId: "STRING_VALUE", diff --git a/clients/client-medialive/src/commands/RestartChannelPipelinesCommand.ts b/clients/client-medialive/src/commands/RestartChannelPipelinesCommand.ts index d0eb61df57ae..9c9715ec2ce3 100644 --- a/clients/client-medialive/src/commands/RestartChannelPipelinesCommand.ts +++ b/clients/client-medialive/src/commands/RestartChannelPipelinesCommand.ts @@ -78,6 +78,9 @@ export interface RestartChannelPipelinesCommandOutput extends RestartChannelPipe * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -558,7 +561,7 @@ export interface RestartChannelPipelinesCommandOutput extends RestartChannelPipe * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1060,6 +1063,8 @@ export interface RestartChannelPipelinesCommandOutput extends RestartChannelPipe * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/StartChannelCommand.ts b/clients/client-medialive/src/commands/StartChannelCommand.ts index 5535a4038419..37129bc8964a 100644 --- a/clients/client-medialive/src/commands/StartChannelCommand.ts +++ b/clients/client-medialive/src/commands/StartChannelCommand.ts @@ -75,6 +75,9 @@ export interface StartChannelCommandOutput extends StartChannelResponse, __Metad * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -555,7 +558,7 @@ export interface StartChannelCommandOutput extends StartChannelResponse, __Metad * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1057,6 +1060,8 @@ export interface StartChannelCommandOutput extends StartChannelResponse, __Metad * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/StopChannelCommand.ts b/clients/client-medialive/src/commands/StopChannelCommand.ts index 5da8670b7bc6..ec3ac6b7210b 100644 --- a/clients/client-medialive/src/commands/StopChannelCommand.ts +++ b/clients/client-medialive/src/commands/StopChannelCommand.ts @@ -75,6 +75,9 @@ export interface StopChannelCommandOutput extends StopChannelResponse, __Metadat * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -555,7 +558,7 @@ export interface StopChannelCommandOutput extends StopChannelResponse, __Metadat * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1057,6 +1060,8 @@ export interface StopChannelCommandOutput extends StopChannelResponse, __Metadat * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/UpdateChannelClassCommand.ts b/clients/client-medialive/src/commands/UpdateChannelClassCommand.ts index 186fa0a5ad54..eeb3022311b8 100644 --- a/clients/client-medialive/src/commands/UpdateChannelClassCommand.ts +++ b/clients/client-medialive/src/commands/UpdateChannelClassCommand.ts @@ -67,6 +67,9 @@ export interface UpdateChannelClassCommandOutput extends UpdateChannelClassRespo * Url: "STRING_VALUE", * }, * ], + * LogicalInterfaceNames: [ // __listOf__string + * "STRING_VALUE", + * ], * }, * ], * }; @@ -108,6 +111,9 @@ export interface UpdateChannelClassCommandOutput extends UpdateChannelClassRespo * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -588,7 +594,7 @@ export interface UpdateChannelClassCommandOutput extends UpdateChannelClassRespo * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -1090,6 +1096,8 @@ export interface UpdateChannelClassCommandOutput extends UpdateChannelClassRespo * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/commands/UpdateChannelCommand.ts b/clients/client-medialive/src/commands/UpdateChannelCommand.ts index d9244cfb40f0..b1c05bc5bd17 100644 --- a/clients/client-medialive/src/commands/UpdateChannelCommand.ts +++ b/clients/client-medialive/src/commands/UpdateChannelCommand.ts @@ -69,6 +69,9 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * Url: "STRING_VALUE", * }, * ], + * LogicalInterfaceNames: [ // __listOf__string + * "STRING_VALUE", + * ], * }, * ], * EncoderSettings: { // EncoderSettings @@ -544,7 +547,7 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * }, * Outputs: [ // __listOfOutput // required * { // Output - * AudioDescriptionNames: [ // __listOf__string + * AudioDescriptionNames: [ * "STRING_VALUE", * ], * CaptionDescriptionNames: [ @@ -1046,6 +1049,8 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * Prefix: "STRING_VALUE", * }, + * Bitrate: Number("int"), + * RateControlMode: "CBR" || "QVBR", * }, * }, * Height: Number("int"), @@ -1267,6 +1272,9 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * // Url: "STRING_VALUE", * // }, * // ], + * // LogicalInterfaceNames: [ // __listOf__string + * // "STRING_VALUE", + * // ], * // }, * // ], * // EgressEndpoints: [ // __listOfChannelEgressEndpoint @@ -1747,7 +1755,7 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * // }, * // Outputs: [ // __listOfOutput // required * // { // Output - * // AudioDescriptionNames: [ // __listOf__string + * // AudioDescriptionNames: [ * // "STRING_VALUE", * // ], * // CaptionDescriptionNames: [ @@ -2249,6 +2257,8 @@ export interface UpdateChannelCommandOutput extends UpdateChannelResponse, __Met * // Position: "BOTTOM_CENTER" || "BOTTOM_LEFT" || "BOTTOM_RIGHT" || "MIDDLE_CENTER" || "MIDDLE_LEFT" || "MIDDLE_RIGHT" || "TOP_CENTER" || "TOP_LEFT" || "TOP_RIGHT", // required * // Prefix: "STRING_VALUE", * // }, + * // Bitrate: Number("int"), + * // RateControlMode: "CBR" || "QVBR", * // }, * // }, * // Height: Number("int"), diff --git a/clients/client-medialive/src/models/models_0.ts b/clients/client-medialive/src/models/models_0.ts index 1628628c9d2c..c1b6139dc7be 100644 --- a/clients/client-medialive/src/models/models_0.ts +++ b/clients/client-medialive/src/models/models_0.ts @@ -2892,6 +2892,12 @@ export interface OutputDestination { * @public */ SrtSettings?: SrtOutputDestinationSettings[] | undefined; + + /** + * Optional assignment of an output to a logical interface on the Node. Only applies to on premises channels. + * @public + */ + LogicalInterfaceNames?: string[] | undefined; } /** diff --git a/clients/client-medialive/src/models/models_1.ts b/clients/client-medialive/src/models/models_1.ts index 9b97c68da4e5..2635598bc617 100644 --- a/clients/client-medialive/src/models/models_1.ts +++ b/clients/client-medialive/src/models/models_1.ts @@ -4772,6 +4772,20 @@ export const Av1LookAheadRateControl = { */ export type Av1LookAheadRateControl = (typeof Av1LookAheadRateControl)[keyof typeof Av1LookAheadRateControl]; +/** + * @public + * @enum + */ +export const Av1RateControlMode = { + CBR: "CBR", + QVBR: "QVBR", +} as const; + +/** + * @public + */ +export type Av1RateControlMode = (typeof Av1RateControlMode)[keyof typeof Av1RateControlMode]; + /** * @public * @enum @@ -4969,6 +4983,24 @@ export interface Av1Settings { * @public */ TimecodeBurninSettings?: TimecodeBurninSettings | undefined; + + /** + * Average bitrate in bits/second. Required when the rate control mode is CBR. Not used for QVBR. + * @public + */ + Bitrate?: number | undefined; + + /** + * Rate control mode. + * + * QVBR: Quality will match the specified quality level except when it is constrained by the + * maximum bitrate. Recommended if you or your viewers pay for bandwidth. + * + * CBR: Quality varies, depending on the video complexity. Recommended only if you distribute + * your assets to devices that cannot handle variable bitrates. + * @public + */ + RateControlMode?: Av1RateControlMode | undefined; } /** @@ -7503,21 +7535,3 @@ export interface BatchUpdateScheduleRequest { */ Deletes?: BatchScheduleActionDeleteRequest | undefined; } - -/** - * Placeholder documentation for BatchUpdateScheduleResponse - * @public - */ -export interface BatchUpdateScheduleResponse { - /** - * Schedule actions created in the schedule. - * @public - */ - Creates?: BatchScheduleActionCreateResult | undefined; - - /** - * Schedule actions deleted from the schedule. - * @public - */ - Deletes?: BatchScheduleActionDeleteResult | undefined; -} diff --git a/clients/client-medialive/src/models/models_2.ts b/clients/client-medialive/src/models/models_2.ts index 5ce9b28b28a0..5040bda09e22 100644 --- a/clients/client-medialive/src/models/models_2.ts +++ b/clients/client-medialive/src/models/models_2.ts @@ -105,6 +105,8 @@ import { AnywhereSettings, AvailBlanking, AvailConfiguration, + BatchScheduleActionCreateResult, + BatchScheduleActionDeleteResult, OutputGroup, PipelineDetail, RenewalSettings, @@ -126,6 +128,24 @@ import { VideoDescription, } from "./models_1"; +/** + * Placeholder documentation for BatchUpdateScheduleResponse + * @public + */ +export interface BatchUpdateScheduleResponse { + /** + * Schedule actions created in the schedule. + * @public + */ + Creates?: BatchScheduleActionCreateResult | undefined; + + /** + * Schedule actions deleted from the schedule. + * @public + */ + Deletes?: BatchScheduleActionDeleteResult | undefined; +} + /** * @public * @enum diff --git a/clients/client-medialive/src/protocols/Aws_restJson1.ts b/clients/client-medialive/src/protocols/Aws_restJson1.ts index ea9c43ab17cb..3b79d6142738 100644 --- a/clients/client-medialive/src/protocols/Aws_restJson1.ts +++ b/clients/client-medialive/src/protocols/Aws_restJson1.ts @@ -7311,6 +7311,7 @@ const se_Av1ColorSpaceSettings = (input: Av1ColorSpaceSettings, context: __Serde const se_Av1Settings = (input: Av1Settings, context: __SerdeContext): any => { return take(input, { afdSignaling: [, , `AfdSignaling`], + bitrate: [, , `Bitrate`], bufSize: [, , `BufSize`], colorSpaceSettings: [, (_) => se_Av1ColorSpaceSettings(_, context), `ColorSpaceSettings`], fixedAfd: [, , `FixedAfd`], @@ -7325,6 +7326,7 @@ const se_Av1Settings = (input: Av1Settings, context: __SerdeContext): any => { parDenominator: [, , `ParDenominator`], parNumerator: [, , `ParNumerator`], qvbrQualityLevel: [, , `QvbrQualityLevel`], + rateControlMode: [, , `RateControlMode`], sceneChangeDetect: [, , `SceneChangeDetect`], timecodeBurninSettings: [, (_) => se_TimecodeBurninSettings(_, context), `TimecodeBurninSettings`], }); @@ -9193,6 +9195,7 @@ const se_Output = (input: Output, context: __SerdeContext): any => { const se_OutputDestination = (input: OutputDestination, context: __SerdeContext): any => { return take(input, { id: [, , `Id`], + logicalInterfaceNames: [, _json, `LogicalInterfaceNames`], mediaPackageSettings: [ , (_) => se___listOfMediaPackageOutputDestinationSettings(_, context), @@ -11257,6 +11260,7 @@ const de_Av1ColorSpaceSettings = (output: any, context: __SerdeContext): Av1Colo const de_Av1Settings = (output: any, context: __SerdeContext): Av1Settings => { return take(output, { AfdSignaling: [, __expectString, `afdSignaling`], + Bitrate: [, __expectInt32, `bitrate`], BufSize: [, __expectInt32, `bufSize`], ColorSpaceSettings: [, (_: any) => de_Av1ColorSpaceSettings(_, context), `colorSpaceSettings`], FixedAfd: [, __expectString, `fixedAfd`], @@ -11271,6 +11275,7 @@ const de_Av1Settings = (output: any, context: __SerdeContext): Av1Settings => { ParDenominator: [, __expectInt32, `parDenominator`], ParNumerator: [, __expectInt32, `parNumerator`], QvbrQualityLevel: [, __expectInt32, `qvbrQualityLevel`], + RateControlMode: [, __expectString, `rateControlMode`], SceneChangeDetect: [, __expectString, `sceneChangeDetect`], TimecodeBurninSettings: [, (_: any) => de_TimecodeBurninSettings(_, context), `timecodeBurninSettings`], }) as any; @@ -13580,6 +13585,7 @@ const de_Output = (output: any, context: __SerdeContext): Output => { const de_OutputDestination = (output: any, context: __SerdeContext): OutputDestination => { return take(output, { Id: [, __expectString, `id`], + LogicalInterfaceNames: [, _json, `logicalInterfaceNames`], MediaPackageSettings: [ , (_: any) => de___listOfMediaPackageOutputDestinationSettings(_, context), diff --git a/clients/client-mediapackage-vod/CHANGELOG.md b/clients/client-mediapackage-vod/CHANGELOG.md index 1849a50cf0a4..7767904d8652 100644 --- a/clients/client-mediapackage-vod/CHANGELOG.md +++ b/clients/client-mediapackage-vod/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediapackage-vod + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediapackage-vod diff --git a/clients/client-mediapackage-vod/package.json b/clients/client-mediapackage-vod/package.json index 4bf3aedcdad0..79682a426f02 100644 --- a/clients/client-mediapackage-vod/package.json +++ b/clients/client-mediapackage-vod/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediapackage-vod", "description": "AWS SDK for JavaScript Mediapackage Vod Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediapackage-vod", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediapackage/CHANGELOG.md b/clients/client-mediapackage/CHANGELOG.md index 2953dcbb23d3..d01b4796ca91 100644 --- a/clients/client-mediapackage/CHANGELOG.md +++ b/clients/client-mediapackage/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediapackage + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediapackage diff --git a/clients/client-mediapackage/package.json b/clients/client-mediapackage/package.json index fe87f2848e9c..ae2c133eb77c 100644 --- a/clients/client-mediapackage/package.json +++ b/clients/client-mediapackage/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediapackage", "description": "AWS SDK for JavaScript Mediapackage Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediapackage", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediapackagev2/CHANGELOG.md b/clients/client-mediapackagev2/CHANGELOG.md index c1418076a6c2..6b7951830bbb 100644 --- a/clients/client-mediapackagev2/CHANGELOG.md +++ b/clients/client-mediapackagev2/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediapackagev2 + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediapackagev2 diff --git a/clients/client-mediapackagev2/package.json b/clients/client-mediapackagev2/package.json index 004fae008e84..7399bcde759d 100644 --- a/clients/client-mediapackagev2/package.json +++ b/clients/client-mediapackagev2/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediapackagev2", "description": "AWS SDK for JavaScript Mediapackagev2 Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediapackagev2", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediastore-data/CHANGELOG.md b/clients/client-mediastore-data/CHANGELOG.md index fb6c9f7991c2..27f0d5bd141b 100644 --- a/clients/client-mediastore-data/CHANGELOG.md +++ b/clients/client-mediastore-data/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediastore-data + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediastore-data diff --git a/clients/client-mediastore-data/package.json b/clients/client-mediastore-data/package.json index 54d9e4f6363a..a9501fbf34ff 100644 --- a/clients/client-mediastore-data/package.json +++ b/clients/client-mediastore-data/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediastore-data", "description": "AWS SDK for JavaScript Mediastore Data Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediastore-data", @@ -33,28 +33,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-stream": "^4.2.0", diff --git a/clients/client-mediastore/CHANGELOG.md b/clients/client-mediastore/CHANGELOG.md index a74a1ea56ccf..5cf551ba7e90 100644 --- a/clients/client-mediastore/CHANGELOG.md +++ b/clients/client-mediastore/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/client-mediastore + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediastore diff --git a/clients/client-mediastore/package.json b/clients/client-mediastore/package.json index 86ca5fac2cde..3f246a31cd73 100644 --- a/clients/client-mediastore/package.json +++ b/clients/client-mediastore/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediastore", "description": "AWS SDK for JavaScript Mediastore Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediastore", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediatailor/CHANGELOG.md b/clients/client-mediatailor/CHANGELOG.md index 758150dfa3ab..d0c57be004f1 100644 --- a/clients/client-mediatailor/CHANGELOG.md +++ b/clients/client-mediatailor/CHANGELOG.md @@ -3,6 +3,17 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + + +### Features + +* **client-mediatailor:** Documenting that EnabledLoggingStrategies is always present in responses of PlaybackConfiguration read operations. ([bf0301e](https://github.com/aws/aws-sdk-js-v3/commit/bf0301e75e18738a573388c5af1e99dacd106fab)) + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/client-mediatailor diff --git a/clients/client-mediatailor/README.md b/clients/client-mediatailor/README.md index ec5213d4afe4..f51e7df4aee4 100644 --- a/clients/client-mediatailor/README.md +++ b/clients/client-mediatailor/README.md @@ -6,8 +6,7 @@ AWS SDK for JavaScript MediaTailor Client for Node.js, Browser and React Native. -Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
-Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
+Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
## Installing diff --git a/clients/client-mediatailor/package.json b/clients/client-mediatailor/package.json index 1770bb81d6ef..534f0a1dd62f 100644 --- a/clients/client-mediatailor/package.json +++ b/clients/client-mediatailor/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-mediatailor", "description": "AWS SDK for JavaScript Mediatailor Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-mediatailor", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-mediatailor/src/MediaTailor.ts b/clients/client-mediatailor/src/MediaTailor.ts index 56fc0a5c9d2b..76dbb842e018 100644 --- a/clients/client-mediatailor/src/MediaTailor.ts +++ b/clients/client-mediatailor/src/MediaTailor.ts @@ -920,8 +920,7 @@ export interface MediaTailor { } /** - *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
- *Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
+ *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
* @public */ export class MediaTailor extends MediaTailorClient implements MediaTailor {} diff --git a/clients/client-mediatailor/src/MediaTailorClient.ts b/clients/client-mediatailor/src/MediaTailorClient.ts index 36384d306ece..d289032d06a9 100644 --- a/clients/client-mediatailor/src/MediaTailorClient.ts +++ b/clients/client-mediatailor/src/MediaTailorClient.ts @@ -448,8 +448,7 @@ export type MediaTailorClientResolvedConfigType = __SmithyResolvedConfiguration< export interface MediaTailorClientResolvedConfig extends MediaTailorClientResolvedConfigType {} /** - *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
- *Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
+ *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
* @public */ export class MediaTailorClient extends __Client< diff --git a/clients/client-mediatailor/src/commands/GetPlaybackConfigurationCommand.ts b/clients/client-mediatailor/src/commands/GetPlaybackConfigurationCommand.ts index 87993666c2b5..ed6095795b54 100644 --- a/clients/client-mediatailor/src/commands/GetPlaybackConfigurationCommand.ts +++ b/clients/client-mediatailor/src/commands/GetPlaybackConfigurationCommand.ts @@ -75,7 +75,7 @@ export interface GetPlaybackConfigurationCommandOutput extends GetPlaybackConfig * // }, * // LogConfiguration: { // LogConfiguration * // PercentEnabled: Number("int"), // required - * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies + * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies // required * // "VENDED_LOGS" || "LEGACY_CLOUDWATCH", * // ], * // AdsInteractionLog: { // AdsInteractionLog diff --git a/clients/client-mediatailor/src/commands/ListPlaybackConfigurationsCommand.ts b/clients/client-mediatailor/src/commands/ListPlaybackConfigurationsCommand.ts index 1e596cde3b13..e0355f0cefb5 100644 --- a/clients/client-mediatailor/src/commands/ListPlaybackConfigurationsCommand.ts +++ b/clients/client-mediatailor/src/commands/ListPlaybackConfigurationsCommand.ts @@ -78,7 +78,7 @@ export interface ListPlaybackConfigurationsCommandOutput extends ListPlaybackCon * // }, * // LogConfiguration: { // LogConfiguration * // PercentEnabled: Number("int"), // required - * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies + * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies // required * // "VENDED_LOGS" || "LEGACY_CLOUDWATCH", * // ], * // AdsInteractionLog: { // AdsInteractionLog diff --git a/clients/client-mediatailor/src/commands/PutPlaybackConfigurationCommand.ts b/clients/client-mediatailor/src/commands/PutPlaybackConfigurationCommand.ts index 4d0e467b7c4d..e4333a5226ac 100644 --- a/clients/client-mediatailor/src/commands/PutPlaybackConfigurationCommand.ts +++ b/clients/client-mediatailor/src/commands/PutPlaybackConfigurationCommand.ts @@ -118,7 +118,7 @@ export interface PutPlaybackConfigurationCommandOutput extends PutPlaybackConfig * // }, * // LogConfiguration: { // LogConfiguration * // PercentEnabled: Number("int"), // required - * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies + * // EnabledLoggingStrategies: [ // __listOfLoggingStrategies // required * // "VENDED_LOGS" || "LEGACY_CLOUDWATCH", * // ], * // AdsInteractionLog: { // AdsInteractionLog diff --git a/clients/client-mediatailor/src/index.ts b/clients/client-mediatailor/src/index.ts index 902615487e3a..490ea89cdd8b 100644 --- a/clients/client-mediatailor/src/index.ts +++ b/clients/client-mediatailor/src/index.ts @@ -1,8 +1,7 @@ // smithy-typescript generated code /* eslint-disable */ /** - *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
- *Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
+ *Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
* * @packageDocumentation */ diff --git a/clients/client-mediatailor/src/models/models_0.ts b/clients/client-mediatailor/src/models/models_0.ts index 54fb48e44e7e..34ca6fa589cc 100644 --- a/clients/client-mediatailor/src/models/models_0.ts +++ b/clients/client-mediatailor/src/models/models_0.ts @@ -152,10 +152,7 @@ export interface SpliceInsertMessage { } /** - *The segmentation_descriptor message can contain advanced metadata fields, like content identifiers, to convey a wide range of information about the ad break. MediaTailor writes the ad metadata in the egress manifest as part of the EXT-X-DATERANGE or EventStream ad marker's SCTE-35 data.
- * segmentation_descriptor messages must be sent with the time_signal message type.
See the segmentation_descriptor() table of the 2022 SCTE-35 specification for more information.
The segmentation_descriptor message can contain advanced metadata fields, like content identifiers, to convey a wide range of information about the ad break. MediaTailor writes the ad metadata in the egress manifest as part of the EXT-X-DATERANGE or EventStream ad marker's SCTE-35 data.
segmentation_descriptor messages must be sent with the time_signal message type.
See the segmentation_descriptor() table of the 2022 SCTE-35 specification for more information.
The SCTE-35 time_signal message can be sent with one or more segmentation_descriptor messages. A time_signal message can be sent only if a single segmentation_descriptor message is sent.
The time_signal message contains only the splice_time field which is constructed using a given presentation timestamp. When sending a time_signal message, the splice_command_type field in the splice_info_section message is set to 6 (0x06).
See the time_signal() table of the 2022 SCTE-35 specification for more information.
The SCTE-35 time_signal message can be sent with one or more segmentation_descriptor messages. A time_signal message can be sent only if a single segmentation_descriptor message is sent.
The time_signal message contains only the splice_time field which is constructed using a given presentation timestamp. When sending a time_signal message, the splice_command_type field in the splice_info_section message is set to 6 (0x06).
See the time_signal() table of the 2022 SCTE-35 specification for more information.
Defines the SCTE-35 time_signal message inserted around the ad.
Programs on a channel's schedule can be configured with one or more ad breaks. You can attach a splice_insert SCTE-35 message to the ad break. This message provides basic metadata about the ad break.
See section 9.7.4 of the 2022 SCTE-35 specification for more information.
+ *Defines the SCTE-35 time_signal message inserted around the ad.
Programs on a channel's schedule can be configured with one or more ad breaks. You can attach a splice_insert SCTE-35 message to the ad break. This message provides basic metadata about the ad break.
See section 9.7.4 of the 2022 SCTE-35 specification for more information.
* @public */ TimeSignalMessage?: TimeSignalMessage | undefined; @@ -421,15 +414,12 @@ export const Operator = { export type Operator = (typeof Operator)[keyof typeof Operator]; /** - *MediaTailor only places (consumes) prefetched ads if the ad break meets the criteria defined by the dynamic variables. This gives you granular control over which ad break to place the prefetched ads into.
- *As an example, let's say that you set DynamicVariable to scte.event_id and Operator to EQUALS, and your playback configuration has an ADS URL of https://my.ads.server.com/path?&podId=[scte.avail_num]&event=[scte.event_id]&duration=[session.avail_duration_secs]. And the prefetch request to the ADS contains these values https://my.ads.server.com/path?&podId=3&event=my-awesome-event&duration=30. MediaTailor will only insert the prefetched ads into the ad break if has a SCTE marker with an event id of my-awesome-event, since it must match the event id that MediaTailor uses to query the ADS.
You can specify up to five AvailMatchingCriteria. If you specify multiple AvailMatchingCriteria, MediaTailor combines them to match using a logical AND. You can model logical OR combinations by creating multiple prefetch schedules.
MediaTailor only places (consumes) prefetched ads if the ad break meets the criteria defined by the dynamic variables. This gives you granular control over which ad break to place the prefetched ads into.
As an example, let's say that you set DynamicVariable to scte.event_id and Operator to EQUALS, and your playback configuration has an ADS URL of https://my.ads.server.com/path?&podId=[scte.avail_num]&event=[scte.event_id]&duration=[session.avail_duration_secs]. And the prefetch request to the ADS contains these values https://my.ads.server.com/path?&podId=3&event=my-awesome-event&duration=30. MediaTailor will only insert the prefetched ads into the ad break if has a SCTE marker with an event id of my-awesome-event, since it must match the event id that MediaTailor uses to query the ADS.
You can specify up to five AvailMatchingCriteria. If you specify multiple AvailMatchingCriteria, MediaTailor combines them to match using a logical AND. You can model logical OR combinations by creating multiple prefetch schedules.
The dynamic variable(s) that MediaTailor should use as avail matching criteria. MediaTailor only places the prefetched ads into the avail if the avail matches the criteria defined by the dynamic variable. For information about dynamic variables, see Using dynamic ad variables in the MediaTailor User Guide.
- *You can include up to 100 dynamic variables.
+ *The dynamic variable(s) that MediaTailor should use as avail matching criteria. MediaTailor only places the prefetched ads into the avail if the avail matches the criteria defined by the dynamic variable. For information about dynamic variables, see Using dynamic ad variables in the MediaTailor User Guide.
You can include up to 100 dynamic variables.
* @public */ DynamicVariable: string | undefined; @@ -594,9 +584,7 @@ export interface Channel { CreationTime?: Date | undefined; /** - *The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR
- * PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP
- * PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode for this channel.
- *
- * LINEAR - Programs play back-to-back only once.
- * LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
The type of playback mode for this channel.
LINEAR - Programs play back-to-back only once.
LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
For ads that have media files with streaming delivery and supported file extensions, indicates what transcoding action MediaTailor takes when it first receives these ads from the ADS.
- * TRANSCODE indicates that MediaTailor must transcode the ads.
- * NONE indicates that you have already transcoded the ads outside of MediaTailor and don't need them transcoded as part of the ad insertion workflow.
- * For more information about ad conditioning see Using preconditioned ads in the Elemental MediaTailor user guide.
For ads that have media files with streaming delivery and supported file extensions, indicates what transcoding action MediaTailor takes when it first receives these ads from the ADS. TRANSCODE indicates that MediaTailor must transcode the ads. NONE indicates that you have already transcoded the ads outside of MediaTailor and don't need them transcoded as part of the ad insertion workflow. For more information about ad conditioning see Using preconditioned ads in the Elemental MediaTailor user guide.
Settings for customizing what events are included in logs for interactions with the ad decision server (ADS).
- *For more information about ADS logs, inlcuding descriptions of the event types, see MediaTailor ADS logs description and event types - * in Elemental MediaTailor User Guide.
+ *Settings for customizing what events are included in logs for interactions with the ad decision server (ADS).
For more information about ADS logs, inlcuding descriptions of the event types, see MediaTailor ADS logs description and event types in Elemental MediaTailor User Guide.
* @public */ export interface AdsInteractionLog { @@ -1015,9 +994,7 @@ export type ManifestServiceExcludeEventType = (typeof ManifestServiceExcludeEventType)[keyof typeof ManifestServiceExcludeEventType]; /** - *Settings for customizing what events are included in logs for interactions with the origin server.
- *For more information about manifest service logs, including descriptions of the event types, see MediaTailor manifest logs description and event types - * in Elemental MediaTailor User Guide.
+ *Settings for customizing what events are included in logs for interactions with the origin server.
For more information about manifest service logs, including descriptions of the event types, see MediaTailor manifest logs description and event types in Elemental MediaTailor User Guide.
* @public */ export interface ManifestServiceInteractionLog { @@ -1034,9 +1011,7 @@ export interface ManifestServiceInteractionLog { */ export interface LogConfiguration { /** - *The percentage of session logs that MediaTailor sends to your configured log destination. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
- *
The percentage of session logs that MediaTailor sends to your configured log destination. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
The method used for collecting logs from AWS Elemental MediaTailor. LEGACY_CLOUDWATCH indicates that MediaTailor is sending logs directly to Amazon CloudWatch Logs. VENDED_LOGS indicates that MediaTailor is sending logs to CloudWatch, which then vends the logs to your destination of choice. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
Settings for customizing what events are included in logs for interactions with the ad decision server (ADS).
@@ -1061,8 +1036,7 @@ export interface LogConfiguration { } /** - *For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
With recurring prefetch, MediaTailor automatically prefetches ads for every avail that occurs during the retrieval window. The following - * configurations describe the MediaTailor behavior when prefetching ads for a live event.
+ *With recurring prefetch, MediaTailor automatically prefetches ads for every avail that occurs during the retrieval window. The following configurations describe the MediaTailor behavior when prefetching ads for a live event.
* @public */ export interface RecurringRetrieval { @@ -1352,8 +1324,7 @@ export interface RecurringPrefetchConfiguration { */ export interface PrefetchRetrieval { /** - *The dynamic variables to use for substitution during prefetch requests to the ad decision server (ADS).
- *You initially configure dynamic variables for the ADS URL when you set up your playback configuration. When you specify DynamicVariables for prefetch retrieval, MediaTailor includes the dynamic variables in the request to the ADS.
The dynamic variables to use for substitution during prefetch requests to the ad decision server (ADS).
You initially configure dynamic variables for the ADS URL when you set up your playback configuration. When you specify DynamicVariables for prefetch retrieval, MediaTailor includes the dynamic variables in the request to the ADS.
The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor. - *
+ *The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.
* @public */ ScheduleType?: PrefetchScheduleType | undefined; @@ -1633,23 +1602,7 @@ export interface SecretsManagerAccessTokenConfiguration { */ export interface AccessConfiguration { /** - *The type of authentication used to access content from HttpConfiguration::BaseUrl on your source location.
- * S3_SIGV4 - AWS Signature Version 4 authentication for Amazon S3 hosted virtual-style access. If your source location base URL is an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the bucket where your source content is stored. Your MediaTailor source location baseURL must follow the S3 virtual hosted-style request URL format. For example, https://bucket-name.s3.Region.amazonaws.com/key-name.
Before you can use S3_SIGV4, you must meet these requirements:
• You must allow MediaTailor to access your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For information about configuring access in IAM, see Access management in the IAM User Guide.
- *• The mediatailor.amazonaws.com service principal must have permissions to read all top level manifests referenced by the VodSource packaging configurations.
- *• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
- *
- * AUTODETECT_SIGV4 - AWS Signature Version 4 authentication for a set of supported services: MediaPackage Version 2 and Amazon S3 hosted virtual-style access. If your source location base URL is a MediaPackage Version 2 endpoint or an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the resource where your source content is stored.
Before you can use AUTODETECT_SIGV4 with a MediaPackage Version 2 endpoint, you must meet these requirements:
• You must grant MediaTailor access to your MediaPackage endpoint by granting mediatailor.amazonaws.com principal access in an Origin Access policy on the endpoint.
• Your MediaTailor source location base URL must be a MediaPackage V2 endpoint.
- *• The caller of the API must have mediapackagev2:GetObject IAM permissions to read all top level manifests referenced by the MediaTailor source packaging configurations.
Before you can use AUTODETECT_SIGV4 with an Amazon S3 bucket, you must meet these requirements:
• You must grant MediaTailor access to your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For more information about configuring access in IAM, see Access management in the IAM User Guide..
• The mediatailor.amazonaws.com service principal must have permissions to read all top-level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
The type of authentication used to access content from HttpConfiguration::BaseUrl on your source location.
S3_SIGV4 - AWS Signature Version 4 authentication for Amazon S3 hosted virtual-style access. If your source location base URL is an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the bucket where your source content is stored. Your MediaTailor source location baseURL must follow the S3 virtual hosted-style request URL format. For example, https://bucket-name.s3.Region.amazonaws.com/key-name.
Before you can use S3_SIGV4, you must meet these requirements:
• You must allow MediaTailor to access your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For information about configuring access in IAM, see Access management in the IAM User Guide.
• The mediatailor.amazonaws.com service principal must have permissions to read all top level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
AUTODETECT_SIGV4 - AWS Signature Version 4 authentication for a set of supported services: MediaPackage Version 2 and Amazon S3 hosted virtual-style access. If your source location base URL is a MediaPackage Version 2 endpoint or an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the resource where your source content is stored.
Before you can use AUTODETECT_SIGV4 with a MediaPackage Version 2 endpoint, you must meet these requirements:
• You must grant MediaTailor access to your MediaPackage endpoint by granting mediatailor.amazonaws.com principal access in an Origin Access policy on the endpoint.
• Your MediaTailor source location base URL must be a MediaPackage V2 endpoint.
• The caller of the API must have mediapackagev2:GetObject IAM permissions to read all top level manifests referenced by the MediaTailor source packaging configurations.
Before you can use AUTODETECT_SIGV4 with an Amazon S3 bucket, you must meet these requirements:
• You must grant MediaTailor access to your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For more information about configuring access in IAM, see Access management in the IAM User Guide..
• The mediatailor.amazonaws.com service principal must have permissions to read all top-level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
- * The configuration for time-shifted viewing. - *
+ *The configuration for time-shifted viewing.
* @public */ export interface TimeShiftConfiguration { /** - *- * The maximum time delay for time-shifted viewing. The minimum allowed maximum time delay is 0 seconds, - * and the maximum allowed maximum time delay is 21600 seconds (6 hours). - *
+ *The maximum time delay for time-shifted viewing. The minimum allowed maximum time delay is 0 seconds, and the maximum allowed maximum time delay is 21600 seconds (6 hours).
* @public */ MaxTimeDelaySeconds: number | undefined; @@ -2007,9 +1955,7 @@ export interface CreateChannelRequest { ChannelName: string | undefined; /** - *The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR
- * PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP
- * PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode to use for this channel.
- *
- * LINEAR - The programs in the schedule play once back-to-back in the schedule.
- * LOOP - The programs in the schedule play back-to-back in an endless loop. When the last program in the schedule stops playing, playback loops back to the first program in the schedule.
The type of playback mode to use for this channel.
LINEAR - The programs in the schedule play once back-to-back in the schedule.
LOOP - The programs in the schedule play back-to-back in an endless loop. When the last program in the schedule stops playing, playback loops back to the first program in the schedule.
- * The time-shifted viewing configuration you want to associate to the channel. - *
+ *The time-shifted viewing configuration you want to associate to the channel.
* @public */ TimeShiftConfiguration?: TimeShiftConfiguration | undefined; @@ -2136,9 +2076,7 @@ export interface CreateChannelResponse { Tier?: string | undefined; /** - *- * The time-shifted viewing configuration assigned to the channel. - *
+ *The time-shifted viewing configuration assigned to the channel.
* @public */ TimeShiftConfiguration?: TimeShiftConfiguration | undefined; @@ -2248,9 +2186,7 @@ export interface DescribeChannelResponse { LogConfiguration: LogConfigurationForChannel | undefined; /** - *- * The time-shifted viewing configuration for the channel. - *
+ *The time-shifted viewing configuration for the channel.
* @public */ TimeShiftConfiguration?: TimeShiftConfiguration | undefined; @@ -2285,10 +2221,7 @@ export interface GetChannelScheduleRequest { MaxResults?: number | undefined; /** - *(Optional) If the playback configuration has more than MaxResults channel schedules, use NextToken to get the second and subsequent pages of results.
For the first GetChannelScheduleRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more channel schedules to get.
(Optional) If the playback configuration has more than MaxResults channel schedules, use NextToken to get the second and subsequent pages of results.
For the first GetChannelScheduleRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more channel schedules to get.
Defines when the program plays in the schedule. You can set the value to ABSOLUTE or RELATIVE.
- * ABSOLUTE - The program plays at a specific wall clock time. This setting can only be used for channels using the LINEAR
- * PlaybackMode.
Note the following considerations when using ABSOLUTE transitions:
If the preceding program in the schedule has a duration that extends past the wall clock time, MediaTailor truncates the preceding program on a common segment boundary.
- *If there are gaps in playback, MediaTailor plays the FillerSlate you configured for your linear channel.
- * RELATIVE - The program is inserted into the schedule either before or after a program that you specify via RelativePosition.
Defines when the program plays in the schedule. You can set the value to ABSOLUTE or RELATIVE.
ABSOLUTE - The program plays at a specific wall clock time. This setting can only be used for channels using the LINEAR PlaybackMode.
Note the following considerations when using ABSOLUTE transitions:
If the preceding program in the schedule has a duration that extends past the wall clock time, MediaTailor truncates the preceding program on a common segment boundary.
If there are gaps in playback, MediaTailor plays the FillerSlate you configured for your linear channel.
RELATIVE - The program is inserted into the schedule either before or after a program that you specify via RelativePosition.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR
- * PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP
- * PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
- * The time-shifted viewing configuration you want to associate to the channel. - *
+ *The time-shifted viewing configuration you want to associate to the channel.
* @public */ TimeShiftConfiguration?: TimeShiftConfiguration | undefined; @@ -2921,9 +2842,7 @@ export interface UpdateChannelResponse { CreationTime?: Date | undefined; /** - *The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR
- * PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP
- * PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode for this channel.
- *
- * LINEAR - Programs play back-to-back only once.
- * LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
The type of playback mode for this channel.
LINEAR - Programs play back-to-back only once.
LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
- * The time-shifted viewing configuration for the channel. - *
+ *The time-shifted viewing configuration for the channel.
* @public */ TimeShiftConfiguration?: TimeShiftConfiguration | undefined; @@ -2983,9 +2896,7 @@ export interface UpdateChannelResponse { */ export interface ConfigureLogsForPlaybackConfigurationRequest { /** - *The percentage of session logs that MediaTailor sends to your CloudWatch Logs account. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
- *
The percentage of session logs that MediaTailor sends to your CloudWatch Logs account. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
The method used for collecting logs from AWS Elemental MediaTailor. To configure MediaTailor to send logs directly to Amazon CloudWatch Logs, choose LEGACY_CLOUDWATCH. To configure MediaTailor to
- * send logs to CloudWatch, which then vends the logs to your destination of choice, choose VENDED_LOGS. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
To use vended logs, you must configure the delivery destination in Amazon CloudWatch, as described in Enable logging from AWS services, Logging that requires additional permissions [V2].
+ *The method used for collecting logs from AWS Elemental MediaTailor. To configure MediaTailor to send logs directly to Amazon CloudWatch Logs, choose LEGACY_CLOUDWATCH. To configure MediaTailor to send logs to CloudWatch, which then vends the logs to your destination of choice, choose VENDED_LOGS. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
To use vended logs, you must configure the delivery destination in Amazon CloudWatch, as described in Enable logging from AWS services, Logging that requires additional permissions [V2].
* @public */ EnabledLoggingStrategies?: LoggingStrategy[] | undefined; @@ -3163,9 +3072,7 @@ export interface CreatePrefetchScheduleRequest { RecurringPrefetchConfiguration?: RecurringPrefetchConfiguration | undefined; /** - *The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor. - *
+ *The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.
* @public */ ScheduleType?: PrefetchScheduleType | undefined; @@ -4078,10 +3985,7 @@ export interface ListPrefetchSchedulesRequest { MaxResults?: number | undefined; /** - *(Optional) If the playback configuration has more than MaxResults prefetch schedules, use NextToken to get the second and subsequent pages of results.
For the first ListPrefetchSchedulesRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more prefetch schedules to get.
(Optional) If the playback configuration has more than MaxResults prefetch schedules, use NextToken to get the second and subsequent pages of results.
For the first ListPrefetchSchedulesRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more prefetch schedules to get.
The type of prefetch schedules that you want to list. SINGLE indicates that you want to list the configured single prefetch schedules. RECURRING
- * indicates that you want to list the configured recurring prefetch schedules. ALL indicates that you want to list all configured prefetch schedules.
The type of prefetch schedules that you want to list. SINGLE indicates that you want to list the configured single prefetch schedules. RECURRING indicates that you want to list the configured recurring prefetch schedules. ALL indicates that you want to list all configured prefetch schedules.
Provides APIs for creating and managing SageMaker resources.
-Other Resources:
-Provides APIs for creating and managing SageMaker resources.
Other Resources:
## Installing diff --git a/clients/client-sagemaker/package.json b/clients/client-sagemaker/package.json index 101c941dd20c..4fe098ce41ee 100644 --- a/clients/client-sagemaker/package.json +++ b/clients/client-sagemaker/package.json @@ -1,7 +1,7 @@ { "name": "@aws-sdk/client-sagemaker", "description": "AWS SDK for JavaScript Sagemaker Client for Node.js, Browser and React Native", - "version": "3.806.0", + "version": "3.808.0", "scripts": { "build": "concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", "build:cjs": "node ../../scripts/compilation/inline client-sagemaker", @@ -31,28 +31,28 @@ "@aws-sdk/util-endpoints": "*", "@aws-sdk/util-user-agent-browser": "*", "@aws-sdk/util-user-agent-node": "*", - "@smithy/config-resolver": "^4.1.1", + "@smithy/config-resolver": "^4.1.2", "@smithy/core": "^3.3.1", "@smithy/fetch-http-handler": "^5.0.2", "@smithy/hash-node": "^4.0.2", "@smithy/invalid-dependency": "^4.0.2", "@smithy/middleware-content-length": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/middleware-retry": "^4.1.4", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/middleware-retry": "^4.1.5", "@smithy/middleware-serde": "^4.0.3", "@smithy/middleware-stack": "^4.0.2", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/node-http-handler": "^4.0.4", "@smithy/protocol-http": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/url-parser": "^4.0.2", "@smithy/util-base64": "^4.0.0", "@smithy/util-body-length-browser": "^4.0.0", "@smithy/util-body-length-node": "^4.0.0", - "@smithy/util-defaults-mode-browser": "^4.0.11", - "@smithy/util-defaults-mode-node": "^4.0.11", - "@smithy/util-endpoints": "^3.0.3", + "@smithy/util-defaults-mode-browser": "^4.0.12", + "@smithy/util-defaults-mode-node": "^4.0.12", + "@smithy/util-endpoints": "^3.0.4", "@smithy/util-middleware": "^4.0.2", "@smithy/util-retry": "^4.0.3", "@smithy/util-utf8": "^4.0.0", diff --git a/clients/client-sagemaker/src/SageMaker.ts b/clients/client-sagemaker/src/SageMaker.ts index 228b3e530d13..a078bf1b9fe4 100644 --- a/clients/client-sagemaker/src/SageMaker.ts +++ b/clients/client-sagemaker/src/SageMaker.ts @@ -7707,22 +7707,7 @@ export interface SageMaker { } /** - *Provides APIs for creating and managing SageMaker resources.
- *Other Resources:
- *- * SageMaker Developer - * Guide - *
- *Provides APIs for creating and managing SageMaker resources.
Other Resources:
* @public */ export class SageMaker extends SageMakerClient implements SageMaker {} diff --git a/clients/client-sagemaker/src/SageMakerClient.ts b/clients/client-sagemaker/src/SageMakerClient.ts index c16e08bc69f8..d1a22ca8103d 100644 --- a/clients/client-sagemaker/src/SageMakerClient.ts +++ b/clients/client-sagemaker/src/SageMakerClient.ts @@ -1909,22 +1909,7 @@ export type SageMakerClientResolvedConfigType = __SmithyResolvedConfiguration<__ export interface SageMakerClientResolvedConfig extends SageMakerClientResolvedConfigType {} /** - *Provides APIs for creating and managing SageMaker resources.
- *Other Resources:
- *- * SageMaker Developer - * Guide - *
- *Provides APIs for creating and managing SageMaker resources.
Other Resources:
* @public */ export class SageMakerClient extends __Client< diff --git a/clients/client-sagemaker/src/commands/AddAssociationCommand.ts b/clients/client-sagemaker/src/commands/AddAssociationCommand.ts index 225f86e6f5c8..2a58128ed382 100644 --- a/clients/client-sagemaker/src/commands/AddAssociationCommand.ts +++ b/clients/client-sagemaker/src/commands/AddAssociationCommand.ts @@ -28,11 +28,7 @@ export interface AddAssociationCommandInput extends AddAssociationRequest {} export interface AddAssociationCommandOutput extends AddAssociationResponse, __MetadataBearer {} /** - *Creates an association between the source and the destination. A - * source can be associated with multiple destinations, and a destination can be associated - * with multiple sources. An association is a lineage tracking entity. For more information, see - * Amazon SageMaker - * ML Lineage Tracking.
+ *Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -60,8 +56,7 @@ export interface AddAssociationCommandOutput extends AddAssociationResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/AddTagsCommand.ts b/clients/client-sagemaker/src/commands/AddTagsCommand.ts index 3a2f5373a621..2b053836ce1f 100644 --- a/clients/client-sagemaker/src/commands/AddTagsCommand.ts +++ b/clients/client-sagemaker/src/commands/AddTagsCommand.ts @@ -28,32 +28,7 @@ export interface AddTagsCommandInput extends AddTagsInput {} export interface AddTagsCommandOutput extends AddTagsOutput, __MetadataBearer {} /** - *Adds or overwrites one or more tags for the specified SageMaker resource. You can add - * tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform - * jobs, models, labeling jobs, work teams, endpoint configurations, and - * endpoints.
- *Each tag consists of a key and an optional value. Tag keys must be unique per - * resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
- *Tags that you add to a hyperparameter tuning job by calling this API are also
- * added to any training jobs that the hyperparameter tuning job launches after you
- * call this API, but not to training jobs that the hyperparameter tuning job launched
- * before you called this API. To make sure that the tags associated with a
- * hyperparameter tuning job are also added to all training jobs that the
- * hyperparameter tuning job launches, add the tags when you first create the tuning
- * job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
- *
Tags that you add to a SageMaker Domain or User Profile by calling this API are
- * also added to any Apps that the Domain or User Profile launches after you call this
- * API, but not to Apps that the Domain or User Profile launched before you called this
- * API. To make sure that the tags associated with a Domain or User Profile are also
- * added to all Apps that the Domain or User Profile launches, add the tags when you
- * first create the Domain or User Profile by specifying them in the Tags
- * parameter of CreateDomain
- * or CreateUserProfile.
Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
Associates a trial component with a trial. A trial component can be associated with - * multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
+ *Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -56,8 +55,7 @@ export interface AssociateTrialComponentCommandOutput extends AssociateTrialComp * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/BatchDeleteClusterNodesCommand.ts b/clients/client-sagemaker/src/commands/BatchDeleteClusterNodesCommand.ts index 28321296bcf8..6fa9e2225752 100644 --- a/clients/client-sagemaker/src/commands/BatchDeleteClusterNodesCommand.ts +++ b/clients/client-sagemaker/src/commands/BatchDeleteClusterNodesCommand.ts @@ -28,23 +28,7 @@ export interface BatchDeleteClusterNodesCommandInput extends BatchDeleteClusterN export interface BatchDeleteClusterNodesCommandOutput extends BatchDeleteClusterNodesResponse, __MetadataBearer {} /** - *Deletes specific nodes within a SageMaker HyperPod cluster. BatchDeleteClusterNodes
- * accepts a cluster name and a list of node IDs.
To safeguard your work, back up your data to Amazon S3 or an FSx for - * Lustre file system before invoking the API on a worker node group. This will help - * prevent any potential data loss from the instance root volume. For more - * information about backup, see Use the backup script provided by SageMaker HyperPod.
- *If you want to invoke this API on an existing cluster, you'll first need to - * patch the cluster by running the UpdateClusterSoftware API. For more information about patching a - * cluster, see Update the SageMaker HyperPod platform software of a cluster.
- *Deletes specific nodes within a SageMaker HyperPod cluster. BatchDeleteClusterNodes accepts a cluster name and a list of node IDs.
To safeguard your work, back up your data to Amazon S3 or an FSx for Lustre file system before invoking the API on a worker node group. This will help prevent any potential data loss from the instance root volume. For more information about backup, see Use the backup script provided by SageMaker HyperPod.
If you want to invoke this API on an existing cluster, you'll first need to patch the cluster by running the UpdateClusterSoftware API. For more information about patching a cluster, see Update the SageMaker HyperPod platform software of a cluster.
Creates an action. An action is a lineage tracking entity that - * represents an action or activity. For example, a model deployment or an HPO job. - * Generally, an action involves at least one input or output artifact. For more information, see - * Amazon SageMaker - * ML Lineage Tracking.
+ *Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -80,8 +76,7 @@ export interface CreateActionCommandOutput extends CreateActionResponse, __Metad * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateAppCommand.ts b/clients/client-sagemaker/src/commands/CreateAppCommand.ts index 39c014fdf75f..4caf039b6bf1 100644 --- a/clients/client-sagemaker/src/commands/CreateAppCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateAppCommand.ts @@ -28,10 +28,7 @@ export interface CreateAppCommandInput extends CreateAppRequest {} export interface CreateAppCommandOutput extends CreateAppResponse, __MetadataBearer {} /** - *Creates a running app for the specified UserProfile. This operation is automatically - * invoked by Amazon SageMaker AI upon access to the associated Domain, and when new kernel - * configurations are selected by the user. A user may have multiple Apps active - * simultaneously.
+ *Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker AI upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -77,8 +74,7 @@ export interface CreateAppCommandOutput extends CreateAppResponse, __MetadataBea *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateAppImageConfigCommand.ts b/clients/client-sagemaker/src/commands/CreateAppImageConfigCommand.ts index e11cae85eaee..f6e8df1a959d 100644 --- a/clients/client-sagemaker/src/commands/CreateAppImageConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateAppImageConfigCommand.ts @@ -28,9 +28,7 @@ export interface CreateAppImageConfigCommandInput extends CreateAppImageConfigRe export interface CreateAppImageConfigCommandOutput extends CreateAppImageConfigResponse, __MetadataBearer {} /** - *Creates a configuration for running a SageMaker AI image as a KernelGateway app. The - * configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the - * kernels in the image.
+ *Creates a configuration for running a SageMaker AI image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/CreateArtifactCommand.ts b/clients/client-sagemaker/src/commands/CreateArtifactCommand.ts index 7cc1e1074406..0677c1189424 100644 --- a/clients/client-sagemaker/src/commands/CreateArtifactCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateArtifactCommand.ts @@ -28,11 +28,7 @@ export interface CreateArtifactCommandInput extends CreateArtifactRequest {} export interface CreateArtifactCommandOutput extends CreateArtifactResponse, __MetadataBearer {} /** - *Creates an artifact. An artifact is a lineage tracking entity that - * represents a URI addressable object or data. Some examples are the S3 URI of a dataset and - * the ECR registry path of an image. For more information, see - * Amazon SageMaker - * ML Lineage Tracking.
+ *Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -82,8 +78,7 @@ export interface CreateArtifactCommandOutput extends CreateArtifactResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts b/clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts index 366e759f6469..29fceaabdc57 100644 --- a/clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateAutoMLJobCommand.ts @@ -28,30 +28,7 @@ export interface CreateAutoMLJobCommandInput extends CreateAutoMLJobRequest {} export interface CreateAutoMLJobCommandOutput extends CreateAutoMLJobResponse, __MetadataBearer {} /** - *Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
- *An AutoML job in SageMaker AI is a fully automated process that allows you to build machine - * learning models with minimal effort and machine learning expertise. When initiating an - * AutoML job, you provide your data and optionally specify parameters tailored to your use - * case. SageMaker AI then automates the entire model development lifecycle, including data - * preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify - * and accelerate the model building process by automating various tasks and exploring - * different combinations of machine learning algorithms, data preprocessing techniques, and - * hyperparameter values. The output of an AutoML job comprises one or more trained models - * ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate - * model leaderboard, allowing you to select the best-performing model for deployment.
- *For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html - * in the SageMaker AI developer guide.
- *We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
- *
- * CreateAutoMLJobV2 can manage tabular problem types identical to those of
- * its previous version CreateAutoMLJob, as well as time-series forecasting,
- * non-tabular problem types such as image or text classification, and text generation
- * (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to
- * CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
+ *Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -147,8 +124,7 @@ export interface CreateAutoMLJobCommandOutput extends CreateAutoMLJobResponse, _ *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts b/clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts index 162024498805..5d4bcefd9ce8 100644 --- a/clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts +++ b/clients/client-sagemaker/src/commands/CreateAutoMLJobV2Command.ts @@ -28,37 +28,7 @@ export interface CreateAutoMLJobV2CommandInput extends CreateAutoMLJobV2Request export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Response, __MetadataBearer {} /** - *Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
- *An AutoML job in SageMaker AI is a fully automated process that allows you to build machine - * learning models with minimal effort and machine learning expertise. When initiating an - * AutoML job, you provide your data and optionally specify parameters tailored to your use - * case. SageMaker AI then automates the entire model development lifecycle, including data - * preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify - * and accelerate the model building process by automating various tasks and exploring - * different combinations of machine learning algorithms, data preprocessing techniques, and - * hyperparameter values. The output of an AutoML job comprises one or more trained models - * ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate - * model leaderboard, allowing you to select the best-performing model for deployment.
- *For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html - * in the SageMaker AI developer guide.
- *AutoML jobs V2 support various problem types such as regression, binary, and multiclass - * classification with tabular data, text and image classification, time-series forecasting, - * and fine-tuning of large language models (LLMs) for text generation.
- *- * CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob - * and DescribeAutoMLJob which offer backward compatibility.
- *
- * CreateAutoMLJobV2 can manage tabular problem types identical to those of
- * its previous version CreateAutoMLJob, as well as time-series forecasting,
- * non-tabular problem types such as image or text classification, and text generation
- * (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to
- * CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see
- * AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
+ *Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.
AutoML jobs V2 support various problem types such as regression, binary, and multiclass classification with tabular data, text and image classification, time-series forecasting, and fine-tuning of large language models (LLMs) for text generation.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -236,8 +206,7 @@ export interface CreateAutoMLJobV2CommandOutput extends CreateAutoMLJobV2Respons *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateClusterCommand.ts b/clients/client-sagemaker/src/commands/CreateClusterCommand.ts index c3846a5d2241..c0f0568794b7 100644 --- a/clients/client-sagemaker/src/commands/CreateClusterCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateClusterCommand.ts @@ -28,10 +28,7 @@ export interface CreateClusterCommandInput extends CreateClusterRequest {} export interface CreateClusterCommandOutput extends CreateClusterResponse, __MetadataBearer {} /** - *Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing - * persistent clusters for developing large machine learning models, such as large language - * models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the - * Amazon SageMaker Developer Guide.
+ *Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -132,8 +129,7 @@ export interface CreateClusterCommandOutput extends CreateClusterResponse, __Met *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateClusterSchedulerConfigCommand.ts b/clients/client-sagemaker/src/commands/CreateClusterSchedulerConfigCommand.ts index 86dcd1a4cba5..c625d2ef8d5a 100644 --- a/clients/client-sagemaker/src/commands/CreateClusterSchedulerConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateClusterSchedulerConfigCommand.ts @@ -33,9 +33,7 @@ export interface CreateClusterSchedulerConfigCommandOutput __MetadataBearer {} /** - *Create cluster policy configuration. This policy is used for task prioritization and - * fair-share allocation of idle compute. This helps prioritize critical workloads and distributes - * idle compute across entities.
+ *Create cluster policy configuration. This policy is used for task prioritization and fair-share allocation of idle compute. This helps prioritize critical workloads and distributes idle compute across entities.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -78,12 +76,10 @@ export interface CreateClusterSchedulerConfigCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateCodeRepositoryCommand.ts b/clients/client-sagemaker/src/commands/CreateCodeRepositoryCommand.ts index da0866971f43..bca1701cfe32 100644 --- a/clients/client-sagemaker/src/commands/CreateCodeRepositoryCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateCodeRepositoryCommand.ts @@ -28,13 +28,7 @@ export interface CreateCodeRepositoryCommandInput extends CreateCodeRepositoryIn export interface CreateCodeRepositoryCommandOutput extends CreateCodeRepositoryOutput, __MetadataBearer {} /** - *Creates a Git repository as a resource in your SageMaker AI account. You can - * associate the repository with notebook instances so that you can use Git source control - * for the notebooks you create. The Git repository is a resource in your SageMaker AI - * account, so it can be associated with more than one notebook instance, and it persists - * independently from the lifecycle of any notebook instances it is associated with.
- *The repository can be hosted either in Amazon Web Services CodeCommit - * or in any other Git repository.
+ *Creates a Git repository as a resource in your SageMaker AI account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker AI account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/CreateCompilationJobCommand.ts b/clients/client-sagemaker/src/commands/CreateCompilationJobCommand.ts index bb6cdd9461ef..75fcb49dfed4 100644 --- a/clients/client-sagemaker/src/commands/CreateCompilationJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateCompilationJobCommand.ts @@ -28,37 +28,7 @@ export interface CreateCompilationJobCommandInput extends CreateCompilationJobRe export interface CreateCompilationJobCommandOutput extends CreateCompilationJobResponse, __MetadataBearer {} /** - *Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the - * resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
- *If - * you choose to host your model using Amazon SageMaker AI hosting services, you can use the resulting - * model artifacts as part of the model. You can also use the artifacts with - * Amazon Web Services IoT Greengrass. In that case, deploy them as an ML - * resource.
- *In the request body, you provide the following:
- *A name for the compilation job
- *Information about the input model artifacts
- *The output location for the compiled model and the device (target) that the - * model runs on
- *The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker AI assumes to perform - * the model compilation job.
- *You can also provide a Tag to track the model compilation job's resource
- * use and costs. The response body contains the
- * CompilationJobArn
- * for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation - * job, use DescribeCompilationJob. To get information about multiple model compilation - * jobs, use ListCompilationJobs.
+ *Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker AI hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker AI assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -124,8 +94,7 @@ export interface CreateCompilationJobCommandOutput extends CreateCompilationJobR *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateComputeQuotaCommand.ts b/clients/client-sagemaker/src/commands/CreateComputeQuotaCommand.ts index 1e89792f99e1..fb301b5d4916 100644 --- a/clients/client-sagemaker/src/commands/CreateComputeQuotaCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateComputeQuotaCommand.ts @@ -28,9 +28,7 @@ export interface CreateComputeQuotaCommandInput extends CreateComputeQuotaReques export interface CreateComputeQuotaCommandOutput extends CreateComputeQuotaResponse, __MetadataBearer {} /** - *Create compute allocation definition. This defines how compute is allocated, shared, and - * borrowed for specified entities. Specifically, how to lend and borrow idle compute and - * assign a fair-share weight to the specified entities.
+ *Create compute allocation definition. This defines how compute is allocated, shared, and borrowed for specified entities. Specifically, how to lend and borrow idle compute and assign a fair-share weight to the specified entities.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -82,12 +80,10 @@ export interface CreateComputeQuotaCommandOutput extends CreateComputeQuotaRespo * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateContextCommand.ts b/clients/client-sagemaker/src/commands/CreateContextCommand.ts index e581c404bdec..9756a1b6f676 100644 --- a/clients/client-sagemaker/src/commands/CreateContextCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateContextCommand.ts @@ -28,11 +28,7 @@ export interface CreateContextCommandInput extends CreateContextRequest {} export interface CreateContextCommandOutput extends CreateContextResponse, __MetadataBearer {} /** - *Creates a context. A context is a lineage tracking entity that - * represents a logical grouping of other tracking or experiment entities. Some examples are - * an endpoint and a model package. For more information, see - * Amazon SageMaker - * ML Lineage Tracking.
+ *Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -73,8 +69,7 @@ export interface CreateContextCommandOutput extends CreateContextResponse, __Met * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateDataQualityJobDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateDataQualityJobDefinitionCommand.ts index 0cacd74e6186..bf1fc93cc3dc 100644 --- a/clients/client-sagemaker/src/commands/CreateDataQualityJobDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateDataQualityJobDefinitionCommand.ts @@ -33,9 +33,7 @@ export interface CreateDataQualityJobDefinitionCommandOutput __MetadataBearer {} /** - *Creates a definition for a job that monitors data quality and drift. For information - * about model monitor, see Amazon SageMaker AI Model - * Monitor.
+ *Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -165,8 +163,7 @@ export interface CreateDataQualityJobDefinitionCommandOutput *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateDeviceFleetCommand.ts b/clients/client-sagemaker/src/commands/CreateDeviceFleetCommand.ts index e1ef3c87fbf8..b12eac142f80 100644 --- a/clients/client-sagemaker/src/commands/CreateDeviceFleetCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateDeviceFleetCommand.ts @@ -69,8 +69,7 @@ export interface CreateDeviceFleetCommandOutput extends __MetadataBearer {} *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateDomainCommand.ts b/clients/client-sagemaker/src/commands/CreateDomainCommand.ts index 5760074a3edf..9b9929ae78ab 100644 --- a/clients/client-sagemaker/src/commands/CreateDomainCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateDomainCommand.ts @@ -28,50 +28,7 @@ export interface CreateDomainCommandInput extends CreateDomainRequest {} export interface CreateDomainCommandOutput extends CreateDomainResponse, __MetadataBearer {} /** - *Creates a Domain. A domain consists of an associated Amazon Elastic File System
- * volume, a list of authorized users, and a variety of security, application, policy, and
- * Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files
- * and other artifacts with each other.
- * EFS storage - *
- *When a domain is created, an EFS volume is created for use by all of the users within the - * domain. Each user receives a private home directory within the EFS volume for notebooks, Git - * repositories, and data files.
- *SageMaker AI uses the Amazon Web Services Key Management Service (Amazon Web Services - * KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key - * by default. For more control, you can specify a customer managed key. For more information, - * see Protect Data - * at Rest Using Encryption.
- *- * VPC configuration - *
- *All traffic between the domain and the Amazon EFS volume is through the specified
- * VPC and subnets. For other traffic, you can specify the AppNetworkAccessType
- * parameter. AppNetworkAccessType corresponds to the network access type that you
- * choose when you onboard to the domain. The following options are available:
- * PublicInternetOnly - Non-EFS traffic goes through a VPC managed by
- * Amazon SageMaker AI, which allows internet access. This is the default value.
- * VpcOnly - All traffic is through the specified VPC and subnets. Internet
- * access is disabled by default. To allow internet access, you must specify a NAT
- * gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker AI - * Studio notebook or to train or host models unless your VPC has an interface endpoint to - * the SageMaker AI API and runtime or a NAT gateway and your security groups allow - * outbound connections.
- *NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules - * in order to launch a Amazon SageMaker AI Studio app successfully.
- *For more information, see Connect Amazon SageMaker AI Studio Notebooks to Resources in a VPC.
+ *Creates a Domain. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker AI uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker AI, which allows internet access. This is the default value.
VpcOnly - All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker AI Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker AI API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker AI Studio app successfully.
For more information, see Connect Amazon SageMaker AI Studio Notebooks to Resources in a VPC.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -442,8 +399,7 @@ export interface CreateDomainCommandOutput extends CreateDomainResponse, __Metad *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateEdgeDeploymentPlanCommand.ts b/clients/client-sagemaker/src/commands/CreateEdgeDeploymentPlanCommand.ts index fe236d8e80a0..dc0cbd12c7b2 100644 --- a/clients/client-sagemaker/src/commands/CreateEdgeDeploymentPlanCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateEdgeDeploymentPlanCommand.ts @@ -28,8 +28,7 @@ export interface CreateEdgeDeploymentPlanCommandInput extends CreateEdgeDeployme export interface CreateEdgeDeploymentPlanCommandOutput extends CreateEdgeDeploymentPlanResponse, __MetadataBearer {} /** - *Creates an edge deployment plan, consisting of multiple stages. Each stage may have a - * different deployment configuration and devices.
+ *Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -83,8 +82,7 @@ export interface CreateEdgeDeploymentPlanCommandOutput extends CreateEdgeDeploym * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateEdgeDeploymentStageCommand.ts b/clients/client-sagemaker/src/commands/CreateEdgeDeploymentStageCommand.ts index cbd6333628f9..c6f2cb616f47 100644 --- a/clients/client-sagemaker/src/commands/CreateEdgeDeploymentStageCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateEdgeDeploymentStageCommand.ts @@ -67,8 +67,7 @@ export interface CreateEdgeDeploymentStageCommandOutput extends __MetadataBearer * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateEdgePackagingJobCommand.ts b/clients/client-sagemaker/src/commands/CreateEdgePackagingJobCommand.ts index 733a33a79bad..cc80f59a5d38 100644 --- a/clients/client-sagemaker/src/commands/CreateEdgePackagingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateEdgePackagingJobCommand.ts @@ -68,8 +68,7 @@ export interface CreateEdgePackagingJobCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateEndpointCommand.ts b/clients/client-sagemaker/src/commands/CreateEndpointCommand.ts index a49ceabfb9fb..b69c014d75b6 100644 --- a/clients/client-sagemaker/src/commands/CreateEndpointCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateEndpointCommand.ts @@ -28,81 +28,7 @@ export interface CreateEndpointCommandInput extends CreateEndpointInput {} export interface CreateEndpointCommandOutput extends CreateEndpointOutput, __MetadataBearer {} /** - *Creates an endpoint using the endpoint configuration specified in the request. SageMaker - * uses the endpoint to provision resources and deploy models. You create the endpoint - * configuration with the CreateEndpointConfig API.
- *Use this API to deploy models using SageMaker hosting services.
- * You must not delete an EndpointConfig that is in use by an endpoint
- * that is live or while the UpdateEndpoint or CreateEndpoint
- * operations are being performed on the endpoint. To update an endpoint, you must
- * create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your - * Amazon Web Services account.
- *When it receives the request, SageMaker creates the endpoint, launches the resources (ML - * compute instances), and deploys the model(s) on them.
- *When you call CreateEndpoint, a load call is made to DynamoDB to verify that your
- * endpoint configuration exists. When you read data from a DynamoDB table supporting
- *
- * Eventually Consistent Reads
- * , the response might not
- * reflect the results of a recently completed write operation. The response might
- * include some stale data. If the dependent entities are not yet in DynamoDB, this
- * causes a validation error. If you repeat your read request after a short time, the
- * response should return the latest data. So retry logic is recommended to handle
- * these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB
- * eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to
- * Creating. After it creates the endpoint, it sets the status to
- * InService. SageMaker can then process incoming requests for inferences. To
- * check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, - * SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the - * S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services - * account by default. If you previously deactivated Amazon Web Services STS for a region, - * you need to reactivate Amazon Web Services STS for that region. For more information, see - * Activating and - * Deactivating Amazon Web Services STS in an Amazon Web Services Region in the - * Amazon Web Services Identity and Access Management User - * Guide.
- *To add the IAM role policies for using this API operation, go to the IAM console, and choose - * Roles in the left navigation pane. Search the IAM role that you want to grant - * access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the - * role.
- *Option 1: For a full SageMaker access, search and attach the
- * AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the - * following Action elements manually into the JSON file of the IAM role:
- *
- * "Action": ["sagemaker:CreateEndpoint",
- * "sagemaker:CreateEndpointConfig"]
- *
- * "Resource": [
- *
- * "arn:aws:sagemaker:region:account-id:endpoint/endpointName"
- *
- * "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
- *
- * ]
- *
For more information, see SageMaker API - * Permissions: Actions, Permissions, and Resources - * Reference.
- *Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
"Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
"Resource": [
"arn:aws:sagemaker:region:account-id:endpoint/endpointName"
"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateEndpointConfigCommand.ts b/clients/client-sagemaker/src/commands/CreateEndpointConfigCommand.ts index b491a96519cf..0780da51a463 100644 --- a/clients/client-sagemaker/src/commands/CreateEndpointConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateEndpointConfigCommand.ts @@ -28,37 +28,7 @@ export interface CreateEndpointConfigCommandInput extends CreateEndpointConfigIn export interface CreateEndpointConfigCommandOutput extends CreateEndpointConfigOutput, __MetadataBearer {} /** - *Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In
- * the configuration, you identify one or more models, created using the
- * CreateModel API, to deploy and the resources that you want SageMaker to
- * provision. Then you call the CreateEndpoint
- * API.
Use this API if you want to use SageMaker hosting services to deploy models into - * production.
- *In the request, you define a ProductionVariant, for each model that you
- * want to deploy. Each ProductionVariant parameter also describes the
- * resources that you want SageMaker to provision. This includes the number and type of ML
- * compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to
- * specify how much traffic you want to allocate to each model. For example, suppose that
- * you want to host two models, A and B, and you assign traffic weight 2 for model A and 1
- * for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to
- * model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your
- * endpoint configuration exists. When you read data from a DynamoDB table supporting
- *
- * Eventually Consistent Reads
- * , the response might not
- * reflect the results of a recently completed write operation. The response might
- * include some stale data. If the dependent entities are not yet in DynamoDB, this
- * causes a validation error. If you repeat your read request after a short time, the
- * response should return the latest data. So retry logic is recommended to handle
- * these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB
- * eventually consistent read.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateExperimentCommand.ts b/clients/client-sagemaker/src/commands/CreateExperimentCommand.ts index 4851ac19651b..da30fc337494 100644 --- a/clients/client-sagemaker/src/commands/CreateExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateExperimentCommand.ts @@ -28,26 +28,7 @@ export interface CreateExperimentCommandInput extends CreateExperimentRequest {} export interface CreateExperimentCommandOutput extends CreateExperimentResponse, __MetadataBearer {} /** - *Creates a SageMaker experiment. An experiment is a collection of - * trials that are observed, compared and evaluated as a group. A trial is - * a set of steps, called trial components, that produce a machine learning - * model.
- *In the Studio UI, trials are referred to as run groups and trial - * components are referred to as runs.
- *The goal of an experiment is to determine the components that produce the best model. - * Multiple trials are performed, each one isolating and measuring the impact of a change to one - * or more inputs, while keeping the remaining inputs constant.
- *When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial - * components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you - * must use the logging APIs provided by the SDK.
- *You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
- *To add a description to an experiment, specify the optional Description
- * parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To - * view an experiment's properties, call the DescribeExperiment API. To get a - * list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
+ *Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -80,8 +61,7 @@ export interface CreateExperimentCommandOutput extends CreateExperimentResponse, * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts index 493d1567398d..2001843c32e9 100644 --- a/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateFeatureGroupCommand.ts @@ -28,24 +28,7 @@ export interface CreateFeatureGroupCommandInput extends CreateFeatureGroupReques export interface CreateFeatureGroupCommandOutput extends CreateFeatureGroupResponse, __MetadataBearer {} /** - *Create a new FeatureGroup. A FeatureGroup is a group of
- * Features defined in the FeatureStore to describe a
- * Record.
The FeatureGroup defines the schema and features contained in the
- * FeatureGroup. A FeatureGroup definition is composed of a list
- * of Features, a RecordIdentifierFeatureName, an
- * EventTimeFeatureName and configurations for its OnlineStore
- * and OfflineStore. Check Amazon Web Services service
- * quotas to see the FeatureGroups quota for your Amazon Web Services
- * account.
Note that it can take approximately 10-15 minutes to provision an
- * OnlineStore
- * FeatureGroup with the InMemory
- * StorageType.
You must include at least one of OnlineStoreConfig and
- * OfflineStoreConfig to create a FeatureGroup.
Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore FeatureGroup with the InMemory StorageType.
You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateFlowDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateFlowDefinitionCommand.ts index aed298a47500..19ff2155cefa 100644 --- a/clients/client-sagemaker/src/commands/CreateFlowDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateFlowDefinitionCommand.ts @@ -94,8 +94,7 @@ export interface CreateFlowDefinitionCommandOutput extends CreateFlowDefinitionR *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateHubCommand.ts b/clients/client-sagemaker/src/commands/CreateHubCommand.ts index 8b4909081620..a867a8e0363c 100644 --- a/clients/client-sagemaker/src/commands/CreateHubCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateHubCommand.ts @@ -70,8 +70,7 @@ export interface CreateHubCommandOutput extends CreateHubResponse, __MetadataBea *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateHubContentReferenceCommand.ts b/clients/client-sagemaker/src/commands/CreateHubContentReferenceCommand.ts index 18c5514da672..ca98814ddb79 100644 --- a/clients/client-sagemaker/src/commands/CreateHubContentReferenceCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateHubContentReferenceCommand.ts @@ -66,8 +66,7 @@ export interface CreateHubContentReferenceCommandOutput extends CreateHubContent *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateHumanTaskUiCommand.ts b/clients/client-sagemaker/src/commands/CreateHumanTaskUiCommand.ts index 4bd8f83be98a..fd99c2fad4af 100644 --- a/clients/client-sagemaker/src/commands/CreateHumanTaskUiCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateHumanTaskUiCommand.ts @@ -65,8 +65,7 @@ export interface CreateHumanTaskUiCommandOutput extends CreateHumanTaskUiRespons *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateHyperParameterTuningJobCommand.ts b/clients/client-sagemaker/src/commands/CreateHyperParameterTuningJobCommand.ts index e86ebcf81656..221bc3285090 100644 --- a/clients/client-sagemaker/src/commands/CreateHyperParameterTuningJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateHyperParameterTuningJobCommand.ts @@ -33,22 +33,7 @@ export interface CreateHyperParameterTuningJobCommandOutput __MetadataBearer {} /** - *Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version - * of a model by running many training jobs on your dataset using the algorithm you choose - * and values for hyperparameters within ranges that you specify. It then chooses the - * hyperparameter values that result in a model that performs the best, as measured by an - * objective metric that you choose.
- *A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and - * trial components for each training job that it runs. You can view these entities in - * Amazon SageMaker Studio. For more information, see View - * Experiments, Trials, and Trial Components.
- *Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any hyperparameter fields. As part of the shared responsibility model, - * you are responsible for any potential exposure, unauthorized access, or - * compromise of your sensitive data if caused by any security-sensitive information included - * in the request hyperparameter variable or plain text fields..
- *Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request hyperparameter variable or plain text fields..
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateImageCommand.ts b/clients/client-sagemaker/src/commands/CreateImageCommand.ts index 19f6bce62a56..4f84d63a6722 100644 --- a/clients/client-sagemaker/src/commands/CreateImageCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateImageCommand.ts @@ -28,9 +28,7 @@ export interface CreateImageCommandInput extends CreateImageRequest {} export interface CreateImageCommandOutput extends CreateImageResponse, __MetadataBearer {} /** - *Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image - * version represents a container image stored in Amazon ECR. For more information, see - * Bring your own SageMaker AI image.
+ *Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker AI image.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -67,8 +65,7 @@ export interface CreateImageCommandOutput extends CreateImageResponse, __Metadat *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateImageVersionCommand.ts b/clients/client-sagemaker/src/commands/CreateImageVersionCommand.ts index 7c2a57eda72a..72945d0631b1 100644 --- a/clients/client-sagemaker/src/commands/CreateImageVersionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateImageVersionCommand.ts @@ -28,8 +28,7 @@ export interface CreateImageVersionCommandInput extends CreateImageVersionReques export interface CreateImageVersionCommandOutput extends CreateImageVersionResponse, __MetadataBearer {} /** - *Creates a version of the SageMaker AI image specified by ImageName. The version
- * represents the Amazon ECR container image specified by BaseImage.
Creates a version of the SageMaker AI image specified by ImageName. The version represents the Amazon ECR container image specified by BaseImage.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateInferenceComponentCommand.ts b/clients/client-sagemaker/src/commands/CreateInferenceComponentCommand.ts index 80a1b9c8ebae..1c4ab576a827 100644 --- a/clients/client-sagemaker/src/commands/CreateInferenceComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateInferenceComponentCommand.ts @@ -28,14 +28,7 @@ export interface CreateInferenceComponentCommandInput extends CreateInferenceCom export interface CreateInferenceComponentCommandOutput extends CreateInferenceComponentOutput, __MetadataBearer {} /** - *Creates an inference component, which is a SageMaker AI hosting object that you can - * use to deploy a model to an endpoint. In the inference component settings, you specify the - * model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You - * can optimize resource utilization by tailoring how the required CPU cores, accelerators, - * and memory are allocated. You can deploy multiple inference components to an endpoint, - * where each inference component contains one model and the resource utilization needs for - * that individual model. After you deploy an inference component, you can directly invoke the - * associated model when you use the InvokeEndpoint API action.
+ *Creates an inference component, which is a SageMaker AI hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -92,8 +85,7 @@ export interface CreateInferenceComponentCommandOutput extends CreateInferenceCo * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateInferenceExperimentCommand.ts b/clients/client-sagemaker/src/commands/CreateInferenceExperimentCommand.ts index 7bb48380e366..73391209c631 100644 --- a/clients/client-sagemaker/src/commands/CreateInferenceExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateInferenceExperimentCommand.ts @@ -28,21 +28,7 @@ export interface CreateInferenceExperimentCommandInput extends CreateInferenceEx export interface CreateInferenceExperimentCommandOutput extends CreateInferenceExperimentResponse, __MetadataBearer {} /** - *- * Creates an inference experiment using the configurations specified in the request. - *
- *- * Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For - * more information about inference experiments, see Shadow tests. - *
- *- * Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based - * on your specified configuration. - *
- *- * While the experiment is in progress or after it has concluded, you can view metrics that compare your model - * variants. For more information, see View, monitor, and edit shadow tests. - *
+ *Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -119,8 +105,7 @@ export interface CreateInferenceExperimentCommandOutput extends CreateInferenceE *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateInferenceRecommendationsJobCommand.ts b/clients/client-sagemaker/src/commands/CreateInferenceRecommendationsJobCommand.ts index 89ce7966ffed..d872c2ee4ede 100644 --- a/clients/client-sagemaker/src/commands/CreateInferenceRecommendationsJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateInferenceRecommendationsJobCommand.ts @@ -36,8 +36,7 @@ export interface CreateInferenceRecommendationsJobCommandOutput __MetadataBearer {} /** - *Starts a recommendation job. You can create either an instance - * recommendation or load test job.
+ *Starts a recommendation job. You can create either an instance recommendation or load test job.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -170,8 +169,7 @@ export interface CreateInferenceRecommendationsJobCommandOutput *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateLabelingJobCommand.ts b/clients/client-sagemaker/src/commands/CreateLabelingJobCommand.ts index 016d24deb9c5..f3c4b0477168 100644 --- a/clients/client-sagemaker/src/commands/CreateLabelingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateLabelingJobCommand.ts @@ -28,44 +28,7 @@ export interface CreateLabelingJobCommandInput extends CreateLabelingJobRequest export interface CreateLabelingJobCommandOutput extends CreateLabelingJobResponse, __MetadataBearer {} /** - *Creates a job that uses workers to label the data objects in your input dataset. You - * can use the labeled data to train machine learning models.
- *You can select your workforce from one of three providers:
- *A private workforce that you create. It can include employees, contractors, - * and outside experts. Use a private workforce when want the data to stay within - * your organization or when a specific set of skills is required.
- *One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide - * expertise in specific areas.
- *The Amazon Mechanical Turk workforce. This is the largest workforce, but it - * should only be used for public data or data that has been stripped of any - * personally identifiable information.
- *You can also use automated data labeling to reduce the number of - * data objects that need to be labeled by a human. Automated data labeling uses - * active learning to determine if a data object can be labeled by - * machine or if it needs to be sent to a human worker. For more information, see Using - * Automated Data Labeling.
- *The data objects to be labeled are contained in an Amazon S3 bucket. You create a - * manifest file that describes the location of each object. For - * more information, see Using Input and Output Data.
- *The output can be used as the manifest file for another labeling job or as training - * data for your machine learning models.
- *You can use this operation to create a static labeling job or a streaming labeling
- * job. A static labeling job stops if all data objects in the input manifest file
- * identified in ManifestS3Uri have been labeled. A streaming labeling job
- * runs perpetually until it is manually stopped, or remains idle for 10 days. You can send
- * new data objects to an active (InProgress) streaming labeling job in real
- * time. To learn how to create a static labeling job, see Create a Labeling Job
- * (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming
- * labeling job, see Create a Streaming Labeling
- * Job.
Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateMlflowTrackingServerCommand.ts b/clients/client-sagemaker/src/commands/CreateMlflowTrackingServerCommand.ts index b9898b7c7a94..43c1e68faf91 100644 --- a/clients/client-sagemaker/src/commands/CreateMlflowTrackingServerCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateMlflowTrackingServerCommand.ts @@ -28,9 +28,7 @@ export interface CreateMlflowTrackingServerCommandInput extends CreateMlflowTrac export interface CreateMlflowTrackingServerCommandOutput extends CreateMlflowTrackingServerResponse, __MetadataBearer {} /** - *Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact - * store. For more information, see Create an MLflow Tracking - * Server.
+ *Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store. For more information, see Create an MLflow Tracking Server.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -67,8 +65,7 @@ export interface CreateMlflowTrackingServerCommandOutput extends CreateMlflowTra * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelBiasJobDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateModelBiasJobDefinitionCommand.ts index 15965d0c8f5f..9677a4b2abbd 100644 --- a/clients/client-sagemaker/src/commands/CreateModelBiasJobDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelBiasJobDefinitionCommand.ts @@ -156,8 +156,7 @@ export interface CreateModelBiasJobDefinitionCommandOutput *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelCardCommand.ts b/clients/client-sagemaker/src/commands/CreateModelCardCommand.ts index 46e8a2521333..51daee7a70e3 100644 --- a/clients/client-sagemaker/src/commands/CreateModelCardCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelCardCommand.ts @@ -32,8 +32,7 @@ export interface CreateModelCardCommandInput extends CreateModelCardRequest {} export interface CreateModelCardCommandOutput extends CreateModelCardResponse, __MetadataBearer {} /** - *Creates an Amazon SageMaker Model Card.
- *For information about how to use model cards, see Amazon SageMaker Model Card.
+ *Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -69,12 +68,10 @@ export interface CreateModelCardCommandOutput extends CreateModelCardResponse, _ * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelCardExportJobCommand.ts b/clients/client-sagemaker/src/commands/CreateModelCardExportJobCommand.ts index 181908b7249e..d73a746929c1 100644 --- a/clients/client-sagemaker/src/commands/CreateModelCardExportJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelCardExportJobCommand.ts @@ -58,12 +58,10 @@ export interface CreateModelCardExportJobCommandOutput extends CreateModelCardEx * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateModelCommand.ts b/clients/client-sagemaker/src/commands/CreateModelCommand.ts index e1097c93eb22..460f07deb7bd 100644 --- a/clients/client-sagemaker/src/commands/CreateModelCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelCommand.ts @@ -28,23 +28,7 @@ export interface CreateModelCommandInput extends CreateModelInput {} export interface CreateModelCommandOutput extends CreateModelOutput, __MetadataBearer {} /** - *Creates a model in SageMaker. In the request, you name the model and describe a primary - * container. For the primary container, you specify the Docker image that - * contains inference code, artifacts (from prior training), and a custom environment map - * that the inference code uses when you deploy the model for predictions.
- *Use this API to create a model if you want to use SageMaker hosting services or run a batch - * transform job.
- *To host your model, you create an endpoint configuration with the
- * CreateEndpointConfig API, and then create an endpoint with the
- * CreateEndpoint API. SageMaker then deploys all of the containers that you
- * defined for the model in the hosting environment.
To run a batch transform using your model, you start a job with the
- * CreateTransformJob API. SageMaker uses your model and your dataset to get
- * inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model - * artifacts and docker image for deployment on ML compute hosting instances or for batch - * transform jobs. In addition, you also use the IAM role to manage permissions the - * inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
+ *Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -187,8 +171,7 @@ export interface CreateModelCommandOutput extends CreateModelOutput, __MetadataB * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelExplainabilityJobDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateModelExplainabilityJobDefinitionCommand.ts index 6eacc2b83353..5a08c5f0db86 100644 --- a/clients/client-sagemaker/src/commands/CreateModelExplainabilityJobDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelExplainabilityJobDefinitionCommand.ts @@ -157,8 +157,7 @@ export interface CreateModelExplainabilityJobDefinitionCommandOutput *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelPackageCommand.ts b/clients/client-sagemaker/src/commands/CreateModelPackageCommand.ts index 5f6edd4a83ae..aa0acd4faca9 100644 --- a/clients/client-sagemaker/src/commands/CreateModelPackageCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelPackageCommand.ts @@ -32,26 +32,7 @@ export interface CreateModelPackageCommandInput extends CreateModelPackageInput export interface CreateModelPackageCommandOutput extends CreateModelPackageOutput, __MetadataBearer {} /** - *Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers - * can subscribe to model packages listed on Amazon Web Services Marketplace to create - * models in SageMaker.
- *To create a model package by specifying a Docker container that contains your
- * inference code and the Amazon S3 location of your model artifacts, provide values for
- * InferenceSpecification. To create a model from an algorithm resource
- * that you created or subscribed to in Amazon Web Services Marketplace, provide a value for
- * SourceAlgorithmSpecification.
There are two types of model packages:
- *Versioned - a model that is part of a model group in the model - * registry.
- *Unversioned - a model package that is not part of a model group.
- *Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelPackageGroupCommand.ts b/clients/client-sagemaker/src/commands/CreateModelPackageGroupCommand.ts index c924a01e9c71..796931b11371 100644 --- a/clients/client-sagemaker/src/commands/CreateModelPackageGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelPackageGroupCommand.ts @@ -60,8 +60,7 @@ export interface CreateModelPackageGroupCommandOutput extends CreateModelPackage * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts b/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts index 826b827c99d3..9cd7bba15985 100644 --- a/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateModelQualityJobDefinitionCommand.ts @@ -33,9 +33,7 @@ export interface CreateModelQualityJobDefinitionCommandOutput __MetadataBearer {} /** - *Creates a definition for a job that monitors model quality and drift. For information - * about model monitor, see Amazon SageMaker AI Model - * Monitor.
+ *Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -166,8 +164,7 @@ export interface CreateModelQualityJobDefinitionCommandOutput *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts b/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts index 9ccc0c55feda..7d98c710d3b4 100644 --- a/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateMonitoringScheduleCommand.ts @@ -28,8 +28,7 @@ export interface CreateMonitoringScheduleCommandInput extends CreateMonitoringSc export interface CreateMonitoringScheduleCommandOutput extends CreateMonitoringScheduleResponse, __MetadataBearer {} /** - *Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to - * monitor the data captured for an Amazon SageMaker AI Endpoint.
+ *Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -172,8 +171,7 @@ export interface CreateMonitoringScheduleCommandOutput extends CreateMonitoringS *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateNotebookInstanceCommand.ts b/clients/client-sagemaker/src/commands/CreateNotebookInstanceCommand.ts index 9659bef93389..b941c2443be9 100644 --- a/clients/client-sagemaker/src/commands/CreateNotebookInstanceCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateNotebookInstanceCommand.ts @@ -28,42 +28,7 @@ export interface CreateNotebookInstanceCommandInput extends CreateNotebookInstan export interface CreateNotebookInstanceCommandOutput extends CreateNotebookInstanceOutput, __MetadataBearer {} /** - *Creates an SageMaker AI notebook instance. A notebook instance is a machine - * learning (ML) compute instance running on a Jupyter notebook.
- *In a CreateNotebookInstance request, specify the type of ML compute
- * instance that you want to run. SageMaker AI launches the instance, installs common
- * libraries that you can use to explore datasets for model training, and attaches an ML
- * storage volume to the notebook instance.
SageMaker AI also provides a set of example notebooks. Each notebook - * demonstrates how to use SageMaker AI with a specific algorithm or with a machine - * learning framework.
- *After receiving the request, SageMaker AI does the following:
- *Creates a network interface in the SageMaker AI VPC.
- *(Option) If you specified SubnetId, SageMaker AI creates
- * a network interface in your own VPC, which is inferred from the subnet ID that
- * you provide in the input. When creating this network interface, SageMaker AI attaches the security group that you specified in the request to the network
- * interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the
- * SageMaker AI VPC. If you specified SubnetId of your VPC,
- * SageMaker AI specifies both network interfaces when launching this
- * instance. This enables inbound traffic from your own VPC to the notebook
- * instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker AI returns its Amazon Resource - * Name (ARN). You can't change the name of a notebook instance after you create - * it.
- *After SageMaker AI creates the notebook instance, you can connect to the - * Jupyter server and work in Jupyter notebooks. For example, you can write code to explore - * a dataset that you can use for model training, train a model, host models by creating - * SageMaker AI endpoints, and validate hosted models.
- *For more information, see How It Works.
+ *Creates an SageMaker AI notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker AI launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker AI also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker AI with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker AI does the following:
Creates a network interface in the SageMaker AI VPC.
(Option) If you specified SubnetId, SageMaker AI creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker AI attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker AI VPC. If you specified SubnetId of your VPC, SageMaker AI specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker AI returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
After SageMaker AI creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker AI endpoints, and validate hosted models.
For more information, see How It Works.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -116,8 +81,7 @@ export interface CreateNotebookInstanceCommandOutput extends CreateNotebookInsta * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateNotebookInstanceLifecycleConfigCommand.ts b/clients/client-sagemaker/src/commands/CreateNotebookInstanceLifecycleConfigCommand.ts index b6891f84baef..6504e52ddcb7 100644 --- a/clients/client-sagemaker/src/commands/CreateNotebookInstanceLifecycleConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateNotebookInstanceLifecycleConfigCommand.ts @@ -36,20 +36,7 @@ export interface CreateNotebookInstanceLifecycleConfigCommandOutput __MetadataBearer {} /** - *Creates a lifecycle configuration that you can associate with a notebook instance. A - * lifecycle configuration is a collection of shell scripts that - * run when you create or start a notebook instance.
- *Each lifecycle configuration script has a limit of 16384 characters.
- *The value of the $PATH environment variable that is available to both
- * scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log
- * group /aws/sagemaker/NotebookInstances in log stream
- * [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs - * for longer than 5 minutes, it fails and the notebook instance is not created or - * started.
- *For information about notebook instance lifestyle configurations, see Step - * 2.1: (Optional) Customize a Notebook Instance.
+ *Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -90,8 +77,7 @@ export interface CreateNotebookInstanceLifecycleConfigCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateOptimizationJobCommand.ts b/clients/client-sagemaker/src/commands/CreateOptimizationJobCommand.ts index 2c38dff045cf..ad2d2dcf2ee7 100644 --- a/clients/client-sagemaker/src/commands/CreateOptimizationJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateOptimizationJobCommand.ts @@ -28,12 +28,7 @@ export interface CreateOptimizationJobCommandInput extends CreateOptimizationJob export interface CreateOptimizationJobCommandOutput extends CreateOptimizationJobResponse, __MetadataBearer {} /** - *Creates a job that optimizes a model for inference performance. To create the job, you - * provide the location of a source model, and you provide the settings for the optimization - * techniques that you want the job to apply. When the job completes successfully, SageMaker - * uploads the new optimized model to the output destination that you specify.
- *For more information about how to use this action, and about the supported optimization - * techniques, see Optimize model inference with Amazon SageMaker.
+ *Creates a job that optimizes a model for inference performance. To create the job, you provide the location of a source model, and you provide the settings for the optimization techniques that you want the job to apply. When the job completes successfully, SageMaker uploads the new optimized model to the output destination that you specify.
For more information about how to use this action, and about the supported optimization techniques, see Optimize model inference with Amazon SageMaker.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -119,8 +114,7 @@ export interface CreateOptimizationJobCommandOutput extends CreateOptimizationJo *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreatePartnerAppCommand.ts b/clients/client-sagemaker/src/commands/CreatePartnerAppCommand.ts index 3f960635cac6..26866c84338f 100644 --- a/clients/client-sagemaker/src/commands/CreatePartnerAppCommand.ts +++ b/clients/client-sagemaker/src/commands/CreatePartnerAppCommand.ts @@ -77,12 +77,10 @@ export interface CreatePartnerAppCommandOutput extends CreatePartnerAppResponse, * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreatePipelineCommand.ts b/clients/client-sagemaker/src/commands/CreatePipelineCommand.ts index 337c8bab78c1..9c93029fb6c1 100644 --- a/clients/client-sagemaker/src/commands/CreatePipelineCommand.ts +++ b/clients/client-sagemaker/src/commands/CreatePipelineCommand.ts @@ -72,12 +72,10 @@ export interface CreatePipelineCommandOutput extends CreatePipelineResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreatePresignedDomainUrlCommand.ts b/clients/client-sagemaker/src/commands/CreatePresignedDomainUrlCommand.ts index 16c990928f83..9ffc165f3553 100644 --- a/clients/client-sagemaker/src/commands/CreatePresignedDomainUrlCommand.ts +++ b/clients/client-sagemaker/src/commands/CreatePresignedDomainUrlCommand.ts @@ -28,32 +28,7 @@ export interface CreatePresignedDomainUrlCommandInput extends CreatePresignedDom export interface CreatePresignedDomainUrlCommandOutput extends CreatePresignedDomainUrlResponse, __MetadataBearer {} /** - *Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the - * user will be automatically signed in to the domain, and granted access to all of the Apps and - * files associated with the Domain's Amazon Elastic File System volume. This operation can only be - * called when the authentication mode equals IAM.
- *The IAM role or user passed to this API defines the permissions to access - * the app. Once the presigned URL is created, no additional permission is required to access - * this URL. IAM authorization policies for this API are also enforced for every - * HTTP request and WebSocket frame that attempts to connect to the app.
- *You can restrict access to this API and to the URL that it returns to a list of IP - * addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more - * information, see Connect to Amazon SageMaker AI - * Studio Through an Interface VPC Endpoint .
- *The URL that you get from a call to CreatePresignedDomainUrl has a
- * default timeout of 5 minutes. You can configure this value using
- * ExpiresInSeconds. If you try to use the URL after the timeout limit
- * expires, you are directed to the Amazon Web Services console sign-in page.
The JupyterLab session default expiration time is 12 hours. You can configure this - * value using SessionExpirationDurationInSeconds.
- *Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker AI Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
The JupyterLab session default expiration time is 12 hours. You can configure this value using SessionExpirationDurationInSeconds.
Returns a presigned URL that you can use to connect to the MLflow UI attached to your - * tracking server. For more information, see Launch the MLflow UI using a presigned URL.
+ *Returns a presigned URL that you can use to connect to the MLflow UI attached to your tracking server. For more information, see Launch the MLflow UI using a presigned URL.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/CreatePresignedNotebookInstanceUrlCommand.ts b/clients/client-sagemaker/src/commands/CreatePresignedNotebookInstanceUrlCommand.ts index 2c5118a372d3..dd055027312c 100644 --- a/clients/client-sagemaker/src/commands/CreatePresignedNotebookInstanceUrlCommand.ts +++ b/clients/client-sagemaker/src/commands/CreatePresignedNotebookInstanceUrlCommand.ts @@ -33,24 +33,7 @@ export interface CreatePresignedNotebookInstanceUrlCommandOutput __MetadataBearer {} /** - *Returns a URL that you can use to connect to the Jupyter server from a notebook
- * instance. In the SageMaker AI console, when you choose Open next to a
- * notebook instance, SageMaker AI opens a new tab showing the Jupyter server home
- * page from the notebook instance. The console uses this API to get the URL and show the
- * page.
The IAM role or user used to call this API defines the permissions to - * access the notebook instance. Once the presigned URL is created, no additional - * permission is required to access this URL. IAM authorization policies for - * this API are also enforced for every HTTP request and WebSocket frame that attempts to - * connect to the notebook instance.
- *You can restrict access to this API and to the URL that it returns to a list of IP
- * addresses that you specify. Use the NotIpAddress condition operator and the
- * aws:SourceIP condition context key to specify the list of IP addresses
- * that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you - * try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
- *Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker AI console, when you choose Open next to a notebook instance, SageMaker AI opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateProjectCommand.ts b/clients/client-sagemaker/src/commands/CreateProjectCommand.ts index 07b2e93e910c..a57fa34debc8 100644 --- a/clients/client-sagemaker/src/commands/CreateProjectCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateProjectCommand.ts @@ -28,8 +28,7 @@ export interface CreateProjectCommandInput extends CreateProjectInput {} export interface CreateProjectCommandOutput extends CreateProjectOutput, __MetadataBearer {} /** - *Creates a machine learning (ML) project that can contain one or more templates that set - * up an ML pipeline from training to deploying an approved model.
+ *Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -73,8 +72,7 @@ export interface CreateProjectCommandOutput extends CreateProjectOutput, __Metad * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateSpaceCommand.ts b/clients/client-sagemaker/src/commands/CreateSpaceCommand.ts index e6a109ffc62b..f33e0331eba1 100644 --- a/clients/client-sagemaker/src/commands/CreateSpaceCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateSpaceCommand.ts @@ -158,8 +158,7 @@ export interface CreateSpaceCommandOutput extends CreateSpaceResponse, __Metadat *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateTrainingJobCommand.ts b/clients/client-sagemaker/src/commands/CreateTrainingJobCommand.ts index de26c82cc93d..2bf42afff1af 100644 --- a/clients/client-sagemaker/src/commands/CreateTrainingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateTrainingJobCommand.ts @@ -28,92 +28,7 @@ export interface CreateTrainingJobCommandInput extends CreateTrainingJobRequest export interface CreateTrainingJobCommandOutput extends CreateTrainingJobResponse, __MetadataBearer {} /** - *Starts a model training job. After training completes, SageMaker saves the resulting - * model artifacts to an Amazon S3 location that you specify.
- *If you choose to host your model using SageMaker hosting services, you can use the - * resulting model artifacts as part of the model. You can also use the artifacts in a - * machine learning service other than SageMaker, provided that you know how to use them for - * inference. - *
- *In the request body, you provide the following:
- *
- * AlgorithmSpecification - Identifies the training algorithm to
- * use.
- *
- * HyperParameters - Specify these algorithm-specific parameters to
- * enable the estimation of model parameters during training. Hyperparameters can
- * be tuned to optimize this learning process. For a list of hyperparameters for
- * each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any hyperparameter fields. As part of the shared responsibility - * model, you are responsible for any potential exposure, unauthorized access, or compromise of - * your sensitive data if caused by security-sensitive information included in the - * request hyperparameter variable or plain text fields.
- *
- * InputDataConfig - Describes the input required by the training
- * job and the Amazon S3, EFS, or FSx location where it is stored.
- * OutputDataConfig - Identifies the Amazon S3 bucket where you want
- * SageMaker to save the results of model training.
- * ResourceConfig - Identifies the resources, ML compute
- * instances, and ML storage volumes to deploy for model training. In distributed
- * training, you specify more than one instance.
- * EnableManagedSpotTraining - Optimize the cost of training machine
- * learning models by up to 80% by using Amazon EC2 Spot instances. For more
- * information, see Managed Spot
- * Training.
- * RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on
- * your behalf during model training.
- *
- * You must grant this role the necessary permissions so that SageMaker can successfully
- * complete model training.
- * StoppingCondition - To help cap training costs, use
- * MaxRuntimeInSeconds to set a time limit for training. Use
- * MaxWaitTimeInSeconds to specify how long a managed spot
- * training job has to complete.
- * Environment - The environment variables to set in the Docker
- * container.
Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any environment fields. As part of the shared responsibility model, you are - * responsible for any potential exposure, unauthorized access, or compromise of your sensitive - * data if caused by security-sensitive information included in the request environment variable - * or plain text fields.
- *
- * RetryStrategy - The number of times to retry the job when the job
- * fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
+ *Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification - Identifies the training algorithm to use.
HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request hyperparameter variable or plain text fields.
InputDataConfig - Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
Environment - The environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -326,8 +241,7 @@ export interface CreateTrainingJobCommandOutput extends CreateTrainingJobRespons *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateTrainingPlanCommand.ts b/clients/client-sagemaker/src/commands/CreateTrainingPlanCommand.ts index 6255032aab90..f113f77fedd1 100644 --- a/clients/client-sagemaker/src/commands/CreateTrainingPlanCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateTrainingPlanCommand.ts @@ -28,67 +28,7 @@ export interface CreateTrainingPlanCommandInput extends CreateTrainingPlanReques export interface CreateTrainingPlanCommandOutput extends CreateTrainingPlanResponse, __MetadataBearer {} /** - *Creates a new training plan in SageMaker to reserve compute capacity.
- *Amazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU - * capacity for large-scale AI model training. It provides a way to secure predictable access - * to computational resources within specific timelines and budgets, without the need to - * manage underlying infrastructure.
- *- * How it works - *
- *Plans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod - * clusters, automatically provisioning resources, setting up infrastructure, executing - * workloads, and handling infrastructure failures.
- *- * Plan creation workflow - *
- *Users search for available plan offerings based on their requirements (e.g.,
- * instance type, count, start time, duration) using the
- * SearchTrainingPlanOfferings
- * API operation.
They create a plan that best matches their needs using the ID of the plan offering - * they want to use.
- *After successful upfront payment, the plan's status becomes
- * Scheduled.
The plan can be used to:
- *Queue training jobs.
- *Allocate to an instance group of a SageMaker HyperPod cluster.
- *When the plan start date arrives, it becomes Active. Based on
- * available reserved capacity:
Training jobs are launched.
- *Instance groups are provisioned.
- *- * Plan composition - *
- *A plan can consist of one or more Reserved Capacities, each defined by a specific
- * instance type, quantity, Availability Zone, duration, and start and end times. For more
- * information about Reserved Capacity, see
- * ReservedCapacitySummary
- * .
Creates a new training plan in SageMaker to reserve compute capacity.
Amazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU capacity for large-scale AI model training. It provides a way to secure predictable access to computational resources within specific timelines and budgets, without the need to manage underlying infrastructure.
How it works
Plans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod clusters, automatically provisioning resources, setting up infrastructure, executing workloads, and handling infrastructure failures.
Plan creation workflow
Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration) using the SearchTrainingPlanOfferings API operation.
They create a plan that best matches their needs using the ID of the plan offering they want to use.
After successful upfront payment, the plan's status becomes Scheduled.
The plan can be used to:
Queue training jobs.
Allocate to an instance group of a SageMaker HyperPod cluster.
When the plan start date arrives, it becomes Active. Based on available reserved capacity:
Training jobs are launched.
Instance groups are provisioned.
Plan composition
A plan can consist of one or more Reserved Capacities, each defined by a specific instance type, quantity, Availability Zone, duration, and start and end times. For more information about Reserved Capacity, see ReservedCapacitySummary .
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateTransformJobCommand.ts b/clients/client-sagemaker/src/commands/CreateTransformJobCommand.ts index f7ec10e29578..94189f2c1f81 100644 --- a/clients/client-sagemaker/src/commands/CreateTransformJobCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateTransformJobCommand.ts @@ -28,41 +28,7 @@ export interface CreateTransformJobCommandInput extends CreateTransformJobReques export interface CreateTransformJobCommandOutput extends CreateTransformJobResponse, __MetadataBearer {} /** - *Starts a transform job. A transform job uses a trained model to get inferences on a - * dataset and saves these results to an Amazon S3 location that you specify.
- *To perform batch transformations, you create a transform job and use the data that you - * have readily available.
- *In the request body, you provide the following:
- *
- * TransformJobName - Identifies the transform job. The name must be
- * unique within an Amazon Web Services Region in an Amazon Web Services account.
- * ModelName - Identifies the model to use. ModelName
- * must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services
- * account. For information on creating a model, see CreateModel.
- * TransformInput - Describes the dataset to be transformed and the
- * Amazon S3 location where it is stored.
- * TransformOutput - Identifies the Amazon S3 location where you want
- * Amazon SageMaker to save the results from the transform job.
- * TransformResources - Identifies the ML compute instances and AMI
- * image versions for the transform job.
For more information about how batch transformation works, see Batch - * Transform.
+ *Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources - Identifies the ML compute instances and AMI image versions for the transform job.
For more information about how batch transformation works, see Batch Transform.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -146,8 +112,7 @@ export interface CreateTransformJobCommandOutput extends CreateTransformJobRespo *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateTrialCommand.ts b/clients/client-sagemaker/src/commands/CreateTrialCommand.ts index f94e9a25bc75..2f497d785f8c 100644 --- a/clients/client-sagemaker/src/commands/CreateTrialCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateTrialCommand.ts @@ -28,17 +28,7 @@ export interface CreateTrialCommandInput extends CreateTrialRequest {} export interface CreateTrialCommandOutput extends CreateTrialResponse, __MetadataBearer {} /** - *Creates an SageMaker trial. A trial is a set of steps called - * trial components that produce a machine learning model. A trial is part - * of a single SageMaker experiment.
- *When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial - * components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you - * must use the logging APIs provided by the SDK.
- *You can add tags to a trial and then use the Search API to search for - * the tags.
- *To get a list of all your trials, call the ListTrials API. To view a - * trial's properties, call the DescribeTrial API. To create a trial component, - * call the CreateTrialComponent API.
+ *Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -77,8 +67,7 @@ export interface CreateTrialCommandOutput extends CreateTrialResponse, __Metadat * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/CreateTrialComponentCommand.ts b/clients/client-sagemaker/src/commands/CreateTrialComponentCommand.ts index 851f6c0ff6b7..e0a2d16b8411 100644 --- a/clients/client-sagemaker/src/commands/CreateTrialComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateTrialComponentCommand.ts @@ -28,16 +28,7 @@ export interface CreateTrialComponentCommandInput extends CreateTrialComponentRe export interface CreateTrialComponentCommandOutput extends CreateTrialComponentResponse, __MetadataBearer {} /** - *Creates a trial component, which is a stage of a machine learning - * trial. A trial is composed of one or more trial components. A trial - * component can be used in multiple trials.
- *Trial components include pre-processing jobs, training jobs, and batch transform - * jobs.
- *When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial - * components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you - * must use the logging APIs provided by the SDK.
- *You can add tags to a trial component and then use the Search API to - * search for the tags.
+ *Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -99,8 +90,7 @@ export interface CreateTrialComponentCommandOutput extends CreateTrialComponentR * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateUserProfileCommand.ts b/clients/client-sagemaker/src/commands/CreateUserProfileCommand.ts index 8533503fc9b7..e7855158898f 100644 --- a/clients/client-sagemaker/src/commands/CreateUserProfileCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateUserProfileCommand.ts @@ -28,13 +28,7 @@ export interface CreateUserProfileCommandInput extends CreateUserProfileRequest export interface CreateUserProfileCommandOutput extends CreateUserProfileResponse, __MetadataBearer {} /** - *Creates a user profile. A user profile represents a single user within a domain, and is - * the main way to reference a "person" for the purposes of sharing, reporting, and other - * user-oriented features. This entity is created when a user onboards to a domain. If an - * administrator invites a person by email or imports them from IAM Identity Center, a user - * profile is automatically created. A user profile is the primary holder of settings for an - * individual user and has a reference to the user's private Amazon Elastic File System home - * directory.
+ *Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to a domain. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System home directory.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -288,8 +282,7 @@ export interface CreateUserProfileCommandOutput extends CreateUserProfileRespons *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/CreateWorkforceCommand.ts b/clients/client-sagemaker/src/commands/CreateWorkforceCommand.ts index c27d825ec003..f1ca46101730 100644 --- a/clients/client-sagemaker/src/commands/CreateWorkforceCommand.ts +++ b/clients/client-sagemaker/src/commands/CreateWorkforceCommand.ts @@ -32,24 +32,7 @@ export interface CreateWorkforceCommandInput extends CreateWorkforceRequest {} export interface CreateWorkforceCommandOutput extends CreateWorkforceResponse, __MetadataBearer {} /** - *Use this operation to create a workforce. This operation will return an error - * if a workforce already exists in the Amazon Web Services Region that you specify. You can only - * create one workforce in each Amazon Web Services Region per Amazon Web Services account.
- *If you want to create a new workforce in an Amazon Web Services Region where
- * a workforce already exists, use the DeleteWorkforce API
- * operation to delete the existing workforce and then use CreateWorkforce
- * to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool
- * in CognitoConfig.
- * You can also create an Amazon Cognito workforce using the Amazon SageMaker console.
- * For more information, see
- *
- * Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP
- * configuration in OidcConfig. Your OIDC IdP must support groups
- * because groups are used by Ground Truth and Amazon A2I to create work teams.
- * For more information, see
- * Create a Private Workforce (OIDC IdP).
Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Creates a new work team for labeling your data. A work team is defined by one or more - * Amazon Cognito user pools. You must first create the user pools before you can create a work - * team.
- *You cannot create more than 25 work teams in an account and region.
+ *Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -92,8 +89,7 @@ export interface CreateWorkteamCommandOutput extends CreateWorkteamResponse, __M *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DeleteAlgorithmCommand.ts b/clients/client-sagemaker/src/commands/DeleteAlgorithmCommand.ts index 89dbfd2c39d1..2f725bf48c84 100644 --- a/clients/client-sagemaker/src/commands/DeleteAlgorithmCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteAlgorithmCommand.ts @@ -51,8 +51,7 @@ export interface DeleteAlgorithmCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DeleteArtifactCommand.ts b/clients/client-sagemaker/src/commands/DeleteArtifactCommand.ts index 0847b58d2033..8f28b13274df 100644 --- a/clients/client-sagemaker/src/commands/DeleteArtifactCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteArtifactCommand.ts @@ -28,8 +28,7 @@ export interface DeleteArtifactCommandInput extends DeleteArtifactRequest {} export interface DeleteArtifactCommandOutput extends DeleteArtifactResponse, __MetadataBearer {} /** - *Deletes an artifact. Either ArtifactArn or Source must be
- * specified.
Deletes an artifact. Either ArtifactArn or Source must be specified.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DeleteCompilationJobCommand.ts b/clients/client-sagemaker/src/commands/DeleteCompilationJobCommand.ts index d29e9231fd8e..35157514a9ec 100644 --- a/clients/client-sagemaker/src/commands/DeleteCompilationJobCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteCompilationJobCommand.ts @@ -28,14 +28,7 @@ export interface DeleteCompilationJobCommandInput extends DeleteCompilationJobRe export interface DeleteCompilationJobCommandOutput extends __MetadataBearer {} /** - *Deletes the specified compilation job. This action deletes only the compilation job - * resource in Amazon SageMaker AI. It doesn't delete other resources that are related to - * that job, such as the model artifacts that the job creates, the compilation logs in - * CloudWatch, the compiled model, or the IAM role.
- *You can delete a compilation job only if its current status is COMPLETED,
- * FAILED, or STOPPED. If the job status is
- * STARTING or INPROGRESS, stop the job, and then delete it
- * after its status becomes STOPPED.
Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker AI. It doesn't delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.
You can delete a compilation job only if its current status is COMPLETED, FAILED, or STOPPED. If the job status is STARTING or INPROGRESS, stop the job, and then delete it after its status becomes STOPPED.
Used to delete a domain. If you onboarded with IAM mode, you will need to delete your - * domain to onboard again using IAM Identity Center. Use with caution. All of the members of the - * domain will lose access to their EFS volume, including data, notebooks, and other artifacts. - *
+ *Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts index 1ae73b93868d..90cfdfcbb2bb 100644 --- a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentPlanCommand.ts @@ -28,8 +28,7 @@ export interface DeleteEdgeDeploymentPlanCommandInput extends DeleteEdgeDeployme export interface DeleteEdgeDeploymentPlanCommandOutput extends __MetadataBearer {} /** - *Deletes an edge deployment plan if (and only if) all the stages in the plan are - * inactive or there are no stages in the plan.
+ *Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts index e79eccd3ef2c..f37d0bedc3ef 100644 --- a/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEdgeDeploymentStageCommand.ts @@ -28,8 +28,7 @@ export interface DeleteEdgeDeploymentStageCommandInput extends DeleteEdgeDeploym export interface DeleteEdgeDeploymentStageCommandOutput extends __MetadataBearer {} /** - *Delete a stage in an edge deployment plan if (and only if) the stage is - * inactive.
+ *Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts b/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts index ebcea9063db7..d63b584ecfdf 100644 --- a/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteEndpointCommand.ts @@ -28,17 +28,7 @@ export interface DeleteEndpointCommandInput extends DeleteEndpointInput {} export interface DeleteEndpointCommandOutput extends __MetadataBearer {} /** - *Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the - * endpoint was created.
- *SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't - * need to use the RevokeGrant API call.
- *When you delete your endpoint, SageMaker asynchronously deletes associated endpoint
- * resources such as KMS key grants. You might still see these resources in your account
- * for a few minutes after deleting your endpoint. Do not delete or revoke the permissions
- * for your
- * ExecutionRoleArn
- * , otherwise SageMaker cannot delete these
- * resources.
Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig API
- * deletes only the specified configuration. It does not delete endpoints created using the
- * configuration.
You must not delete an EndpointConfig in use by an endpoint that is
- * live or while the UpdateEndpoint or CreateEndpoint operations
- * are being performed on the endpoint. If you delete the EndpointConfig of an
- * endpoint that is active or being created or updated you may lose visibility into the
- * instance type the endpoint is using. The endpoint must be deleted in order to stop
- * incurring charges.
Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted - * first. Use the ListTrials API to get a list of the trials associated with - * the experiment.
+ *Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/DeleteFeatureGroupCommand.ts index e4e8711b135f..d10449f652a3 100644 --- a/clients/client-sagemaker/src/commands/DeleteFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteFeatureGroupCommand.ts @@ -28,14 +28,7 @@ export interface DeleteFeatureGroupCommandInput extends DeleteFeatureGroupReques export interface DeleteFeatureGroupCommandOutput extends __MetadataBearer {} /** - *Delete the FeatureGroup and any data that was written to the
- * OnlineStore of the FeatureGroup. Data cannot be accessed from
- * the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your
- * OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore
- * FeatureGroup with the InMemory
- * StorageType.
Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore FeatureGroup with the InMemory StorageType.
Use this operation to delete a human task user interface (worker task template).
- *
- * To see a list of human task user interfaces
- * (work task templates) in your account, use ListHumanTaskUis.
- * When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob
- * API deletes only the tuning job entry that was created in SageMaker when you called the
- * CreateHyperParameterTuningJob API. It does not delete training jobs,
- * artifacts, or the IAM role that you specified when creating the model.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob API deletes only the tuning job entry that was created in SageMaker when you called the CreateHyperParameterTuningJob API. It does not delete training jobs, artifacts, or the IAM role that you specified when creating the model.
Deletes a SageMaker AI image and all versions of the image. The container images aren't - * deleted.
+ *Deletes a SageMaker AI image and all versions of the image. The container images aren't deleted.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteImageVersionCommand.ts b/clients/client-sagemaker/src/commands/DeleteImageVersionCommand.ts index 16e8d178c2b4..c326f0c84d8b 100644 --- a/clients/client-sagemaker/src/commands/DeleteImageVersionCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteImageVersionCommand.ts @@ -28,8 +28,7 @@ export interface DeleteImageVersionCommandInput extends DeleteImageVersionReques export interface DeleteImageVersionCommandOutput extends DeleteImageVersionResponse, __MetadataBearer {} /** - *Deletes a version of a SageMaker AI image. The container image the version represents isn't - * deleted.
+ *Deletes a version of a SageMaker AI image. The container image the version represents isn't deleted.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteInferenceExperimentCommand.ts b/clients/client-sagemaker/src/commands/DeleteInferenceExperimentCommand.ts index e166379abba9..5626eee19496 100644 --- a/clients/client-sagemaker/src/commands/DeleteInferenceExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteInferenceExperimentCommand.ts @@ -28,13 +28,7 @@ export interface DeleteInferenceExperimentCommandInput extends DeleteInferenceEx export interface DeleteInferenceExperimentCommandOutput extends DeleteInferenceExperimentResponse, __MetadataBearer {} /** - *Deletes an inference experiment.
- *- * This operation does not delete your endpoint, variants, or any underlying resources. This operation only - * deletes the metadata of your experiment. - *
- *Deletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DeleteModelCardCommand.ts b/clients/client-sagemaker/src/commands/DeleteModelCardCommand.ts index 35581ada7b11..58b22823af5d 100644 --- a/clients/client-sagemaker/src/commands/DeleteModelCardCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteModelCardCommand.ts @@ -51,8 +51,7 @@ export interface DeleteModelCardCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DeleteModelCommand.ts b/clients/client-sagemaker/src/commands/DeleteModelCommand.ts index a1f50cb75b07..e925663ff453 100644 --- a/clients/client-sagemaker/src/commands/DeleteModelCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteModelCommand.ts @@ -28,10 +28,7 @@ export interface DeleteModelCommandInput extends DeleteModelInput {} export interface DeleteModelCommandOutput extends __MetadataBearer {} /** - *Deletes a model. The DeleteModel API deletes only the model entry that
- * was created in SageMaker when you called the CreateModel API. It does not delete
- * model artifacts, inference code, or the IAM role that you specified when creating the
- * model.
Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes a model package.
- *A model package is used to create SageMaker models or list on Amazon Web Services - * Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services - * Marketplace to create models in SageMaker.
+ *Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -54,8 +51,7 @@ export interface DeleteModelPackageCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DeleteModelPackageGroupCommand.ts b/clients/client-sagemaker/src/commands/DeleteModelPackageGroupCommand.ts index 08bc94aab679..155e67f4bfad 100644 --- a/clients/client-sagemaker/src/commands/DeleteModelPackageGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteModelPackageGroupCommand.ts @@ -51,8 +51,7 @@ export interface DeleteModelPackageGroupCommandOutput extends __MetadataBearer { * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DeleteMonitoringScheduleCommand.ts b/clients/client-sagemaker/src/commands/DeleteMonitoringScheduleCommand.ts index 192dea791fbe..ea995cd6daf4 100644 --- a/clients/client-sagemaker/src/commands/DeleteMonitoringScheduleCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteMonitoringScheduleCommand.ts @@ -28,8 +28,7 @@ export interface DeleteMonitoringScheduleCommandInput extends DeleteMonitoringSc export interface DeleteMonitoringScheduleCommandOutput extends __MetadataBearer {} /** - *Deletes a monitoring schedule. Also stops the schedule had not already been stopped. - * This does not delete the job execution history of the monitoring schedule.
+ *Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteNotebookInstanceCommand.ts b/clients/client-sagemaker/src/commands/DeleteNotebookInstanceCommand.ts index 8a3236d962b2..4fa3ed14bd5f 100644 --- a/clients/client-sagemaker/src/commands/DeleteNotebookInstanceCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteNotebookInstanceCommand.ts @@ -28,12 +28,7 @@ export interface DeleteNotebookInstanceCommandInput extends DeleteNotebookInstan export interface DeleteNotebookInstanceCommandOutput extends __MetadataBearer {} /** - * Deletes an SageMaker AI notebook instance. Before you can delete a notebook
- * instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker AI removes the ML compute instance, and deletes the ML storage volume and the - * network interface associated with the notebook instance.
- * Deletes an SageMaker AI notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker AI removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DeletePipelineCommand.ts b/clients/client-sagemaker/src/commands/DeletePipelineCommand.ts index d4d420f9166c..2f63496630f9 100644 --- a/clients/client-sagemaker/src/commands/DeletePipelineCommand.ts +++ b/clients/client-sagemaker/src/commands/DeletePipelineCommand.ts @@ -28,10 +28,7 @@ export interface DeletePipelineCommandInput extends DeletePipelineRequest {} export interface DeletePipelineCommandOutput extends DeletePipelineResponse, __MetadataBearer {} /** - *Deletes a pipeline if there are no running instances of the pipeline. To delete a
- * pipeline, you must stop all running instances of the pipeline using the
- * StopPipelineExecution API. When you delete a pipeline, all instances of the
- * pipeline are deleted.
Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution API. When you delete a pipeline, all instances of the pipeline are deleted.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DeleteProjectCommand.ts b/clients/client-sagemaker/src/commands/DeleteProjectCommand.ts index 90a7112fa392..8471faee84ea 100644 --- a/clients/client-sagemaker/src/commands/DeleteProjectCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteProjectCommand.ts @@ -51,8 +51,7 @@ export interface DeleteProjectCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DeleteStudioLifecycleConfigCommand.ts b/clients/client-sagemaker/src/commands/DeleteStudioLifecycleConfigCommand.ts index 1f1d84ceeb80..26a6687b1ada 100644 --- a/clients/client-sagemaker/src/commands/DeleteStudioLifecycleConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteStudioLifecycleConfigCommand.ts @@ -28,10 +28,7 @@ export interface DeleteStudioLifecycleConfigCommandInput extends DeleteStudioLif export interface DeleteStudioLifecycleConfigCommandOutput extends __MetadataBearer {} /** - *Deletes the Amazon SageMaker AI Studio Lifecycle Configuration. In order to delete the - * Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You - * must also remove the Lifecycle Configuration from UserSettings in all Domains and - * UserProfiles.
+ *Deletes the Amazon SageMaker AI Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteTagsCommand.ts b/clients/client-sagemaker/src/commands/DeleteTagsCommand.ts index 6ce90a35f322..375cd68c605e 100644 --- a/clients/client-sagemaker/src/commands/DeleteTagsCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteTagsCommand.ts @@ -28,18 +28,7 @@ export interface DeleteTagsCommandInput extends DeleteTagsInput {} export interface DeleteTagsCommandOutput extends DeleteTagsOutput, __MetadataBearer {} /** - *Deletes the specified tags from an SageMaker resource.
- *To list a resource's tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the - * deleted tags are not removed from training jobs that the hyperparameter tuning job - * launched before you called this API.
- *When you call this API to delete tags from a SageMaker Domain or User Profile, the - * deleted tags are not removed from Apps that the SageMaker Domain or User Profile - * launched before you called this API.
- *Deletes the specified tags from an SageMaker resource.
To list a resource's tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.
Deletes the specified trial. All trial components that make up the trial must be deleted - * first. Use the DescribeTrialComponent API to get the list of trial - * components.
+ *Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteTrialComponentCommand.ts b/clients/client-sagemaker/src/commands/DeleteTrialComponentCommand.ts index c96d6a9c3680..6a186d23f604 100644 --- a/clients/client-sagemaker/src/commands/DeleteTrialComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteTrialComponentCommand.ts @@ -28,9 +28,7 @@ export interface DeleteTrialComponentCommandInput extends DeleteTrialComponentRe export interface DeleteTrialComponentCommandOutput extends DeleteTrialComponentResponse, __MetadataBearer {} /** - *Deletes the specified trial component. A trial component must be disassociated from all - * trials before the trial component can be deleted. To disassociate a trial component from a - * trial, call the DisassociateTrialComponent API.
+ *Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteUserProfileCommand.ts b/clients/client-sagemaker/src/commands/DeleteUserProfileCommand.ts index a5ebf34b2d3e..b624c2c28dd6 100644 --- a/clients/client-sagemaker/src/commands/DeleteUserProfileCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteUserProfileCommand.ts @@ -28,8 +28,7 @@ export interface DeleteUserProfileCommandInput extends DeleteUserProfileRequest export interface DeleteUserProfileCommandOutput extends __MetadataBearer {} /** - *Deletes a user profile. When a user profile is deleted, the user loses access to their EFS - * volume, including data, notebooks, and other artifacts.
+ *Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DeleteWorkforceCommand.ts b/clients/client-sagemaker/src/commands/DeleteWorkforceCommand.ts index a3314d5cfe16..830d3db07ea6 100644 --- a/clients/client-sagemaker/src/commands/DeleteWorkforceCommand.ts +++ b/clients/client-sagemaker/src/commands/DeleteWorkforceCommand.ts @@ -28,18 +28,7 @@ export interface DeleteWorkforceCommandInput extends DeleteWorkforceRequest {} export interface DeleteWorkforceCommandOutput extends DeleteWorkforceResponse, __MetadataBearer {} /** - *Use this operation to delete a workforce.
- *If you want to create a new workforce in an Amazon Web Services Region where - * a workforce already exists, use this operation to delete the - * existing workforce and then use CreateWorkforce - * to create a new workforce.
- *If a private workforce contains one or more work teams, you must use
- * the DeleteWorkteam
- * operation to delete all work teams before you delete the workforce.
- * If you try to delete a workforce that contains one or more work teams,
- * you will receive a ResourceInUse error.
Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will receive a ResourceInUse error.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts b/clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts index cd1e2c8f9f89..a43a2f24c80b 100644 --- a/clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeAutoMLJobCommand.ts @@ -28,11 +28,7 @@ export interface DescribeAutoMLJobCommandInput extends DescribeAutoMLJobRequest export interface DescribeAutoMLJobCommandOutput extends DescribeAutoMLJobResponse, __MetadataBearer {} /** - *Returns information about an AutoML job created by calling CreateAutoMLJob.
- *AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by
- * DescribeAutoMLJob.
Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob.
Returns information about an AutoML job created by calling CreateAutoMLJobV2 - * or CreateAutoMLJob.
+ *Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeClusterNodeCommand.ts b/clients/client-sagemaker/src/commands/DescribeClusterNodeCommand.ts index 32e68e9562c2..a6ee146a16ea 100644 --- a/clients/client-sagemaker/src/commands/DescribeClusterNodeCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeClusterNodeCommand.ts @@ -28,8 +28,7 @@ export interface DescribeClusterNodeCommandInput extends DescribeClusterNodeRequ export interface DescribeClusterNodeCommandOutput extends DescribeClusterNodeResponse, __MetadataBearer {} /** - *Retrieves information of a node (also called a instance - * interchangeably) of a SageMaker HyperPod cluster.
+ *Retrieves information of a node (also called a instance interchangeably) of a SageMaker HyperPod cluster.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeClusterSchedulerConfigCommand.ts b/clients/client-sagemaker/src/commands/DescribeClusterSchedulerConfigCommand.ts index 3416ad4ef698..4d41beb82e76 100644 --- a/clients/client-sagemaker/src/commands/DescribeClusterSchedulerConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeClusterSchedulerConfigCommand.ts @@ -33,9 +33,7 @@ export interface DescribeClusterSchedulerConfigCommandOutput __MetadataBearer {} /** - *Description of the cluster policy. This policy is used for task prioritization and - * fair-share allocation. This helps prioritize critical workloads and distributes - * idle compute across entities.
+ *Description of the cluster policy. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeCompilationJobCommand.ts b/clients/client-sagemaker/src/commands/DescribeCompilationJobCommand.ts index d30d99db7758..2b09df902e7e 100644 --- a/clients/client-sagemaker/src/commands/DescribeCompilationJobCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeCompilationJobCommand.ts @@ -28,9 +28,7 @@ export interface DescribeCompilationJobCommandInput extends DescribeCompilationJ export interface DescribeCompilationJobCommandOutput extends DescribeCompilationJobResponse, __MetadataBearer {} /** - *Returns information about a model compilation job.
- *To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation - * jobs, use ListCompilationJobs.
+ *Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeEndpointConfigCommand.ts b/clients/client-sagemaker/src/commands/DescribeEndpointConfigCommand.ts index 44033b4846ed..95999c4f3aac 100644 --- a/clients/client-sagemaker/src/commands/DescribeEndpointConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeEndpointConfigCommand.ts @@ -28,8 +28,7 @@ export interface DescribeEndpointConfigCommandInput extends DescribeEndpointConf export interface DescribeEndpointConfigCommandOutput extends DescribeEndpointConfigOutput, __MetadataBearer {} /** - *Returns the description of an endpoint configuration created using the
- * CreateEndpointConfig API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Use this operation to describe a FeatureGroup. The response includes
- * information on the creation time, FeatureGroup name, the unique identifier for
- * each FeatureGroup, and more.
Use this operation to describe a FeatureGroup. The response includes information on the creation time, FeatureGroup name, the unique identifier for each FeatureGroup, and more.
Returns a description of a hyperparameter tuning job, depending on the fields - * selected. These fields can include the name, Amazon Resource Name (ARN), job status of - * your tuning job and more.
+ *Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeInferenceRecommendationsJobCommand.ts b/clients/client-sagemaker/src/commands/DescribeInferenceRecommendationsJobCommand.ts index b48439c1cce8..1692385d07bd 100644 --- a/clients/client-sagemaker/src/commands/DescribeInferenceRecommendationsJobCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeInferenceRecommendationsJobCommand.ts @@ -36,8 +36,7 @@ export interface DescribeInferenceRecommendationsJobCommandOutput __MetadataBearer {} /** - *Provides the results of the Inference Recommender job. - * One or more recommendation jobs are returned.
+ *Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeLineageGroupCommand.ts b/clients/client-sagemaker/src/commands/DescribeLineageGroupCommand.ts index 1c0e68e42de1..17ded58a6d37 100644 --- a/clients/client-sagemaker/src/commands/DescribeLineageGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeLineageGroupCommand.ts @@ -28,9 +28,7 @@ export interface DescribeLineageGroupCommandInput extends DescribeLineageGroupRe export interface DescribeLineageGroupCommandOutput extends DescribeLineageGroupResponse, __MetadataBearer {} /** - *Provides a list of properties for the requested lineage group. - * For more information, see - * Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
+ *Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeModelCommand.ts b/clients/client-sagemaker/src/commands/DescribeModelCommand.ts index c914d0be5e60..52ce45c6759a 100644 --- a/clients/client-sagemaker/src/commands/DescribeModelCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeModelCommand.ts @@ -28,8 +28,7 @@ export interface DescribeModelCommandInput extends DescribeModelInput {} export interface DescribeModelCommandOutput extends DescribeModelOutput, __MetadataBearer {} /** - *Describes a model that you created using the CreateModel
- * API.
Describes a model that you created using the CreateModel API.
Returns a description of the specified model package, which is used to create SageMaker - * models or list them on Amazon Web Services Marketplace.
- *If you provided a KMS Key ID when you created your model package, - * you will see the KMS Decrypt API call in - * your CloudTrail logs when you use this API.
- *To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
+ *Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
If you provided a KMS Key ID when you created your model package, you will see the KMS Decrypt API call in your CloudTrail logs when you use this API.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeNotebookInstanceLifecycleConfigCommand.ts b/clients/client-sagemaker/src/commands/DescribeNotebookInstanceLifecycleConfigCommand.ts index 14017544863a..2fd3f2505300 100644 --- a/clients/client-sagemaker/src/commands/DescribeNotebookInstanceLifecycleConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeNotebookInstanceLifecycleConfigCommand.ts @@ -37,9 +37,7 @@ export interface DescribeNotebookInstanceLifecycleConfigCommandOutput __MetadataBearer {} /** - *Returns a description of a notebook instance lifecycle configuration.
- *For information about notebook instance lifestyle configurations, see Step - * 2.1: (Optional) Customize a Notebook Instance.
+ *Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeSubscribedWorkteamCommand.ts b/clients/client-sagemaker/src/commands/DescribeSubscribedWorkteamCommand.ts index f9e8613cf768..206f6f92dc22 100644 --- a/clients/client-sagemaker/src/commands/DescribeSubscribedWorkteamCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeSubscribedWorkteamCommand.ts @@ -28,8 +28,7 @@ export interface DescribeSubscribedWorkteamCommandInput extends DescribeSubscrib export interface DescribeSubscribedWorkteamCommandOutput extends DescribeSubscribedWorkteamResponse, __MetadataBearer {} /** - *Gets information about a work team provided by a vendor. It returns details about the - * subscription with a vendor in the Amazon Web Services Marketplace.
+ *Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DescribeTrainingJobCommand.ts b/clients/client-sagemaker/src/commands/DescribeTrainingJobCommand.ts index 96912e8a18bf..0a2462cc2a59 100644 --- a/clients/client-sagemaker/src/commands/DescribeTrainingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeTrainingJobCommand.ts @@ -28,13 +28,7 @@ export interface DescribeTrainingJobCommandInput extends DescribeTrainingJobRequ export interface DescribeTrainingJobCommandOutput extends DescribeTrainingJobResponse, __MetadataBearer {} /** - *Returns information about a training job.
- *Some of the attributes below only appear if the training job successfully starts.
- * If the training job fails, TrainingJobStatus is Failed and,
- * depending on the FailureReason, attributes like
- * TrainingStartTime, TrainingTimeInSeconds,
- * TrainingEndTime, and BillableTimeInSeconds may not be
- * present in the response.
Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus is Failed and, depending on the FailureReason, attributes like TrainingStartTime, TrainingTimeInSeconds, TrainingEndTime, and BillableTimeInSeconds may not be present in the response.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/DescribeWorkforceCommand.ts b/clients/client-sagemaker/src/commands/DescribeWorkforceCommand.ts index 64d143ff7774..9f8f104a8d81 100644 --- a/clients/client-sagemaker/src/commands/DescribeWorkforceCommand.ts +++ b/clients/client-sagemaker/src/commands/DescribeWorkforceCommand.ts @@ -28,12 +28,7 @@ export interface DescribeWorkforceCommandInput extends DescribeWorkforceRequest export interface DescribeWorkforceCommandOutput extends DescribeWorkforceResponse, __MetadataBearer {} /** - *Lists private workforce information, including workforce name, Amazon Resource Name - * (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address - * ranges are the IP addresses that workers can use to access tasks.
- *This operation applies only to private workforces.
- *Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
Gets information about a specific work team. You can see information such as the - * creation date, the last updated date, membership information, and the work team's Amazon - * Resource Name (ARN).
+ *Gets information about a specific work team. You can see information such as the creation date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DisableSagemakerServicecatalogPortfolioCommand.ts b/clients/client-sagemaker/src/commands/DisableSagemakerServicecatalogPortfolioCommand.ts index c216e613369b..99dd81a5b51c 100644 --- a/clients/client-sagemaker/src/commands/DisableSagemakerServicecatalogPortfolioCommand.ts +++ b/clients/client-sagemaker/src/commands/DisableSagemakerServicecatalogPortfolioCommand.ts @@ -37,8 +37,7 @@ export interface DisableSagemakerServicecatalogPortfolioCommandOutput __MetadataBearer {} /** - *Disables using Service Catalog in SageMaker. Service Catalog is used to create - * SageMaker projects.
+ *Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/DisassociateTrialComponentCommand.ts b/clients/client-sagemaker/src/commands/DisassociateTrialComponentCommand.ts index 27812532ac5e..0b314347030d 100644 --- a/clients/client-sagemaker/src/commands/DisassociateTrialComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/DisassociateTrialComponentCommand.ts @@ -28,12 +28,7 @@ export interface DisassociateTrialComponentCommandInput extends DisassociateTria export interface DisassociateTrialComponentCommandOutput extends DisassociateTrialComponentResponse, __MetadataBearer {} /** - *Disassociates a trial component from a trial. This doesn't effect other trials the - * component is associated with. Before you can delete a component, you must disassociate the - * component from all trials it is associated with. To associate a trial component with a trial, - * call the AssociateTrialComponent API.
- *To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter.
- * The list appears in the response under Results.TrialComponent.Parents.
Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.
Enables using Service Catalog in SageMaker. Service Catalog is used to create - * SageMaker projects.
+ *Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/GetModelPackageGroupPolicyCommand.ts b/clients/client-sagemaker/src/commands/GetModelPackageGroupPolicyCommand.ts index 9cf83e19c292..66edb9e1e20b 100644 --- a/clients/client-sagemaker/src/commands/GetModelPackageGroupPolicyCommand.ts +++ b/clients/client-sagemaker/src/commands/GetModelPackageGroupPolicyCommand.ts @@ -28,10 +28,7 @@ export interface GetModelPackageGroupPolicyCommandInput extends GetModelPackageG export interface GetModelPackageGroupPolicyCommandOutput extends GetModelPackageGroupPolicyOutput, __MetadataBearer {} /** - *Gets a resource policy that manages access for a model group. For information about - * resource policies, see Identity-based - * policies and resource-based policies in the Amazon Web Services - * Identity and Access Management User Guide..
+ *Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/GetSagemakerServicecatalogPortfolioStatusCommand.ts b/clients/client-sagemaker/src/commands/GetSagemakerServicecatalogPortfolioStatusCommand.ts index aed11b43dc37..996657543b23 100644 --- a/clients/client-sagemaker/src/commands/GetSagemakerServicecatalogPortfolioStatusCommand.ts +++ b/clients/client-sagemaker/src/commands/GetSagemakerServicecatalogPortfolioStatusCommand.ts @@ -37,8 +37,7 @@ export interface GetSagemakerServicecatalogPortfolioStatusCommandOutput __MetadataBearer {} /** - *Gets the status of Service Catalog in SageMaker. Service Catalog is used to create - * SageMaker projects.
+ *Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/GetScalingConfigurationRecommendationCommand.ts b/clients/client-sagemaker/src/commands/GetScalingConfigurationRecommendationCommand.ts index 4ff115480514..7f8067497eac 100644 --- a/clients/client-sagemaker/src/commands/GetScalingConfigurationRecommendationCommand.ts +++ b/clients/client-sagemaker/src/commands/GetScalingConfigurationRecommendationCommand.ts @@ -37,8 +37,7 @@ export interface GetScalingConfigurationRecommendationCommandOutput __MetadataBearer {} /** - *Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies - * that you can apply to your SageMaker endpoint.
+ *Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/GetSearchSuggestionsCommand.ts b/clients/client-sagemaker/src/commands/GetSearchSuggestionsCommand.ts index d2bf94570a75..67103d640328 100644 --- a/clients/client-sagemaker/src/commands/GetSearchSuggestionsCommand.ts +++ b/clients/client-sagemaker/src/commands/GetSearchSuggestionsCommand.ts @@ -28,10 +28,7 @@ export interface GetSearchSuggestionsCommandInput extends GetSearchSuggestionsRe export interface GetSearchSuggestionsCommandOutput extends GetSearchSuggestionsResponse, __MetadataBearer {} /** - *An auto-complete API for the search functionality in the SageMaker console. It returns
- * suggestions of possible matches for the property name to use in Search queries.
- * Provides suggestions for HyperParameters, Tags, and
- * Metrics.
An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/ListAppImageConfigsCommand.ts b/clients/client-sagemaker/src/commands/ListAppImageConfigsCommand.ts index bd0f62fb614e..72d0575556c8 100644 --- a/clients/client-sagemaker/src/commands/ListAppImageConfigsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListAppImageConfigsCommand.ts @@ -28,9 +28,7 @@ export interface ListAppImageConfigsCommandInput extends ListAppImageConfigsRequ export interface ListAppImageConfigsCommandOutput extends ListAppImageConfigsResponse, __MetadataBearer {} /** - *Lists the AppImageConfigs in your account and their properties. The list can be - * filtered by creation time or modified time, and whether the AppImageConfig name contains - * a specified string.
+ *Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListClusterNodesCommand.ts b/clients/client-sagemaker/src/commands/ListClusterNodesCommand.ts index 8cbcc178c942..22fa2caad2c7 100644 --- a/clients/client-sagemaker/src/commands/ListClusterNodesCommand.ts +++ b/clients/client-sagemaker/src/commands/ListClusterNodesCommand.ts @@ -28,8 +28,7 @@ export interface ListClusterNodesCommandInput extends ListClusterNodesRequest {} export interface ListClusterNodesCommandOutput extends ListClusterNodesResponse, __MetadataBearer {} /** - *Retrieves the list of instances (also called nodes interchangeably) - * in a SageMaker HyperPod cluster.
+ *Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListCompilationJobsCommand.ts b/clients/client-sagemaker/src/commands/ListCompilationJobsCommand.ts index 5b9d3928f7c3..7947a7dfe395 100644 --- a/clients/client-sagemaker/src/commands/ListCompilationJobsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListCompilationJobsCommand.ts @@ -28,9 +28,7 @@ export interface ListCompilationJobsCommandInput extends ListCompilationJobsRequ export interface ListCompilationJobsCommandOutput extends ListCompilationJobsResponse, __MetadataBearer {} /** - *Lists model compilation jobs that satisfy various filters.
- *To create a model compilation job, use CreateCompilationJob. To get information about a particular model - * compilation job you have created, use DescribeCompilationJob.
+ *Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListExperimentsCommand.ts b/clients/client-sagemaker/src/commands/ListExperimentsCommand.ts index 0859c7ea23a6..a8ccba7e1396 100644 --- a/clients/client-sagemaker/src/commands/ListExperimentsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListExperimentsCommand.ts @@ -28,9 +28,7 @@ export interface ListExperimentsCommandInput extends ListExperimentsRequest {} export interface ListExperimentsCommandOutput extends ListExperimentsResponse, __MetadataBearer {} /** - *Lists all the experiments in your account. The list can be filtered to show only - * experiments that were created in a specific time range. The list can be sorted by experiment - * name or creation time.
+ *Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListHyperParameterTuningJobsCommand.ts b/clients/client-sagemaker/src/commands/ListHyperParameterTuningJobsCommand.ts index 2734af049c77..1739bdf10310 100644 --- a/clients/client-sagemaker/src/commands/ListHyperParameterTuningJobsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListHyperParameterTuningJobsCommand.ts @@ -33,9 +33,7 @@ export interface ListHyperParameterTuningJobsCommandOutput __MetadataBearer {} /** - *Gets a list of HyperParameterTuningJobSummary objects that - * describe - * the hyperparameter tuning jobs launched in your account.
+ *Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListImageVersionsCommand.ts b/clients/client-sagemaker/src/commands/ListImageVersionsCommand.ts index 0a07c5a694c0..d628e26e5b88 100644 --- a/clients/client-sagemaker/src/commands/ListImageVersionsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListImageVersionsCommand.ts @@ -28,8 +28,7 @@ export interface ListImageVersionsCommandInput extends ListImageVersionsRequest export interface ListImageVersionsCommandOutput extends ListImageVersionsResponse, __MetadataBearer {} /** - *Lists the versions of a specified image and their properties. The list can be filtered - * by creation time or modified time.
+ *Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListImagesCommand.ts b/clients/client-sagemaker/src/commands/ListImagesCommand.ts index 798646cb3854..41e1b3142484 100644 --- a/clients/client-sagemaker/src/commands/ListImagesCommand.ts +++ b/clients/client-sagemaker/src/commands/ListImagesCommand.ts @@ -28,8 +28,7 @@ export interface ListImagesCommandInput extends ListImagesRequest {} export interface ListImagesCommandOutput extends ListImagesResponse, __MetadataBearer {} /** - *Lists the images in your account and their properties. The list can be filtered by - * creation time or modified time, and whether the image name contains a specified string.
+ *Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListInferenceRecommendationsJobStepsCommand.ts b/clients/client-sagemaker/src/commands/ListInferenceRecommendationsJobStepsCommand.ts index 8dfe2074ff90..fde3950a8717 100644 --- a/clients/client-sagemaker/src/commands/ListInferenceRecommendationsJobStepsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListInferenceRecommendationsJobStepsCommand.ts @@ -36,8 +36,7 @@ export interface ListInferenceRecommendationsJobStepsCommandOutput __MetadataBearer {} /** - *Returns a list of the subtasks for an Inference Recommender job.
- *The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
+ *Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListLineageGroupsCommand.ts b/clients/client-sagemaker/src/commands/ListLineageGroupsCommand.ts index 4c7b9541c968..ca9444e86a78 100644 --- a/clients/client-sagemaker/src/commands/ListLineageGroupsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListLineageGroupsCommand.ts @@ -28,9 +28,7 @@ export interface ListLineageGroupsCommandInput extends ListLineageGroupsRequest export interface ListLineageGroupsCommandOutput extends ListLineageGroupsResponse, __MetadataBearer {} /** - *A list of lineage groups shared with your Amazon Web Services account. - * For more information, see - * Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
+ *A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListModelMetadataCommand.ts b/clients/client-sagemaker/src/commands/ListModelMetadataCommand.ts index fbdb67b478a1..1a5971ff6e5f 100644 --- a/clients/client-sagemaker/src/commands/ListModelMetadataCommand.ts +++ b/clients/client-sagemaker/src/commands/ListModelMetadataCommand.ts @@ -28,8 +28,7 @@ export interface ListModelMetadataCommandInput extends ListModelMetadataRequest export interface ListModelMetadataCommandOutput extends ListModelMetadataResponse, __MetadataBearer {} /** - *Lists the domain, framework, task, and model name of standard - * machine learning models found in common model zoos.
+ *Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListNotebookInstancesCommand.ts b/clients/client-sagemaker/src/commands/ListNotebookInstancesCommand.ts index 4242d48407f6..f8890e7f1817 100644 --- a/clients/client-sagemaker/src/commands/ListNotebookInstancesCommand.ts +++ b/clients/client-sagemaker/src/commands/ListNotebookInstancesCommand.ts @@ -28,8 +28,7 @@ export interface ListNotebookInstancesCommandInput extends ListNotebookInstances export interface ListNotebookInstancesCommandOutput extends ListNotebookInstancesOutput, __MetadataBearer {} /** - *Returns a list of the SageMaker AI notebook instances in the requester's - * account in an Amazon Web Services Region.
+ *Returns a list of the SageMaker AI notebook instances in the requester's account in an Amazon Web Services Region.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListResourceCatalogsCommand.ts b/clients/client-sagemaker/src/commands/ListResourceCatalogsCommand.ts index 8b7434a480bf..e3ff0a31a58c 100644 --- a/clients/client-sagemaker/src/commands/ListResourceCatalogsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListResourceCatalogsCommand.ts @@ -28,8 +28,7 @@ export interface ListResourceCatalogsCommandInput extends ListResourceCatalogsRe export interface ListResourceCatalogsCommandOutput extends ListResourceCatalogsResponse, __MetadataBearer {} /** - * Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of
- * ResourceCatalogs viewable is 1000.
Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalogs viewable is 1000.
Lists devices allocated to the stage, containing detailed device information and - * deployment status.
+ *Lists devices allocated to the stage, containing detailed device information and deployment status.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListStudioLifecycleConfigsCommand.ts b/clients/client-sagemaker/src/commands/ListStudioLifecycleConfigsCommand.ts index b9974ca9653c..0c909629f1c9 100644 --- a/clients/client-sagemaker/src/commands/ListStudioLifecycleConfigsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListStudioLifecycleConfigsCommand.ts @@ -28,8 +28,7 @@ export interface ListStudioLifecycleConfigsCommandInput extends ListStudioLifecy export interface ListStudioLifecycleConfigsCommandOutput extends ListStudioLifecycleConfigsResponse, __MetadataBearer {} /** - *Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services - * Account.
+ *Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services Account.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListSubscribedWorkteamsCommand.ts b/clients/client-sagemaker/src/commands/ListSubscribedWorkteamsCommand.ts index 16455360bc96..416832a047db 100644 --- a/clients/client-sagemaker/src/commands/ListSubscribedWorkteamsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListSubscribedWorkteamsCommand.ts @@ -28,9 +28,7 @@ export interface ListSubscribedWorkteamsCommandInput extends ListSubscribedWorkt export interface ListSubscribedWorkteamsCommandOutput extends ListSubscribedWorkteamsResponse, __MetadataBearer {} /** - *Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The
- * list may be empty if no work team satisfies the filter specified in the
- * NameContains parameter.
Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Lists training jobs.
- *When StatusEquals and MaxResults are set at the same
- * time, the MaxResults number of training jobs are first retrieved
- * ignoring the StatusEquals parameter and then they are filtered by the
- * StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following
- * parameters:
- * \{ ... MaxResults: 100, StatusEquals: InProgress ... \}
- *
First, 100 trainings jobs with any status, including those other than
- * InProgress, are selected (sorted according to the creation time,
- * from the most current to the oldest). Next, those with a status of
- * InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI - * code.
- *
- * aws sagemaker list-training-jobs --max-results 100 --status-equals
- * InProgress
- *
Lists training jobs.
When StatusEquals and MaxResults are set at the same time, the MaxResults number of training jobs are first retrieved ignoring the StatusEquals parameter and then they are filtered by the StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following parameters:
\{ ... MaxResults: 100, StatusEquals: InProgress ... \}
First, 100 trainings jobs with any status, including those other than InProgress, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a - * hyperparameter tuning job launched.
+ *Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListTrialComponentsCommand.ts b/clients/client-sagemaker/src/commands/ListTrialComponentsCommand.ts index 6c2013740830..f4b16b5bf03c 100644 --- a/clients/client-sagemaker/src/commands/ListTrialComponentsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListTrialComponentsCommand.ts @@ -28,26 +28,7 @@ export interface ListTrialComponentsCommandInput extends ListTrialComponentsRequ export interface ListTrialComponentsCommandOutput extends ListTrialComponentsResponse, __MetadataBearer {} /** - *Lists the trial components in your account. You can sort the list by trial component name - * or creation time. You can filter the list to show only components that were created in a - * specific time range. You can also filter on one of the following:
- *
- * ExperimentName
- *
- * SourceArn
- *
- * TrialName
- *
Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
Lists the trials in your account. Specify an experiment name to limit the list to the - * trials that are part of that experiment. Specify a trial component name to limit the list to - * the trials that associated with that trial component. The list can be filtered to show only - * trials that were created in a specific time range. The list can be sorted by trial name or - * creation time.
+ *Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListWorkforcesCommand.ts b/clients/client-sagemaker/src/commands/ListWorkforcesCommand.ts index bf7efd738a52..d99dc9b0bc9c 100644 --- a/clients/client-sagemaker/src/commands/ListWorkforcesCommand.ts +++ b/clients/client-sagemaker/src/commands/ListWorkforcesCommand.ts @@ -28,8 +28,7 @@ export interface ListWorkforcesCommandInput extends ListWorkforcesRequest {} export interface ListWorkforcesCommandOutput extends ListWorkforcesResponse, __MetadataBearer {} /** - *Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only - * have one private workforce per Amazon Web Services Region.
+ *Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/ListWorkteamsCommand.ts b/clients/client-sagemaker/src/commands/ListWorkteamsCommand.ts index 09c8d145599a..34f1492e8ae7 100644 --- a/clients/client-sagemaker/src/commands/ListWorkteamsCommand.ts +++ b/clients/client-sagemaker/src/commands/ListWorkteamsCommand.ts @@ -28,9 +28,7 @@ export interface ListWorkteamsCommandInput extends ListWorkteamsRequest {} export interface ListWorkteamsCommandOutput extends ListWorkteamsResponse, __MetadataBearer {} /** - *Gets a list of private work teams that you have defined in a region. The list may be empty if
- * no work team satisfies the filter specified in the NameContains
- * parameter.
Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
Adds a resouce policy to control access to a model group. For information about - * resoure policies, see Identity-based - * policies and resource-based policies in the Amazon Web Services - * Identity and Access Management User Guide..
+ *Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -57,8 +54,7 @@ export interface PutModelPackageGroupPolicyCommandOutput extends PutModelPackage * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/QueryLineageCommand.ts b/clients/client-sagemaker/src/commands/QueryLineageCommand.ts index 8b4a48dd4a33..1761779939fc 100644 --- a/clients/client-sagemaker/src/commands/QueryLineageCommand.ts +++ b/clients/client-sagemaker/src/commands/QueryLineageCommand.ts @@ -28,9 +28,7 @@ export interface QueryLineageCommandInput extends QueryLineageRequest {} export interface QueryLineageCommandOutput extends QueryLineageResponse, __MetadataBearer {} /** - *Use this action to inspect your lineage and discover relationships between entities. - * For more information, see - * Querying Lineage Entities in the Amazon SageMaker Developer Guide.
+ *Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/RegisterDevicesCommand.ts b/clients/client-sagemaker/src/commands/RegisterDevicesCommand.ts index fd9e1089b166..122029f2a858 100644 --- a/clients/client-sagemaker/src/commands/RegisterDevicesCommand.ts +++ b/clients/client-sagemaker/src/commands/RegisterDevicesCommand.ts @@ -64,8 +64,7 @@ export interface RegisterDevicesCommandOutput extends __MetadataBearer {} * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/RetryPipelineExecutionCommand.ts b/clients/client-sagemaker/src/commands/RetryPipelineExecutionCommand.ts index d3a02d3ea143..ff7a71058594 100644 --- a/clients/client-sagemaker/src/commands/RetryPipelineExecutionCommand.ts +++ b/clients/client-sagemaker/src/commands/RetryPipelineExecutionCommand.ts @@ -57,12 +57,10 @@ export interface RetryPipelineExecutionCommandOutput extends RetryPipelineExecut * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/SearchCommand.ts b/clients/client-sagemaker/src/commands/SearchCommand.ts index 39472b044ed5..e1ac7df548ff 100644 --- a/clients/client-sagemaker/src/commands/SearchCommand.ts +++ b/clients/client-sagemaker/src/commands/SearchCommand.ts @@ -29,16 +29,7 @@ export interface SearchCommandInput extends SearchRequest {} export interface SearchCommandOutput extends SearchResponse, __MetadataBearer {} /** - *Finds SageMaker resources that match a search query. Matching resources are returned as a list
- * of SearchRecord objects in the response. You can sort the search results by any
- * resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and - * timestamp.
- *The Search API may provide access to otherwise restricted data. See Amazon SageMaker API - * Permissions: Actions, Permissions, and Resources Reference for more - * information.
- *Finds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
Searches for available training plan offerings based on specified criteria.
- *Users search for available plan offerings based on their requirements (e.g., - * instance type, count, start time, duration).
- *And then, they create a plan that best matches their needs using the ID of the - * plan offering they want to use.
- *For more information about how to reserve GPU capacity for your SageMaker training jobs or
- * SageMaker HyperPod clusters using Amazon SageMaker Training Plan , see
- * CreateTrainingPlan
- * .
Searches for available training plan offerings based on specified criteria.
Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration).
And then, they create a plan that best matches their needs using the ID of the plan offering they want to use.
For more information about how to reserve GPU capacity for your SageMaker training jobs or SageMaker HyperPod clusters using Amazon SageMaker Training Plan , see CreateTrainingPlan .
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/SendPipelineExecutionStepFailureCommand.ts b/clients/client-sagemaker/src/commands/SendPipelineExecutionStepFailureCommand.ts index 1d9b4d9faad6..d637558451aa 100644 --- a/clients/client-sagemaker/src/commands/SendPipelineExecutionStepFailureCommand.ts +++ b/clients/client-sagemaker/src/commands/SendPipelineExecutionStepFailureCommand.ts @@ -33,9 +33,7 @@ export interface SendPipelineExecutionStepFailureCommandOutput __MetadataBearer {} /** - *Notifies the pipeline that the execution of a callback step failed, along with a - * message describing why. When a callback step is run, the pipeline generates a callback - * token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
+ *Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -62,12 +60,10 @@ export interface SendPipelineExecutionStepFailureCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/SendPipelineExecutionStepSuccessCommand.ts b/clients/client-sagemaker/src/commands/SendPipelineExecutionStepSuccessCommand.ts index fee5a237d5ec..f8241213fb72 100644 --- a/clients/client-sagemaker/src/commands/SendPipelineExecutionStepSuccessCommand.ts +++ b/clients/client-sagemaker/src/commands/SendPipelineExecutionStepSuccessCommand.ts @@ -33,9 +33,7 @@ export interface SendPipelineExecutionStepSuccessCommandOutput __MetadataBearer {} /** - *Notifies the pipeline that the execution of a callback step succeeded and provides a - * list of the step's output parameters. When a callback step is run, the pipeline generates - * a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
+ *Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -67,12 +65,10 @@ export interface SendPipelineExecutionStepSuccessCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StartInferenceExperimentCommand.ts b/clients/client-sagemaker/src/commands/StartInferenceExperimentCommand.ts index d7d7e86b997f..e089b54472ac 100644 --- a/clients/client-sagemaker/src/commands/StartInferenceExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/StartInferenceExperimentCommand.ts @@ -53,8 +53,7 @@ export interface StartInferenceExperimentCommandOutput extends StartInferenceExp * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StartMlflowTrackingServerCommand.ts b/clients/client-sagemaker/src/commands/StartMlflowTrackingServerCommand.ts index 99a8be295955..b51f3e282c7d 100644 --- a/clients/client-sagemaker/src/commands/StartMlflowTrackingServerCommand.ts +++ b/clients/client-sagemaker/src/commands/StartMlflowTrackingServerCommand.ts @@ -53,8 +53,7 @@ export interface StartMlflowTrackingServerCommandOutput extends StartMlflowTrack * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StartMonitoringScheduleCommand.ts b/clients/client-sagemaker/src/commands/StartMonitoringScheduleCommand.ts index aedae48ab7ac..e7b16ad551b4 100644 --- a/clients/client-sagemaker/src/commands/StartMonitoringScheduleCommand.ts +++ b/clients/client-sagemaker/src/commands/StartMonitoringScheduleCommand.ts @@ -28,11 +28,7 @@ export interface StartMonitoringScheduleCommandInput extends StartMonitoringSche export interface StartMonitoringScheduleCommandOutput extends __MetadataBearer {} /** - *Starts a previously stopped monitoring schedule.
- *By default, when you successfully create a new schedule, the status of a monitoring
- * schedule is scheduled.
Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
Launches an ML compute instance with the latest version of the libraries and
- * attaches your ML storage volume. After configuring the notebook instance, SageMaker AI sets the notebook instance status to InService. A notebook
- * instance's status must be InService before you can connect to your Jupyter
- * notebook.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker AI sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/StartPipelineExecutionCommand.ts b/clients/client-sagemaker/src/commands/StartPipelineExecutionCommand.ts index 9724450a41bc..8c238e57daa1 100644 --- a/clients/client-sagemaker/src/commands/StartPipelineExecutionCommand.ts +++ b/clients/client-sagemaker/src/commands/StartPipelineExecutionCommand.ts @@ -73,12 +73,10 @@ export interface StartPipelineExecutionCommandOutput extends StartPipelineExecut * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StopCompilationJobCommand.ts b/clients/client-sagemaker/src/commands/StopCompilationJobCommand.ts index be2e19878d95..61affb9f52f8 100644 --- a/clients/client-sagemaker/src/commands/StopCompilationJobCommand.ts +++ b/clients/client-sagemaker/src/commands/StopCompilationJobCommand.ts @@ -28,13 +28,7 @@ export interface StopCompilationJobCommandInput extends StopCompilationJobReques export interface StopCompilationJobCommandOutput extends __MetadataBearer {} /** - *Stops a model compilation job.
- *To stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal. This gracefully shuts the - * job down. If the job hasn't stopped, it sends the SIGKILL signal.
- *When it receives a StopCompilationJob request, Amazon SageMaker AI changes the
- * CompilationJobStatus of the job to Stopping. After Amazon
- * SageMaker stops the job, it sets the CompilationJobStatus to
- * Stopped.
Stops a model compilation job.
To stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob request, Amazon SageMaker AI changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.
Stops a running hyperparameter tuning job and all running training jobs that the - * tuning job launched.
- *All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All
- * data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the
- * tuning job moves to the Stopped state, it releases all
- * reserved
- * resources for the tuning job.
Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StopLabelingJobCommand.ts b/clients/client-sagemaker/src/commands/StopLabelingJobCommand.ts index 8cbf04ee66ef..619a17692040 100644 --- a/clients/client-sagemaker/src/commands/StopLabelingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/StopLabelingJobCommand.ts @@ -28,8 +28,7 @@ export interface StopLabelingJobCommandInput extends StopLabelingJobRequest {} export interface StopLabelingJobCommandOutput extends __MetadataBearer {} /** - *Stops a running labeling job. A job that is stopped cannot be restarted. Any results - * obtained before the job is stopped are placed in the Amazon S3 output bucket.
+ *Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/StopMlflowTrackingServerCommand.ts b/clients/client-sagemaker/src/commands/StopMlflowTrackingServerCommand.ts index c0a65616a04c..f995d8af98cf 100644 --- a/clients/client-sagemaker/src/commands/StopMlflowTrackingServerCommand.ts +++ b/clients/client-sagemaker/src/commands/StopMlflowTrackingServerCommand.ts @@ -53,8 +53,7 @@ export interface StopMlflowTrackingServerCommandOutput extends StopMlflowTrackin * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StopNotebookInstanceCommand.ts b/clients/client-sagemaker/src/commands/StopNotebookInstanceCommand.ts index df248dc20e9b..5cdf3d1cfb10 100644 --- a/clients/client-sagemaker/src/commands/StopNotebookInstanceCommand.ts +++ b/clients/client-sagemaker/src/commands/StopNotebookInstanceCommand.ts @@ -28,14 +28,7 @@ export interface StopNotebookInstanceCommandInput extends StopNotebookInstanceIn export interface StopNotebookInstanceCommandOutput extends __MetadataBearer {} /** - *Terminates the ML compute instance. Before terminating the instance, SageMaker AI disconnects the ML storage volume from it. SageMaker AI preserves the
- * ML storage volume. SageMaker AI stops charging you for the ML compute instance when
- * you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been
- * terminated, call the StartNotebookInstance API.
- * StartNotebookInstance launches another ML compute instance, configures
- * it, and attaches the preserved ML storage volume so you can continue your work.
- *
Terminates the ML compute instance. Before terminating the instance, SageMaker AI disconnects the ML storage volume from it. SageMaker AI preserves the ML storage volume. SageMaker AI stops charging you for the ML compute instance when you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
- *- * Callback Step - *
- *A pipeline execution won't stop while a callback step is running.
- * When you call StopPipelineExecution
- * on a pipeline execution with a running callback step, SageMaker Pipelines sends an
- * additional Amazon SQS message to the specified SQS queue. The body of the SQS message
- * contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for
- * example, resource cleanup) upon receipt of the message followed by a call to
- * SendPipelineExecutionStepSuccess or
- * SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
- *- * Lambda Step - *
- *A pipeline execution can't be stopped while a lambda step is running because the Lambda
- * function invoked by the lambda step can't be stopped. If you attempt to stop the execution
- * while the Lambda function is running, the pipeline waits for the Lambda function to finish
- * or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function
- * finishes, the pipeline execution status is Stopped. If the timeout is hit
- * the pipeline execution status is Failed.
Stops a pipeline execution.
Callback Step
A pipeline execution won't stop while a callback step is running. When you call StopPipelineExecution on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a "Status" field which is set to "Stopping".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess or SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can't be stopped while a lambda step is running because the Lambda function invoked by the lambda step can't be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped. If the timeout is hit the pipeline execution status is Failed.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/StopTrainingJobCommand.ts b/clients/client-sagemaker/src/commands/StopTrainingJobCommand.ts index c3787fde09f4..0609b16ad2ac 100644 --- a/clients/client-sagemaker/src/commands/StopTrainingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/StopTrainingJobCommand.ts @@ -28,13 +28,7 @@ export interface StopTrainingJobCommandInput extends StopTrainingJobRequest {} export interface StopTrainingJobCommandOutput extends __MetadataBearer {} /** - *Stops a training job. To stop a job, SageMaker sends the algorithm the
- * SIGTERM signal, which delays job termination for 120 seconds.
- * Algorithms might use this 120-second window to save the model artifacts, so the results
- * of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of
- * the job to Stopping. After SageMaker stops the job, it sets the status to
- * Stopped.
Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of the job to Stopping. After SageMaker stops the job, it sets the status to Stopped.
Stops a batch transform job.
- *When Amazon SageMaker receives a StopTransformJob request, the status of the job
- * changes to Stopping. After Amazon SageMaker
- * stops
- * the job, the status is set to Stopped. When you stop a batch transform job before
- * it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a batch transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateArtifactCommand.ts b/clients/client-sagemaker/src/commands/UpdateArtifactCommand.ts index 8e5198d3f919..b21182d77bbd 100644 --- a/clients/client-sagemaker/src/commands/UpdateArtifactCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateArtifactCommand.ts @@ -60,8 +60,7 @@ export interface UpdateArtifactCommandOutput extends UpdateArtifactResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateClusterCommand.ts b/clients/client-sagemaker/src/commands/UpdateClusterCommand.ts index a55a08a3b3b4..f1d2b8dbab84 100644 --- a/clients/client-sagemaker/src/commands/UpdateClusterCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateClusterCommand.ts @@ -110,12 +110,10 @@ export interface UpdateClusterCommandOutput extends UpdateClusterResponse, __Met * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateClusterSchedulerConfigCommand.ts b/clients/client-sagemaker/src/commands/UpdateClusterSchedulerConfigCommand.ts index 66d103033e7c..0b7658a1695e 100644 --- a/clients/client-sagemaker/src/commands/UpdateClusterSchedulerConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateClusterSchedulerConfigCommand.ts @@ -70,12 +70,10 @@ export interface UpdateClusterSchedulerConfigCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts b/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts index 59ac1ef416c7..b994c103fee7 100644 --- a/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateClusterSoftwareCommand.ts @@ -28,13 +28,7 @@ export interface UpdateClusterSoftwareCommandInput extends UpdateClusterSoftware export interface UpdateClusterSoftwareCommandOutput extends UpdateClusterSoftwareResponse, __MetadataBearer {} /** - *Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to - * use this API, see Update the SageMaker HyperPod platform software of a cluster.
- *The UpgradeClusterSoftware API call may impact your SageMaker HyperPod cluster
- * uptime and availability. Plan accordingly to mitigate potential disruptions to your
- * workloads.
Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to use this API, see Update the SageMaker HyperPod platform software of a cluster.
The UpgradeClusterSoftware API call may impact your SageMaker HyperPod cluster uptime and availability. Plan accordingly to mitigate potential disruptions to your workloads.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateCodeRepositoryCommand.ts b/clients/client-sagemaker/src/commands/UpdateCodeRepositoryCommand.ts index b1daf0d612a5..2fc0c978b283 100644 --- a/clients/client-sagemaker/src/commands/UpdateCodeRepositoryCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateCodeRepositoryCommand.ts @@ -56,8 +56,7 @@ export interface UpdateCodeRepositoryCommandOutput extends UpdateCodeRepositoryO * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateComputeQuotaCommand.ts b/clients/client-sagemaker/src/commands/UpdateComputeQuotaCommand.ts index 80a7f9c12642..979fbbb19ac9 100644 --- a/clients/client-sagemaker/src/commands/UpdateComputeQuotaCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateComputeQuotaCommand.ts @@ -74,12 +74,10 @@ export interface UpdateComputeQuotaCommandOutput extends UpdateComputeQuotaRespo * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateContextCommand.ts b/clients/client-sagemaker/src/commands/UpdateContextCommand.ts index 385b4a7e9218..96f7a3bb00f3 100644 --- a/clients/client-sagemaker/src/commands/UpdateContextCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateContextCommand.ts @@ -60,8 +60,7 @@ export interface UpdateContextCommandOutput extends UpdateContextResponse, __Met * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateDomainCommand.ts b/clients/client-sagemaker/src/commands/UpdateDomainCommand.ts index 50378d7557ed..278608d47013 100644 --- a/clients/client-sagemaker/src/commands/UpdateDomainCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateDomainCommand.ts @@ -387,8 +387,7 @@ export interface UpdateDomainCommandOutput extends UpdateDomainResponse, __Metad *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts b/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts index 14ebf93f0a93..319ba36c7b17 100644 --- a/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateEndpointCommand.ts @@ -28,26 +28,7 @@ export interface UpdateEndpointCommandInput extends UpdateEndpointInput {} export interface UpdateEndpointCommandOutput extends UpdateEndpointOutput, __MetadataBearer {} /** - *Deploys the EndpointConfig specified in the request to a new fleet of
- * instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint
- * configuration and then deletes the old instances using the previous
- * EndpointConfig (there is no availability loss). For more information
- * about how to control the update and traffic shifting process, see Update
- * models in production.
When SageMaker receives the request, it sets the endpoint status to Updating.
- * After updating the endpoint, it sets the status to InService. To check the
- * status of an endpoint, use the DescribeEndpoint API.
- *
- *
You must not delete an EndpointConfig in use by an endpoint that is
- * live or while the UpdateEndpoint or CreateEndpoint
- * operations are being performed on the endpoint. To update an endpoint, you must
- * create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or
- * being created or updated you may lose visibility into the instance type the endpoint
- * is using. The endpoint must be deleted in order to stop incurring charges.
Deploys the EndpointConfig specified in the request to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint configuration and then deletes the old instances using the previous EndpointConfig (there is no availability loss). For more information about how to control the update and traffic shifting process, see Update models in production.
When SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateEndpointWeightsAndCapacitiesCommand.ts b/clients/client-sagemaker/src/commands/UpdateEndpointWeightsAndCapacitiesCommand.ts index 67d48d781801..6853edfa7212 100644 --- a/clients/client-sagemaker/src/commands/UpdateEndpointWeightsAndCapacitiesCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateEndpointWeightsAndCapacitiesCommand.ts @@ -33,11 +33,7 @@ export interface UpdateEndpointWeightsAndCapacitiesCommandOutput __MetadataBearer {} /** - *Updates variant weight of one or more variants associated with an existing
- * endpoint, or capacity of one variant associated with an existing endpoint. When it
- * receives the request, SageMaker sets the endpoint status to Updating. After
- * updating the endpoint, it sets the status to InService. To check the status
- * of an endpoint, use the DescribeEndpoint API.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateExperimentCommand.ts b/clients/client-sagemaker/src/commands/UpdateExperimentCommand.ts index 2a74255f2907..15f0dc76c316 100644 --- a/clients/client-sagemaker/src/commands/UpdateExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateExperimentCommand.ts @@ -28,8 +28,7 @@ export interface UpdateExperimentCommandInput extends UpdateExperimentRequest {} export interface UpdateExperimentCommandOutput extends UpdateExperimentResponse, __MetadataBearer {} /** - *Adds, updates, or removes the description of an experiment. Updates the display name of an - * experiment.
+ *Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -56,8 +55,7 @@ export interface UpdateExperimentCommandOutput extends UpdateExperimentResponse, * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts b/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts index 37f175eed6fe..abfe71291d15 100644 --- a/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateFeatureGroupCommand.ts @@ -28,21 +28,7 @@ export interface UpdateFeatureGroupCommandInput extends UpdateFeatureGroupReques export interface UpdateFeatureGroupCommandOutput extends UpdateFeatureGroupResponse, __MetadataBearer {} /** - *Updates the feature group by either adding features or updating the online store
- * configuration. Use one of the following request parameters at a time while using the
- * UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions
- * request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the
- * OnlineStoreConfig request parameter. If a TtlDuration is
- * specified, the default TtlDuration applies for all records added to the
- * feature group after the feature group is updated. If a record level
- * TtlDuration exists from using the PutRecord API, the record
- * level TtlDuration applies to that record instead of the default
- * TtlDuration. To remove the default TtlDuration from an
- * existing feature group, use the UpdateFeatureGroup API and set the
- * TtlDuration
- * Unit and Value to null.
Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig request parameter. If a TtlDuration is specified, the default TtlDuration applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration exists from using the PutRecord API, the record level TtlDuration applies to that record instead of the default TtlDuration. To remove the default TtlDuration from an existing feature group, use the UpdateFeatureGroup API and set the TtlDuration Unit and Value to null.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateHubContentCommand.ts b/clients/client-sagemaker/src/commands/UpdateHubContentCommand.ts index 564f8139383b..f8a855318924 100644 --- a/clients/client-sagemaker/src/commands/UpdateHubContentCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateHubContentCommand.ts @@ -28,42 +28,7 @@ export interface UpdateHubContentCommandInput extends UpdateHubContentRequest {} export interface UpdateHubContentCommandOutput extends UpdateHubContentResponse, __MetadataBearer {} /** - *Updates SageMaker hub content (either a Model or Notebook
- * resource).
You can update the metadata that describes the resource. In addition to the required request - * fields, specify at least one of the following fields to update:
- *
- * HubContentDescription
- *
- * HubContentDisplayName
- *
- * HubContentMarkdown
- *
- * HubContentSearchKeywords
- *
- * SupportStatus
- *
For more information about hubs, see Private curated hubs for foundation model access control in JumpStart.
- *If you want to update a ModelReference resource in your hub, use the
- * UpdateHubContentResource API instead.
Updates SageMaker hub content (either a Model or Notebook resource).
You can update the metadata that describes the resource. In addition to the required request fields, specify at least one of the following fields to update:
HubContentDescription
HubContentDisplayName
HubContentMarkdown
HubContentSearchKeywords
SupportStatus
For more information about hubs, see Private curated hubs for foundation model access control in JumpStart.
If you want to update a ModelReference resource in your hub, use the UpdateHubContentResource API instead.
Updates the contents of a SageMaker hub for a ModelReference resource.
- * A ModelReference allows you to access public SageMaker JumpStart
- * models from within your private hub.
When using this API, you can update the
- * MinVersion field for additional flexibility in the model version. You shouldn't update
- * any additional fields when using this API, because the metadata in your private hub
- * should match the public JumpStart model's metadata.
If you want to update a Model or Notebook
- * resource in your hub, use the UpdateHubContent API instead.
For more information about adding model references to your hub, see - * - * Add models to a private hub.
+ *Updates the contents of a SageMaker hub for a ModelReference resource. A ModelReference allows you to access public SageMaker JumpStart models from within your private hub.
When using this API, you can update the MinVersion field for additional flexibility in the model version. You shouldn't update any additional fields when using this API, because the metadata in your private hub should match the public JumpStart model's metadata.
If you want to update a Model or Notebook resource in your hub, use the UpdateHubContent API instead.
For more information about adding model references to your hub, see Add models to a private hub.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/UpdateImageCommand.ts b/clients/client-sagemaker/src/commands/UpdateImageCommand.ts index c630fb8280bc..1327df2bbfb9 100644 --- a/clients/client-sagemaker/src/commands/UpdateImageCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateImageCommand.ts @@ -28,8 +28,7 @@ export interface UpdateImageCommandInput extends UpdateImageRequest {} export interface UpdateImageCommandOutput extends UpdateImageResponse, __MetadataBearer {} /** - *Updates the properties of a SageMaker AI image. To change the image's tags, use the - * AddTags and DeleteTags APIs.
+ *Updates the properties of a SageMaker AI image. To change the image's tags, use the AddTags and DeleteTags APIs.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript diff --git a/clients/client-sagemaker/src/commands/UpdateInferenceComponentCommand.ts b/clients/client-sagemaker/src/commands/UpdateInferenceComponentCommand.ts index 28a54d8f491f..98cc6b751d07 100644 --- a/clients/client-sagemaker/src/commands/UpdateInferenceComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateInferenceComponentCommand.ts @@ -98,8 +98,7 @@ export interface UpdateInferenceComponentCommandOutput extends UpdateInferenceCo * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateInferenceComponentRuntimeConfigCommand.ts b/clients/client-sagemaker/src/commands/UpdateInferenceComponentRuntimeConfigCommand.ts index b07d1c8fb774..631af7c9c86a 100644 --- a/clients/client-sagemaker/src/commands/UpdateInferenceComponentRuntimeConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateInferenceComponentRuntimeConfigCommand.ts @@ -64,8 +64,7 @@ export interface UpdateInferenceComponentRuntimeConfigCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateInferenceExperimentCommand.ts b/clients/client-sagemaker/src/commands/UpdateInferenceExperimentCommand.ts index 25a431f73b0c..bcc7dd941da3 100644 --- a/clients/client-sagemaker/src/commands/UpdateInferenceExperimentCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateInferenceExperimentCommand.ts @@ -28,11 +28,7 @@ export interface UpdateInferenceExperimentCommandInput extends UpdateInferenceEx export interface UpdateInferenceExperimentCommandOutput extends UpdateInferenceExperimentResponse, __MetadataBearer {} /** - *
- * Updates an inference experiment that you created. The status of the inference experiment has to be either
- * Created, Running. For more information on the status of an inference experiment,
- * see DescribeInferenceExperiment.
- *
Updates an inference experiment that you created. The status of the inference experiment has to be either Created, Running. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateMlflowTrackingServerCommand.ts b/clients/client-sagemaker/src/commands/UpdateMlflowTrackingServerCommand.ts index d4c4a8cea528..c309f05a1aff 100644 --- a/clients/client-sagemaker/src/commands/UpdateMlflowTrackingServerCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateMlflowTrackingServerCommand.ts @@ -57,12 +57,10 @@ export interface UpdateMlflowTrackingServerCommandOutput extends UpdateMlflowTra * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateModelCardCommand.ts b/clients/client-sagemaker/src/commands/UpdateModelCardCommand.ts index 056a2041fea8..c76877e94f21 100644 --- a/clients/client-sagemaker/src/commands/UpdateModelCardCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateModelCardCommand.ts @@ -32,10 +32,7 @@ export interface UpdateModelCardCommandInput extends UpdateModelCardRequest {} export interface UpdateModelCardCommandOutput extends UpdateModelCardResponse, __MetadataBearer {} /** - *Update an Amazon SageMaker Model Card.
- *You cannot update both model card content and model card status in a single call.
- *Update an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateModelPackageCommand.ts b/clients/client-sagemaker/src/commands/UpdateModelPackageCommand.ts index a6381f62c347..5bbc3213d6dd 100644 --- a/clients/client-sagemaker/src/commands/UpdateModelPackageCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateModelPackageCommand.ts @@ -190,8 +190,7 @@ export interface UpdateModelPackageCommandOutput extends UpdateModelPackageOutpu * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateMonitoringAlertCommand.ts b/clients/client-sagemaker/src/commands/UpdateMonitoringAlertCommand.ts index 61c4ca5fe485..3ef0f0d9eeb8 100644 --- a/clients/client-sagemaker/src/commands/UpdateMonitoringAlertCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateMonitoringAlertCommand.ts @@ -57,8 +57,7 @@ export interface UpdateMonitoringAlertCommandOutput extends UpdateMonitoringAler * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateMonitoringScheduleCommand.ts b/clients/client-sagemaker/src/commands/UpdateMonitoringScheduleCommand.ts index 374b82752468..257cc7228665 100644 --- a/clients/client-sagemaker/src/commands/UpdateMonitoringScheduleCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateMonitoringScheduleCommand.ts @@ -162,8 +162,7 @@ export interface UpdateMonitoringScheduleCommandOutput extends UpdateMonitoringS * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateNotebookInstanceCommand.ts b/clients/client-sagemaker/src/commands/UpdateNotebookInstanceCommand.ts index ad6338d52d36..51cfe10562e1 100644 --- a/clients/client-sagemaker/src/commands/UpdateNotebookInstanceCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateNotebookInstanceCommand.ts @@ -28,9 +28,7 @@ export interface UpdateNotebookInstanceCommandInput extends UpdateNotebookInstan export interface UpdateNotebookInstanceCommandOutput extends UpdateNotebookInstanceOutput, __MetadataBearer {} /** - *Updates a notebook instance. NotebookInstance updates include upgrading or - * downgrading the ML compute instance used for your notebook instance to accommodate - * changes in your workload requirements.
+ *Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -72,8 +70,7 @@ export interface UpdateNotebookInstanceCommandOutput extends UpdateNotebookInsta * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateNotebookInstanceLifecycleConfigCommand.ts b/clients/client-sagemaker/src/commands/UpdateNotebookInstanceLifecycleConfigCommand.ts index 7b1f5f1f1f21..b2e364e6fc9b 100644 --- a/clients/client-sagemaker/src/commands/UpdateNotebookInstanceLifecycleConfigCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateNotebookInstanceLifecycleConfigCommand.ts @@ -69,8 +69,7 @@ export interface UpdateNotebookInstanceLifecycleConfigCommandOutput * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdatePartnerAppCommand.ts b/clients/client-sagemaker/src/commands/UpdatePartnerAppCommand.ts index 1f0cf972794f..3213b5e3f413 100644 --- a/clients/client-sagemaker/src/commands/UpdatePartnerAppCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdatePartnerAppCommand.ts @@ -28,7 +28,7 @@ export interface UpdatePartnerAppCommandInput extends UpdatePartnerAppRequest {} export interface UpdatePartnerAppCommandOutput extends UpdatePartnerAppResponse, __MetadataBearer {} /** - *Updates all of the SageMaker Partner AI Apps in an account.
+ *Updates all of the SageMaker Partner AI Apps in an account.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -73,8 +73,7 @@ export interface UpdatePartnerAppCommandOutput extends UpdatePartnerAppResponse, * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdatePipelineCommand.ts b/clients/client-sagemaker/src/commands/UpdatePipelineCommand.ts index d0230828d15e..fc6ab6d81189 100644 --- a/clients/client-sagemaker/src/commands/UpdatePipelineCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdatePipelineCommand.ts @@ -65,8 +65,7 @@ export interface UpdatePipelineCommandOutput extends UpdatePipelineResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdatePipelineExecutionCommand.ts b/clients/client-sagemaker/src/commands/UpdatePipelineExecutionCommand.ts index 211926500dd7..0ab5942ab07c 100644 --- a/clients/client-sagemaker/src/commands/UpdatePipelineExecutionCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdatePipelineExecutionCommand.ts @@ -58,8 +58,7 @@ export interface UpdatePipelineExecutionCommandOutput extends UpdatePipelineExec * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateProjectCommand.ts b/clients/client-sagemaker/src/commands/UpdateProjectCommand.ts index 934a1999d98c..f42f0fb150f2 100644 --- a/clients/client-sagemaker/src/commands/UpdateProjectCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateProjectCommand.ts @@ -28,14 +28,7 @@ export interface UpdateProjectCommandInput extends UpdateProjectInput {} export interface UpdateProjectCommandOutput extends UpdateProjectOutput, __MetadataBearer {} /** - *Updates a machine learning (ML) project that is created from a template that - * sets up an ML pipeline from training to deploying an approved model.
- *You must not update a project that is in use. If you update the
- * ServiceCatalogProvisioningUpdateDetails of a project that is active
- * or being created, or updated, you may lose resources already created by the
- * project.
Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails of a project that is active or being created, or updated, you may lose resources already created by the project.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateSpaceCommand.ts b/clients/client-sagemaker/src/commands/UpdateSpaceCommand.ts index 6f1d4382fed4..ce919d864dea 100644 --- a/clients/client-sagemaker/src/commands/UpdateSpaceCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateSpaceCommand.ts @@ -28,10 +28,7 @@ export interface UpdateSpaceCommandInput extends UpdateSpaceRequest {} export interface UpdateSpaceCommandOutput extends UpdateSpaceResponse, __MetadataBearer {} /** - *Updates the settings of a space.
- *You can't edit the app type of a space in the SpaceSettings.
Updates the settings of a space.
You can't edit the app type of a space in the SpaceSettings.
Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateTrainingJobCommand.ts b/clients/client-sagemaker/src/commands/UpdateTrainingJobCommand.ts index e356f53f02e7..866554111bb8 100644 --- a/clients/client-sagemaker/src/commands/UpdateTrainingJobCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateTrainingJobCommand.ts @@ -28,8 +28,7 @@ export interface UpdateTrainingJobCommandInput extends UpdateTrainingJobRequest export interface UpdateTrainingJobCommandOutput extends UpdateTrainingJobResponse, __MetadataBearer {} /** - *Update a model training job to request a new Debugger profiling configuration or to - * change warm pool retention length.
+ *Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -81,8 +80,7 @@ export interface UpdateTrainingJobCommandOutput extends UpdateTrainingJobRespons * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateTrialCommand.ts b/clients/client-sagemaker/src/commands/UpdateTrialCommand.ts index 0bd2c11ce2f5..830d18fe0bab 100644 --- a/clients/client-sagemaker/src/commands/UpdateTrialCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateTrialCommand.ts @@ -54,8 +54,7 @@ export interface UpdateTrialCommandOutput extends UpdateTrialResponse, __Metadat * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateTrialComponentCommand.ts b/clients/client-sagemaker/src/commands/UpdateTrialComponentCommand.ts index 6519d5beaa0b..b50a6ca09040 100644 --- a/clients/client-sagemaker/src/commands/UpdateTrialComponentCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateTrialComponentCommand.ts @@ -87,8 +87,7 @@ export interface UpdateTrialComponentCommandOutput extends UpdateTrialComponentR * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ConflictException} (client fault) - *There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateUserProfileCommand.ts b/clients/client-sagemaker/src/commands/UpdateUserProfileCommand.ts index a630a04ba5e3..0b0c853ab51a 100644 --- a/clients/client-sagemaker/src/commands/UpdateUserProfileCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateUserProfileCommand.ts @@ -274,8 +274,7 @@ export interface UpdateUserProfileCommandOutput extends UpdateUserProfileRespons *Resource being accessed is in use.
* * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link ResourceNotFound} (client fault) *Resource being access is not found.
diff --git a/clients/client-sagemaker/src/commands/UpdateWorkforceCommand.ts b/clients/client-sagemaker/src/commands/UpdateWorkforceCommand.ts index 6ce1f452a765..89d05e2547cb 100644 --- a/clients/client-sagemaker/src/commands/UpdateWorkforceCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateWorkforceCommand.ts @@ -32,32 +32,7 @@ export interface UpdateWorkforceCommandInput extends UpdateWorkforceRequest {} export interface UpdateWorkforceCommandOutput extends UpdateWorkforceResponse, __MetadataBearer {} /** - *Use this operation to update your workforce. You can use this operation to - * require that workers use specific IP addresses to work on tasks - * and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
- *The worker portal is now supported in VPC and public internet.
- * Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses.
- * You specify allowed IP addresses by creating a list of up to ten CIDRs.
- * By default, a workforce isn't restricted to specific IP addresses. If you specify a
- * range of IP addresses, workers who attempt to access tasks using any IP address outside
- * the specified range are denied and get a Not Found error message on
- * the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
- *Use OidcConfig to update the configuration of a workforce created using
- * your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams - * associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
- *After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you - * can view details about your update workforce using the DescribeWorkforce - * operation.
- *This operation only applies to private workforces.
- *Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as "10.0.0.0/16".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/commands/UpdateWorkteamCommand.ts b/clients/client-sagemaker/src/commands/UpdateWorkteamCommand.ts index c0a09b348b06..41442821ad51 100644 --- a/clients/client-sagemaker/src/commands/UpdateWorkteamCommand.ts +++ b/clients/client-sagemaker/src/commands/UpdateWorkteamCommand.ts @@ -115,8 +115,7 @@ export interface UpdateWorkteamCommandOutput extends UpdateWorkteamResponse, __M * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceLimitExceeded} (client fault) - *You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* * @throws {@link SageMakerServiceException} *Base exception class for all service exceptions from SageMaker service.
diff --git a/clients/client-sagemaker/src/index.ts b/clients/client-sagemaker/src/index.ts index ad23751d1894..78c1a2e56ce7 100644 --- a/clients/client-sagemaker/src/index.ts +++ b/clients/client-sagemaker/src/index.ts @@ -1,22 +1,7 @@ // smithy-typescript generated code /* eslint-disable */ /** - *Provides APIs for creating and managing SageMaker resources.
- *Other Resources:
- *- * SageMaker Developer - * Guide - *
- *Provides APIs for creating and managing SageMaker resources.
Other Resources:
* * @packageDocumentation */ diff --git a/clients/client-sagemaker/src/models/models_0.ts b/clients/client-sagemaker/src/models/models_0.ts index 9a003252e29e..471f0d92f2eb 100644 --- a/clients/client-sagemaker/src/models/models_0.ts +++ b/clients/client-sagemaker/src/models/models_0.ts @@ -46,9 +46,7 @@ export const ActionStatus = { export type ActionStatus = (typeof ActionStatus)[keyof typeof ActionStatus]; /** - *Lists the properties of an action. An action represents an action - * or activity. Some examples are a workflow step and a model deployment. Generally, an - * action involves at least one input artifact or output artifact.
+ *Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
* @public */ export interface ActionSummary { @@ -143,27 +141,7 @@ export interface AddAssociationRequest { DestinationArn: string | undefined; /** - *The type of association. The following are suggested uses for each type. Amazon SageMaker - * places no restrictions on their use.
- *ContributedTo - The source contributed to the destination or had a part in - * enabling the destination. For example, the training data contributed to the training - * job.
- *AssociatedWith - The source is connected to the destination. For example, an - * approval workflow is associated with a model deployment.
- *DerivedFrom - The destination is a modification of the source. For example, a digest - * output of a channel input for a processing job is derived from the original inputs.
- *Produced - The source generated the destination. For example, a training job - * produced a model artifact.
- *The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
You have exceeded an SageMaker resource limit. For example, you might have too many - * training jobs created.
+ *You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
* @public */ export class ResourceLimitExceeded extends __BaseException { @@ -261,29 +238,24 @@ export type AdditionalS3DataSourceDataType = (typeof AdditionalS3DataSourceDataType)[keyof typeof AdditionalS3DataSourceDataType]; /** - *A data source used for training or inference that is in addition to the input dataset - * or model data.
+ *A data source used for training or inference that is in addition to the input dataset or model data.
* @public */ export interface AdditionalS3DataSource { /** - *The data type of the additional data source that you specify for use in inference or - * training.
+ *The data type of the additional data source that you specify for use in inference or training.
* @public */ S3DataType: AdditionalS3DataSourceDataType | undefined; /** - *The uniform resource identifier (URI) used to identify an additional data source used - * in inference or training.
+ *The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
* @public */ S3Uri: string | undefined; /** - *The type of compression used for an additional data source used in inference or
- * training. Specify None if your additional data source is not
- * compressed.
The type of compression used for an additional data source used in inference or training. Specify None if your additional data source is not compressed.
The access configuration file to control access to the ML model. You can explicitly accept the model
- * end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
- *If you are an AutoML user, see the Optional Parameters section of - * Create an AutoML job to fine-tune text generation models using the - * API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML - * API.
- *The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
Specifies agreement to the model end-user license agreement (EULA). The
- * AcceptEula value must be explicitly defined as True in order
- * to accept the EULA that this model requires. You are responsible for reviewing and
- * complying with any applicable license terms and making sure they are acceptable for your
- * use case before downloading or using a model.
Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
Specifies the type of ML model data to deploy.
- *If you choose S3Prefix, S3Uri identifies a key name prefix.
- * SageMaker uses all objects that match the specified key name prefix as part of the ML model
- * data to deploy. A valid key name prefix identified by S3Uri always ends
- * with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is
- * the ML model data to deploy.
Specifies the type of ML model data to deploy.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri always ends with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is the ML model data to deploy.
Specifies how the ML model data is prepared.
- *If you choose Gzip and choose S3Object as the value of
- * S3DataType, S3Uri identifies an object that is a
- * gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during
- * model deployment.
If you choose None and chooose S3Object as the value of
- * S3DataType, S3Uri identifies an object that represents an
- * uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of
- * S3DataType, S3Uri identifies a key name prefix, under
- * which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files - * under /opt/ml/model directory for use by your inference code:
- *If you choose S3Object as the value of S3DataType,
- * then SageMaker will split the key of the S3 object referenced by S3Uri
- * by slash (/), and use the last part as the filename of the file holding the
- * content of the S3 object.
If you choose S3Prefix as the value of S3DataType,
- * then for each S3 object under the key name pefix referenced by
- * S3Uri, SageMaker will trim its key by the prefix, and use the
- * remainder as the path (relative to /opt/ml/model) of the file
- * holding the content of the S3 object. SageMaker will split the remainder by slash
- * (/), using intermediate parts as directory names and the last part as filename
- * of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
- *An empty or blank string
- *A string which contains null bytes
- *A string longer than 255 bytes
- *A single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if
- * your uncompressed ML model consists of two S3 objects
- * s3://mybucket/model/weights and
- * s3://mybucket/model/weights/part1 and you specify
- * s3://mybucket/model/ as the value of S3Uri and
- * S3Prefix as the value of S3DataType, then it will
- * result in name clash between /opt/ml/model/weights (a regular file)
- * and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using - * folders. When you create a folder in S3 console, S3 creates a 0-byte - * object with a key set to the folder name you provide. They key of the 0-byte - * object ends with a slash (/) which violates SageMaker restrictions on model artifact - * file names, leading to model deployment failure.
- *Specifies how the ML model data is prepared.
If you choose Gzip and choose S3Object as the value of S3DataType, S3Uri identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None and chooose S3Object as the value of S3DataType, S3Uri identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of S3DataType, S3Uri identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object as the value of S3DataType, then SageMaker will split the key of the S3 object referenced by S3Uri by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix as the value of S3DataType, then for each S3 object under the key name pefix referenced by S3Uri, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights and s3://mybucket/model/weights/part1 and you specify s3://mybucket/model/ as the value of S3Uri and S3Prefix as the value of S3DataType, then it will result in name clash between /opt/ml/model/weights (a regular file) and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Specifies the access configuration file for the ML model. You can explicitly accept the
- * model end-user license agreement (EULA) within the ModelAccessConfig. You are
- * responsible for reviewing and complying with any applicable license terms and making sure
- * they are acceptable for your use case before downloading or using a model.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The Amazon S3 URI of the manifest file. The manifest file is a CSV file that stores the - * artifact locations.
+ *The Amazon S3 URI of the manifest file. The manifest file is a CSV file that stores the artifact locations.
* @public */ ManifestS3Uri?: string | undefined; @@ -494,8 +374,7 @@ export interface S3ModelDataSource { } /** - *Specifies the location of ML model data to deploy. If specified, you must specify one - * and only one of the available data sources.
+ *Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
* @public */ export interface ModelDataSource { @@ -530,31 +409,19 @@ export interface ModelPackageContainerDefinition { ContainerHostname?: string | undefined; /** - *The Amazon Elastic Container Registry (Amazon ECR) path where inference code is stored.
- *If you are using your own custom algorithm instead of an algorithm provided by SageMaker,
- * the inference code must meet SageMaker requirements. SageMaker supports both
- * registry/repository[:tag] and registry/repository[@digest]
- * image path formats. For more information, see Using Your Own Algorithms with Amazon
- * SageMaker.
The Amazon Elastic Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
An MD5 hash of the training algorithm that identifies the Docker image used for - * training.
+ *An MD5 hash of the training algorithm that identifies the Docker image used for training.
* @public */ ImageDigest?: string | undefined; /** - *The Amazon S3 path where the model artifacts, which result from model training, are stored.
- * This path must point to a single gzip compressed tar archive
- * (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the - * model package.
- *The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The environment variables to set in the Docker container. Each key and value in the
- * Environment string to string map can have length of up to 1024. We
- * support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The name of a pre-trained machine learning benchmarked by
- * Amazon SageMaker Inference Recommender model that matches your model.
- * You can find a list of benchmarked models by calling ListModelMetadata.
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
The additional data source that is used during inference in the Docker container for - * your model package.
+ *The additional data source that is used during inference in the Docker container for your model package.
* @public */ AdditionalS3DataSource?: AdditionalS3DataSource | undefined; @@ -969,16 +831,12 @@ export const TransformInstanceType = { export type TransformInstanceType = (typeof TransformInstanceType)[keyof typeof TransformInstanceType]; /** - *A structure of additional Inference Specification. Additional Inference Specification - * specifies details about inference jobs that can be run with models based on - * this model package
+ *A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
* @public */ export interface AdditionalInferenceSpecificationDefinition { /** - *A unique name to identify the additional inference specification. The name must - * be unique within the list of your additional inference specifications for a - * particular model package.
+ *A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
* @public */ Name: string | undefined; @@ -996,8 +854,7 @@ export interface AdditionalInferenceSpecificationDefinition { Containers: ModelPackageContainerDefinition[] | undefined; /** - *A list of the instance types on which a transformation job can be run - * or on which an endpoint can be deployed.
+ *A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
* @public */ SupportedTransformInstanceTypes?: TransformInstanceType[] | undefined; @@ -1040,16 +897,7 @@ export interface AdditionalModelDataSource { } /** - *A tag object that consists of a key and an optional value, used to manage metadata - * for SageMaker Amazon Web Services resources.
- *You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, - * batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and - * endpoints. For more information on adding tags to SageMaker resources, see AddTags.
- *For more information on adding metadata to your Amazon Web Services resources with - * tagging, see Tagging Amazon Web Services resources. For advice on best practices for - * managing Amazon Web Services resources with tagging, see Tagging - * Best Practices: Implement an Effective Amazon Web Services Resource Tagging - * Strategy.
+ *A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
* @public */ export interface Tag { @@ -1077,9 +925,7 @@ export interface AddTagsInput { ResourceArn: string | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags: Tag[] | undefined; @@ -1171,13 +1017,7 @@ export const AlgorithmSortBy = { export type AlgorithmSortBy = (typeof AlgorithmSortBy)[keyof typeof AlgorithmSortBy]; /** - *Specifies a metric that the training algorithm writes to stderr or
- * stdout. You can view these logs to understand how your training job
- * performs and check for any errors encountered during training. SageMaker hyperparameter
- * tuning captures all defined metrics. Specify one of the defined metrics to use as an
- * objective metric using the TuningObjective parameter in the
- * HyperParameterTrainingJobDefinition API to evaluate job performance
- * during hyperparameter tuning.
Specifies a metric that the training algorithm writes to stderr or stdout. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition API to evaluate job performance during hyperparameter tuning.
A regular expression that searches the output of a training job and gets the value of - * the metric. For more information about using regular expressions to define metrics, see - * Defining metrics and environment variables.
+ *A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
* @public */ Regex: string | undefined; @@ -1217,30 +1055,25 @@ export type TrainingRepositoryAccessMode = */ export interface TrainingRepositoryAuthConfig { /** - *The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access - * credentials to your private Docker registry.
+ *The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
* @public */ TrainingRepositoryCredentialsProviderArn: string | undefined; } /** - *The configuration to use an image from a private Docker registry for a training - * job.
+ *The configuration to use an image from a private Docker registry for a training job.
* @public */ export interface TrainingImageConfig { /** - *The method that your training job will use to gain access to the images in your
- * private Docker registry. For access to an image in a private Docker registry, set to
- * Vpc.
The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc.
An object containing authentication information for a private Docker registry - * containing your training images.
+ *An object containing authentication information for a private Docker registry containing your training images.
* @public */ TrainingRepositoryAuthConfig?: TrainingRepositoryAuthConfig | undefined; @@ -1262,154 +1095,54 @@ export const TrainingInputMode = { export type TrainingInputMode = (typeof TrainingInputMode)[keyof typeof TrainingInputMode]; /** - *Specifies the training algorithm to use in a CreateTrainingJob request.
- *SageMaker uses its own SageMaker account credentials to pull and access built-in algorithms - * so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard, - * unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use - * custom algorithms if you require specific access controls.
- *For more information about algorithms provided by SageMaker, see Algorithms. For - * information about using your own algorithms, see Using Your Own Algorithms with - * Amazon SageMaker.
+ *Specifies the training algorithm to use in a CreateTrainingJob request.
SageMaker uses its own SageMaker account credentials to pull and access built-in algorithms so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard, unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use custom algorithms if you require specific access controls.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
* @public */ export interface AlgorithmSpecification { /** - *The registry path of the Docker image
- * that contains the training algorithm.
- * For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry
- * Paths and Example Code in the Amazon SageMaker developer guide.
- * SageMaker supports both registry/repository[:tag] and
- * registry/repository[@digest] image path formats. For more information
- * about using your custom training container, see Using Your Own Algorithms with
- * Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName
- * parameter or the image URI of the algorithm container to the
- * TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter
- * description.
The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
The name of the algorithm resource to use for the training job. This must be an - * algorithm resource that you created or subscribe to on Amazon Web Services - * Marketplace.
- *You must specify either the algorithm name to the AlgorithmName
- * parameter or the image URI of the algorithm container to the
- * TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the
- * TrainingImage parameter. If you specify a value for the
- * AlgorithmName parameter, you can't specify a value for
- * TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you
- * don't specify any value for both parameters, the training job might raise a
- * null error.
The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the TrainingImage parameter. If you specify a value for the AlgorithmName parameter, you can't specify a value for TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a null error.
The training input mode that the algorithm supports. For more information about input - * modes, see Algorithms.
- *- * Pipe mode - *
- *If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from
- * Amazon S3 to the container.
- * File mode - *
- *If an algorithm supports File mode, SageMaker downloads the training data from
- * S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume
- * for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the - * data downloaded from S3. In addition to the training data, the ML storage volume also - * stores the output model. The algorithm container uses the ML storage volume to also - * store intermediate information, if any.
- *For distributed algorithms, training data is distributed uniformly. Your training - * duration is predictable if the input data objects sizes are approximately the same. SageMaker - * does not split the files any further for model training. If the object sizes are skewed, - * training won't be optimal as the data distribution is also skewed when one host in a - * training cluster is overloaded, thus becoming a bottleneck in training.
- *- * FastFile mode - *
- *If an algorithm supports FastFile mode, SageMaker streams data directly from
- * S3 to the container with no code changes, and provides file system access to the data.
- * Users can author their training script to interact with these files as if they were
- * stored on disk.
- * FastFile mode works best when the data is read sequentially. Augmented
- * manifest files aren't supported. The startup time is lower when there are fewer files in
- * the S3 bucket provided.
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
A list of metric definition objects. Each object specifies the metric name and regular - * expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
+ *A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
* @public */ MetricDefinitions?: MetricDefinition[] | undefined; /** - *To generate and save time-series metrics during training, set to true.
- * The default is false and time-series metrics aren't generated except in the
- * following cases:
You use one of the SageMaker built-in algorithms
- *You use one of the following Prebuilt SageMaker Docker Images:
- *Tensorflow (version >= 1.15)
- *MXNet (version >= 1.6)
- *PyTorch (version >= 1.3)
- *You specify at least one MetricDefinition - *
- *To generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren't generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
The entrypoint script - * for a Docker container used to run a training job. This script takes - * precedence over the default train processing instructions. See How Amazon SageMaker - * Runs Your Training Image for more information.
+ *The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
* @public */ ContainerEntrypoint?: string[] | undefined; /** - *The arguments for a container used to run a training job. See How Amazon SageMaker - * Runs Your Training Image for additional information.
+ *The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
* @public */ ContainerArguments?: string[] | undefined; /** - *The configuration to use an image from a private Docker registry for a training - * job.
+ *The configuration to use an image from a private Docker registry for a training job.
* @public */ TrainingImageConfig?: TrainingImageConfig | undefined; @@ -1566,9 +1299,7 @@ export interface FileSystemDataSource { FileSystemId: string | undefined; /** - *The access mode of the mount of the directory associated with the channel. A directory
- * can be mounted either in ro (read-only) or rw (read-write)
- * mode.
The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.
The configuration for a private hub model reference that points to a public SageMaker JumpStart model.
- *For more information about private hubs, see Private curated hubs for foundation model access control in JumpStart.
+ *The configuration for a private hub model reference that points to a public SageMaker JumpStart model.
For more information about private hubs, see Private curated hubs for foundation model access control in JumpStart.
* @public */ export interface HubAccessConfig { /** - *The ARN of your private model hub content. This should be a ModelReference
- * resource type that points to a SageMaker JumpStart public hub model.
The ARN of your private model hub content. This should be a ModelReference resource type that points to a SageMaker JumpStart public hub model.
Describes the S3 data source.
- *Your input bucket must be in the same Amazon Web Services region as your training - * job.
+ *Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
* @public */ export interface S3DataSource { /** - *If you choose S3Prefix, S3Uri identifies a key name prefix.
- * SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that
- * is a manifest file containing a list of object keys that you want SageMaker to use for model
- * training.
If you choose AugmentedManifestFile, S3Uri identifies an
- * object that is an augmented manifest file in JSON lines format. This file contains the
- * data you want to use for model training. AugmentedManifestFile can only be
- * used if the Channel's input mode is Pipe.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile can only be used if the Channel's input mode is Pipe.
Depending on the value specified for the S3DataType, identifies either
- * a key name prefix or a manifest. For example:
A key name prefix might look like this:
- * s3://bucketname/exampleprefix/
- *
A manifest might look like this:
- * s3://bucketname/example.manifest
- *
A manifest is an S3 object which is a JSON file consisting of an array of
- * elements. The first element is a prefix which is followed by one or more
- * suffixes. SageMaker appends the suffix elements to the prefix to get a full set of
- * S3Uri. Note that the prefix must be a valid non-empty
- * S3Uri that precludes users from specifying a manifest whose
- * individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
- *
- * [ \{"prefix": "s3://customer_bucket/some/prefix/"\},
- *
- * "relative/path/to/custdata-1",
- *
- * "relative/path/custdata-2",
- *
- * ...
- *
- * "relative/path/custdata-N"
- *
- * ]
- *
This JSON is equivalent to the following S3Uri
- * list:
- * s3://customer_bucket/some/prefix/relative/path/to/custdata-1
- *
- * s3://customer_bucket/some/prefix/relative/path/custdata-2
- *
- * ...
- *
- * s3://customer_bucket/some/prefix/relative/path/custdata-N
- *
The complete set of S3Uri in this manifest is the input data
- * for the channel for this data source. The object that each S3Uri
- * points to must be readable by the IAM role that SageMaker uses to perform tasks on
- * your behalf.
Your input bucket must be located in same Amazon Web Services region as your - * training job.
+ *Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri. Note that the prefix must be a valid non-empty S3Uri that precludes users from specifying a manifest whose individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ \{"prefix": "s3://customer_bucket/some/prefix/"\},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
This JSON is equivalent to the following S3Uri list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri in this manifest is the input data for the channel for this data source. The object that each S3Uri points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
* @public */ S3Uri: string | undefined; /** - *If you want SageMaker to replicate the entire dataset on each ML compute instance that
- * is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is
- * launched for model training, specify ShardedByS3Key. If there are
- * n ML compute instances launched for a training job, each
- * instance gets approximately 1/n of the number of S3 objects. In
- * this case, model training on each machine uses only the subset of training data.
Don't choose more ML compute instances for training than available S3 objects. If - * you do, some nodes won't get any data and you will pay for nodes that aren't getting any - * training data. This applies in both File and Pipe modes. Keep this in mind when - * developing algorithms.
- *In distributed training, where you use multiple ML compute EC2 instances, you might
- * choose ShardedByS3Key. If the algorithm requires copying training data to
- * the ML storage volume (when TrainingInputMode is set to File),
- * this copies 1/n of the number of objects.
If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode is set to File), this copies 1/n of the number of objects.
A list of one or more attribute names to use that are found in a specified augmented - * manifest file.
+ *A list of one or more attribute names to use that are found in a specified augmented manifest file.
* @public */ AttributeNames?: string[] | undefined; @@ -1748,19 +1394,7 @@ export interface S3DataSource { InstanceGroupNames?: string[] | undefined; /** - *The access configuration file to control access to the ML model. You can explicitly accept the model
- * end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
- *If you are an AutoML user, see the Optional Parameters section of - * Create an AutoML job to fine-tune text generation models using the - * API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML - * API.
- *The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
A configuration for a shuffle option for input data in a channel. If you use
- * S3Prefix for S3DataType, the results of the S3 key prefix
- * matches are shuffled. If you use ManifestFile, the order of the S3 object
- * references in the ManifestFile is shuffled. If you use
- * AugmentedManifestFile, the order of the JSON lines in the
- * AugmentedManifestFile is shuffled. The shuffling order is determined
- * using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at
- * the start of every epoch. With large datasets, this ensures that the order of the
- * training data is different for each epoch, and it helps reduce bias and possible
- * overfitting. In a multi-node training job when ShuffleConfig is combined
- * with S3DataDistributionType of ShardedByS3Key, the data is
- * shuffled across nodes so that the content sent to a particular node on the first epoch
- * might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
If training data is compressed, the compression type. The default value is
- * None. CompressionType is used only in Pipe input mode. In
- * File mode, leave this field unset or set it to None.
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
Specify RecordIO as the value when input data is in raw format but the training - * algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 - * object in a RecordIO record. If the input data is already in RecordIO format, you don't - * need to set this attribute. For more information, see Create - * a Dataset Using RecordIO.
- *In File mode, leave this field unset or set it to None.
+ *Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
* @public */ RecordWrapperType?: RecordWrapper | undefined; /** - *(Optional) The input mode to use for the data channel in a training job. If you don't
- * set a value for InputMode, SageMaker uses the value set for
- * TrainingInputMode. Use this parameter to override the
- * TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a
- * different input mode from the training job's general setting. To download the data from
- * Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a
- * Docker volume, use File input mode. To stream data directly from Amazon S3 to
- * the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
A configuration for a shuffle option for input data in a channel. If you use
- * S3Prefix for S3DataType, this shuffles the results of the
- * S3 key prefix matches. If you use ManifestFile, the order of the S3 object
- * references in the ManifestFile is shuffled. If you use
- * AugmentedManifestFile, the order of the JSON lines in the
- * AugmentedManifestFile is shuffled. The shuffling order is determined
- * using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large
- * datasets this ensures that the order of the training data is different for each epoch,
- * it helps reduce bias and possible overfitting. In a multi-node training job when
- * ShuffleConfig is combined with S3DataDistributionType of
- * ShardedByS3Key, the data is shuffled across nodes so that the content
- * sent to a particular node on the first epoch might be sent to a different node on the
- * second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
Provides information about how to store model training results (model - * artifacts).
+ *Provides information about how to store model training results (model artifacts).
* @public */ export interface OutputDataConfig { /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker
- * uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The
- * KmsKeyId can be any of the following formats:
// KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// KMS Key Alias
- *
- * "alias/ExampleAlias"
- *
// Amazon Resource Name (ARN) of a KMS Key Alias
- *
- * "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
- *
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must
- * include permissions to call kms:Encrypt. If you don't provide a KMS key ID,
- * SageMaker uses the default KMS key for Amazon S3 for your role's account.
- *
- * For more information, see KMS-Managed Encryption
- * Keys in the Amazon Simple Storage Service Developer Guide. If the output
- * data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3
- * managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your
- * CreateTrainingJob, CreateTransformJob, or
- * CreateHyperParameterTuningJob requests. For more information, see
- * Using
- * Key Policies in Amazon Web Services KMS in the Amazon Web Services
- * Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. If the output data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
Identifies the S3 path where you want SageMaker to store the model artifacts. For
- * example, s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
The model output compression type. Select None to output an uncompressed
- * model, recommended for large model outputs. Defaults to gzip.
The model output compression type. Select None to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Defines an instance group for heterogeneous cluster training. When requesting a - * training job using the CreateTrainingJob API, you can configure multiple instance groups .
+ *Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
* @public */ export interface InstanceGroup { @@ -2135,105 +1681,36 @@ export interface InstanceGroup { } /** - *Describes the resources, including machine learning (ML) compute instances and ML - * storage volumes, to use for model training.
+ *Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
* @public */ export interface ResourceConfig { /** - *The ML compute instance type.
- *SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting - * December 9th, 2022.
- *
- * Amazon EC2 P4de instances
- * (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance
- * HBM2e GPU memory, which accelerate the speed of training ML models that need to be
- * trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker
- * supports ML training jobs on P4de instances (ml.p4de.24xlarge) to
- * reduce model training time. The ml.p4de.24xlarge instances are
- * available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
- *US West (Oregon) (us-west-2)
- *To request quota limit increase and start using P4de instances, contact the SageMaker - * Training service team through your account team.
- *The ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge) to reduce model training time. The ml.p4de.24xlarge instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
The number of ML compute instances to use. For distributed training, provide a - * value greater than 1.
+ *The number of ML compute instances to use. For distributed training, provide a value greater than 1.
* @public */ InstanceCount?: number | undefined; /** - *The size of the ML storage volume that you want to provision.
- *ML storage volumes store model artifacts and incremental states. Training
- * algorithms might also use the ML storage volume for scratch space. If you want to store
- * the training data in the ML storage volume, choose File as the
- * TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD
- * volumes, SageMaker doesn't provision Amazon EBS General Purpose SSD (gp2) storage.
- * Available storage is fixed to the NVMe-type instance's storage capacity. SageMaker configures
- * storage paths for training datasets, checkpoints, model artifacts, and outputs to use
- * the entire capacity of the instance storage. For example, ML instance families with the
- * NVMe-type instance storage include ml.p4d, ml.g4dn, and
- * ml.g5.
When using an ML instance with the EBS-only storage option and without instance
- * storage, you must define the size of EBS volume through VolumeSizeInGB in
- * the ResourceConfig API. For example, ML instance families that use EBS
- * volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
- *To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker - * Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and - * Outputs.
+ *The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn't provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance's storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d, ml.g4dn, and ml.g5.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB in the ResourceConfig API. For example, ML instance families that use EBS volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
* @public */ VolumeSizeInGB: number | undefined; /** - *The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume - * attached to the ML compute instance(s) that run the training job.
- *Certain Nitro-based instances include local storage, dependent on the instance
- * type. Local storage volumes are encrypted using a hardware module on the instance.
- * You can't request a VolumeKmsKeyId when using an instance type with
- * local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
- *For more information about local instance storage encryption, see SSD - * Instance Store Volumes.
- *The VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
The duration of time in seconds to retain configured resources in a warm pool for - * subsequent training jobs.
+ *The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
* @public */ KeepAlivePeriodInSeconds?: number | undefined; @@ -2252,80 +1729,24 @@ export interface ResourceConfig { } /** - *Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker - * ends the job. Use this API to cap costs.
- *To stop a training job, SageMaker sends the algorithm the SIGTERM signal,
- * which delays job termination for 120 seconds. Algorithms can use this 120-second window
- * to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results
- * of a model training job when possible. This attempt to save artifacts is only a best
- * effort case as model might not be in a state from which it can be saved. For example, if
- * training has just started, the model might not be ready to save. When saved, this
- * intermediate data is a valid model artifact. You can use it to create a model with
- * CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model - * artifacts. When training NTMs, make sure that the maximum runtime is sufficient for - * the training job to complete.
- *Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
The maximum length of time, in seconds, that a training or compilation job can run - * before it is stopped.
- *For compilation jobs, if the job does not complete during this time, a
- * TimeOut error is generated. We recommend starting with 900 seconds and
- * increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job.
- * When RetryStrategy is specified in the job request,
- * MaxRuntimeInSeconds specifies the maximum time for all of the attempts
- * in total, not each individual attempt. The default value is 1 day. The maximum value is
- * 28 days.
The maximum time that a TrainingJob can run in total, including any time
- * spent publishing metrics or archiving and uploading models after it has been stopped, is
- * 30 days.
The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum length of time, in seconds, that a managed Spot training job has to
- * complete. It is the amount of time spent waiting for Spot capacity plus the amount of
- * time the job can run. It must be equal to or greater than
- * MaxRuntimeInSeconds. If the job does not complete during this time,
- * SageMaker ends the job.
When RetryStrategy is specified in the job request,
- * MaxWaitTimeInSeconds specifies the maximum time for all of the attempts
- * in total, not each individual attempt.
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.
The maximum length of time, in seconds, that a training or compilation job can be - * pending before it is stopped.
- *When working with training jobs that use capacity from training
- * plans, not all Pending job states count against the
- * MaxPendingTimeInSeconds limit. The following scenarios do not
- * increment the MaxPendingTimeInSeconds counter:
The plan is in a Scheduled state: Jobs queued (in
- * Pending status) before a plan's start date (waiting for
- * scheduled start time)
Between capacity reservations: Jobs temporarily back to
- * Pending status between two capacity reservation
- * periods
- * MaxPendingTimeInSeconds only increments when jobs are actively
- * waiting for capacity in an Active plan.
The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
When working with training jobs that use capacity from training plans, not all Pending job states count against the MaxPendingTimeInSeconds limit. The following scenarios do not increment the MaxPendingTimeInSeconds counter:
The plan is in a Scheduled state: Jobs queued (in Pending status) before a plan's start date (waiting for scheduled start time)
Between capacity reservations: Jobs temporarily back to Pending status between two capacity reservation periods
MaxPendingTimeInSeconds only increments when jobs are actively waiting for capacity in an Active plan.
The training input mode that the algorithm supports. For more information about input - * modes, see Algorithms.
- *- * Pipe mode - *
- *If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from
- * Amazon S3 to the container.
- * File mode - *
- *If an algorithm supports File mode, SageMaker downloads the training data from
- * S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume
- * for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the - * data downloaded from S3. In addition to the training data, the ML storage volume also - * stores the output model. The algorithm container uses the ML storage volume to also - * store intermediate information, if any.
- *For distributed algorithms, training data is distributed uniformly. Your training - * duration is predictable if the input data objects sizes are approximately the same. SageMaker - * does not split the files any further for model training. If the object sizes are skewed, - * training won't be optimal as the data distribution is also skewed when one host in a - * training cluster is overloaded, thus becoming a bottleneck in training.
- *- * FastFile mode - *
- *If an algorithm supports FastFile mode, SageMaker streams data directly from
- * S3 to the container with no code changes, and provides file system access to the data.
- * Users can author their training script to interact with these files as if they were
- * stored on disk.
- * FastFile mode works best when the data is read sequentially. Augmented
- * manifest files aren't supported. The startup time is lower when there are fewer files in
- * the S3 bucket provided.
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
An array of Channel objects, each of which specifies an input
- * source.
An array of Channel objects, each of which specifies an input source.
the path to the S3 bucket where you want to store model artifacts. SageMaker creates - * subfolders for the artifacts.
+ *the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
* @public */ OutputDataConfig: OutputDataConfig | undefined; /** - *The resources, including the ML compute instances and ML storage volumes, to use for - * model training.
+ *The resources, including the ML compute instances and ML storage volumes, to use for model training.
* @public */ ResourceConfig: ResourceConfig | undefined; /** - *Specifies a limit to how long a model training job can run. It also specifies how long - * a managed Spot training job has to complete. When the job reaches the time limit, SageMaker - * ends the training job. Use this API to cap model training costs.
- *To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job - * termination for 120 seconds. Algorithms can use this 120-second window to save the model - * artifacts.
+ *Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
* @public */ StoppingCondition: StoppingCondition | undefined; @@ -2433,70 +1814,13 @@ export type BatchStrategy = (typeof BatchStrategy)[keyof typeof BatchStrategy]; */ export interface TransformS3DataSource { /** - *If you choose S3Prefix, S3Uri identifies a key name prefix.
- * Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that
- * is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch
- * transform.
The following values are compatible: ManifestFile,
- * S3Prefix
- *
The following value is not compatible: AugmentedManifestFile
- *
If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile, S3Prefix
The following value is not compatible: AugmentedManifestFile
Depending on the value specified for the S3DataType, identifies either a
- * key name prefix or a manifest. For example:
A key name prefix might look like this:
- * s3://bucketname/exampleprefix/.
A manifest might look like this:
- * s3://bucketname/example.manifest
- *
The manifest is an S3 object which is a JSON file with the following format:
- *
- * [ \{"prefix": "s3://customer_bucket/some/prefix/"\},
- *
- * "relative/path/to/custdata-1",
- *
- * "relative/path/custdata-2",
- *
- * ...
- *
- * "relative/path/custdata-N"
- *
- * ]
- *
The preceding JSON matches the following S3Uris:
- * s3://customer_bucket/some/prefix/relative/path/to/custdata-1
- *
- * s3://customer_bucket/some/prefix/relative/path/custdata-2
- *
- * ...
- *
- * s3://customer_bucket/some/prefix/relative/path/custdata-N
- *
The complete set of S3Uris in this manifest constitutes the
- * input data for the channel for this datasource. The object that each
- * S3Uris points to must be readable by the IAM role that Amazon SageMaker
- * uses to perform tasks on your behalf.
Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ \{"prefix": "s3://customer_bucket/some/prefix/"\},
"relative/path/to/custdata-1",
"relative/path/custdata-2",
...
"relative/path/custdata-N"
]
The preceding JSON matches the following S3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
Describes the input source of a transform job and the way the transform job consumes - * it.
+ *Describes the input source of a transform job and the way the transform job consumes it.
* @public */ export interface TransformInput { /** - *Describes the location of - * the - * channel data, which is, the S3 location of the input data that the - * model can consume.
+ *Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
* @public */ DataSource: TransformDataSource | undefined; /** - *The multipurpose internet mail extension - * (MIME) - * type of the data. Amazon SageMaker uses the MIME type with each http call to - * transfer data to the transform job.
+ *The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
* @public */ ContentType?: string | undefined; /** - *If your transform data
- * is
- * compressed, specify the compression type. Amazon SageMaker automatically
- * decompresses the data for the transform job accordingly. The default value is
- * None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
The method to use to split the transform job's data files into smaller batches.
- * Splitting is necessary when the total size of each object is too large to fit in a
- * single request. You can also use data splitting to improve performance by processing
- * multiple concurrent mini-batches. The default value for SplitType is
- * None, which indicates that input data files are not split, and request
- * payloads contain the entire contents of an input object. Set the value of this parameter
- * to Line to split records on a newline character boundary.
- * SplitType also supports a number of record-oriented binary data
- * formats. Currently, the supported record formats are:
RecordIO
- *TFRecord
- *When splitting is enabled, the size of a mini-batch depends on the values of the
- * BatchStrategy and MaxPayloadInMB parameters. When the
- * value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum
- * number of records in each request, up to the MaxPayloadInMB limit. If the
- * value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual
- * records in each request.
Some data formats represent a record as a binary payload wrapped with extra
- * padding bytes. When splitting is applied to a binary data format, padding is removed
- * if the value of BatchStrategy is set to SingleRecord.
- * Padding is not removed if the value of BatchStrategy is set to
- * MultiRecord.
For more information about RecordIO, see Create a Dataset Using
- * RecordIO in the MXNet documentation. For more information about
- * TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
The method to use to split the transform job's data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType is None, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line to split records on a newline character boundary. SplitType also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy and MaxPayloadInMB parameters. When the value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB limit. If the value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy is set to SingleRecord. Padding is not removed if the value of BatchStrategy is set to MultiRecord.
For more information about RecordIO, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For
- * example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the
- * transformed data with an .out suffix in a corresponding subfolder in the
- * location in the output prefix. For example, for the input data stored at
- * s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform
- * stores the transformed data at
- * s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out.
- * Batch transform doesn't upload partially processed objects. For an input S3 object that
- * contains multiple records, it creates an .out file only if the transform
- * job succeeds on the entire file. When the input contains multiple S3 objects, the batch
- * transform job processes the listed S3 objects and uploads only the output for
- * successfully processed objects. If any object fails in the transform job batch transform
- * marks the job as failed to prompt investigation.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http - * call to transfer data from the transform job.
+ *The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
* @public */ Accept?: string | undefined; /** - *Defines how to assemble the results of the transform job as a single S3 object. Choose
- * a format that is most convenient to you. To concatenate the results in binary format,
- * specify None. To add a newline character at the end of every transformed
- * record, specify
- * Line.
Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using
- * Amazon S3 server-side encryption. The KmsKeyId can be any of the following
- * formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your - * role's account. For more information, see KMS-Managed Encryption Keys in the - * Amazon Simple Storage Service - * Developer Guide. - *
- *The KMS key policy must grant permission to the IAM role that you specify in your - * CreateModel - * request. For more information, see Using - * Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer - * Guide.
+ *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
* @public */ KmsKeyId?: string | undefined; } /** - *Describes the resources, including ML instance types and ML instance count, to use for - * transform job.
+ *Describes the resources, including ML instance types and ML instance count, to use for transform job.
* @public */ export interface TransformResources { /** - *The ML compute instance type for the transform job. If you are using built-in
- * algorithms to
- * transform
- * moderately sized datasets, we recommend using ml.m4.xlarge or
- * ml.m5.largeinstance types.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.largeinstance types.
The number of
- * ML
- * compute instances to use in the transform job. The default value is
- * 1, and the maximum is 100. For distributed transform jobs,
- * specify a value greater than 1.
The number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume - * attached to the ML compute instance(s) that run the batch transform job.
- *Certain Nitro-based instances include local storage, dependent on the instance
- * type. Local storage volumes are encrypted using a hardware module on the instance.
- * You can't request a VolumeKmsKeyId when using an instance type with
- * local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
- *For more information about local instance storage encryption, see SSD - * Instance Store Volumes.
- *
- * The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) - * images. Each image is configured by Amazon Web Services with a set of software and driver - * versions.
- *Accelerator: GPU
- *NVIDIA driver version: 470
- *Accelerator: GPU
- *NVIDIA driver version: 535
- *Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions.
Accelerator: GPU
NVIDIA driver version: 470
Accelerator: GPU
NVIDIA driver version: 535
Defines the input needed to run a transform job using the inference specification - * specified in the algorithm.
+ *Defines the input needed to run a transform job using the inference specification specified in the algorithm.
* @public */ export interface TransformJobDefinition { /** - *The maximum number of parallel requests that can be sent to each instance in a - * transform job. The default value is 1.
+ *The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
* @public */ MaxConcurrentTransforms?: number | undefined; /** - *The maximum payload size allowed, in MB. A payload is the data portion of a record - * (without metadata).
+ *The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
* @public */ MaxPayloadInMB?: number | undefined; /** - *A string that determines the number of records included in a single mini-batch.
- *
- * SingleRecord means only one record is used per mini-batch.
- * MultiRecord means a mini-batch is set to contain as many records that
- * can fit within the MaxPayloadInMB limit.
A string that determines the number of records included in a single mini-batch.
SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.
The environment variables to set in the Docker container. We support up to 16 key and - * values entries in the map.
+ *The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
* @public */ Environment?: RecordIdentifies the Amazon S3 location where you want Amazon SageMaker to save the results from the - * transform job.
+ *Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
* @public */ TransformOutput: TransformOutput | undefined; @@ -2852,38 +2007,31 @@ export interface TransformJobDefinition { } /** - *Defines a training job and a batch transform job that SageMaker runs to validate your - * algorithm.
- *The data provided in the validation profile is made available to your buyers on - * Amazon Web Services Marketplace.
+ *Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
* @public */ export interface AlgorithmValidationProfile { /** - *The name of the profile for the algorithm. The name must have 1 to 63 characters. - * Valid characters are a-z, A-Z, 0-9, and - (hyphen).
+ *The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
* @public */ ProfileName: string | undefined; /** - *The TrainingJobDefinition object that describes the training job that
- * SageMaker runs to validate your algorithm.
The TrainingJobDefinition object that describes the training job that SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job that
- * SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the - * algorithm.
+ *Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
* @public */ export interface AlgorithmValidationSpecification { @@ -2894,8 +2042,7 @@ export interface AlgorithmValidationSpecification { ValidationRole: string | undefined; /** - *An array of AlgorithmValidationProfile objects, each of which specifies a
- * training job and batch transform job that SageMaker runs to validate your algorithm.
An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
- *For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
- * Bounding box - Finds the most similar boxes from - * different workers based on the Jaccard index of the boxes.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
- *
- * Image classification - Uses a variant of the - * Expectation Maximization approach to estimate the true class of an image based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
- *
- * Multi-label image classification - Uses a variant of - * the Expectation Maximization approach to estimate the true classes of an image based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
- *
- * Semantic segmentation - Treats each pixel in an image - * as a multi-class classification and treats pixel annotations from workers as "votes" for - * the correct label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
- *
- * Text classification - Uses a variant of the - * Expectation Maximization approach to estimate the true class of text based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
- *
- * Multi-label text classification - Uses a variant of - * the Expectation Maximization approach to estimate the true classes of text based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
- *
- * Named entity recognition - Groups similar selections - * and calculates aggregate boundaries, resolving to most-assigned label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
- *
- * Video Classification - Use this task type when you need workers to classify videos using - * predefined labels that you specify. Workers are shown videos and are asked to choose one - * label for each video.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
- *
- * Video Frame Object Detection - Use this task type to - * have workers identify and locate objects in a sequence of video frames (images extracted - * from a video) using bounding boxes. For example, you can use this task to ask workers to - * identify and localize various objects in a series of video frames, such as cars, bikes, - * and pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
- *
- * Video Frame Object Tracking - Use this task type to - * have workers track the movement of objects in a sequence of video frames (images - * extracted from a video) using bounding boxes. For example, you can use this task to ask - * workers to track the movement of objects, such as cars, bikes, and pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
- *
- * 3D Point Cloud Object Detection - Use this task type - * when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids - * around objects. For example, you can use this task type to ask workers to identify - * different types of objects in a point cloud, such as cars, bikes, and - * pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
- *
- * 3D Point Cloud Object Tracking - Use this task type - * when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D - * point cloud frames. For example, you can use this task type to ask workers to track the - * movement of vehicles across multiple point cloud frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
- *
- * 3D Point Cloud Semantic Segmentation - Use this task - * type when you want workers to create a point-level semantic segmentation masks by - * painting objects in a 3D point cloud using different colors where each color is assigned - * to one of the classes you specify.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
- *
- * Use the following ARNs for Label Verification and Adjustment Jobs - *
- *Use label verification and adjustment jobs to review and adjust labels. To learn more, - * see Verify and Adjust Labels .
- *- * Semantic Segmentation Adjustment - Treats each pixel - * in an image as a multi-class classification and treats pixel adjusted annotations from - * workers as "votes" for the correct label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
- *
- * Semantic Segmentation Verification - Uses a variant - * of the Expectation Maximization approach to estimate the true class of verification - * judgment for semantic segmentation labels based on annotations from individual - * workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
- *
- * Bounding Box Adjustment - Finds the most similar - * boxes from different workers based on the Jaccard index of the adjusted - * annotations.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
- *
- * Bounding Box Verification - Uses a variant of the - * Expectation Maximization approach to estimate the true class of verification judgement - * for bounding box labels based on annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
- *
- * Video Frame Object Detection Adjustment - - * Use this task type when you want workers to adjust bounding boxes that workers have added - * to video frames to classify and localize objects in a sequence of video frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
- *
- * Video Frame Object Tracking Adjustment - - * Use this task type when you want workers to adjust bounding boxes that workers have added - * to video frames to track object movement across a sequence of video frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
- *
- * 3D Point Cloud Object Detection Adjustment - Use this - * task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
- *
- * 3D Point Cloud Object Tracking Adjustment - Use this - * task type when you want workers to adjust 3D cuboids around objects that appear in a - * sequence of 3D point cloud frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
- *
- * 3D Point Cloud Semantic Segmentation Adjustment - Use this task - * type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
- *
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The instance type that the image version runs on.
- *
- * JupyterServer apps only support the system value.
For KernelGateway apps, the system
- * value is translated to ml.t3.medium. KernelGateway apps also support all other values for available
- * instance types.
The instance type that the image version runs on.
JupyterServer apps only support the system value.
For KernelGateway apps, the system value is translated to ml.t3.medium. KernelGateway apps also support all other values for available instance types.
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the - * Resource.
+ *The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
* @public */ LifecycleConfigArn?: string | undefined; @@ -4720,11 +2388,7 @@ export interface AppDetails { CreationTime?: Date | undefined; /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The path within the image to mount the user's EFS home directory. The directory - * should be empty. If not specified, defaults to /home/sagemaker-user.
+ *The path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
* @public */ MountPath?: string | undefined; @@ -4780,8 +2443,7 @@ export interface FileSystemConfig { } /** - *The configuration for the file system and kernels in a SageMaker image running as a Code Editor app.
- * The FileSystemConfig object is not supported.
The configuration for the file system and kernels in a SageMaker image running as a Code Editor app. The FileSystemConfig object is not supported.
The configuration for the file system and kernels in a SageMaker AI image running as a - * KernelGateway app.
+ *The configuration for the file system and kernels in a SageMaker AI image running as a KernelGateway app.
* @public */ export interface KernelGatewayImageConfig { @@ -4895,8 +2556,7 @@ export interface AppImageConfigDetails { JupyterLabAppImageConfig?: JupyterLabAppImageConfig | undefined; /** - *The configuration for the file system and the runtime, - * such as the environment variables and entry point.
+ *The configuration for the file system and the runtime, such as the environment variables and entry point.
* @public */ CodeEditorAppImageConfig?: CodeEditorAppImageConfig | undefined; @@ -4943,8 +2603,7 @@ export interface IdleSettings { LifecycleManagement?: LifecycleManagement | undefined; /** - *The time that SageMaker waits after the application becomes idle before shutting it - * down.
+ *The time that SageMaker waits after the application becomes idle before shutting it down.
* @public */ IdleTimeoutInMinutes?: number | undefined; @@ -4963,8 +2622,7 @@ export interface IdleSettings { } /** - *Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio - * applications.
+ *Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio applications.
* @public */ export interface AppLifecycleManagement { @@ -5093,8 +2751,7 @@ export interface ArtifactSource { } /** - *Lists a summary of the properties of an artifact. An artifact represents a URI - * addressable object or data. Some examples are a dataset and a model.
+ *Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
* @public */ export interface ArtifactSummary { @@ -5170,8 +2827,7 @@ export interface AssociateTrialComponentResponse { } /** - *The IAM Identity details associated with the user. These details are - * associated with model package groups, model packages and project entities only.
+ *The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
* @public */ export interface IamIdentity { @@ -5195,8 +2851,7 @@ export interface IamIdentity { } /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ export interface UserContext { @@ -5219,17 +2874,14 @@ export interface UserContext { DomainId?: string | undefined; /** - *The IAM Identity details associated with the user. These details are - * associated with model package groups, model packages, and project entities only.
+ *The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
* @public */ IamIdentity?: IamIdentity | undefined; } /** - *Lists a summary of the properties of an association. An association is an entity that - * links other lineage or experiment entities. An example would be an association between a - * training job and a model.
+ *Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
* @public */ export interface AssociationSummary { @@ -5282,22 +2934,19 @@ export interface AssociationSummary { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; } /** - *Configures the behavior of the client used by SageMaker to interact with the model - * container during asynchronous inference.
+ *Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
* @public */ export interface AsyncInferenceClientConfig { /** - *The maximum number of concurrent requests sent by the SageMaker client to the model - * container. If no value is provided, SageMaker chooses an optimal value.
+ *The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
* @public */ MaxConcurrentInvocationsPerInstance?: number | undefined; @@ -5319,31 +2968,24 @@ export type AsyncNotificationTopicTypes = (typeof AsyncNotificationTopicTypes)[keyof typeof AsyncNotificationTopicTypes]; /** - *Specifies the configuration for notifications of inference results for asynchronous - * inference.
+ *Specifies the configuration for notifications of inference results for asynchronous inference.
* @public */ export interface AsyncInferenceNotificationConfig { /** - *Amazon SNS topic to post a notification to when inference completes successfully. If no - * topic is provided, no notification is sent on success.
+ *Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
* @public */ SuccessTopic?: string | undefined; /** - *Amazon SNS topic to post a notification to when inference fails. If no topic is provided, - * no notification is sent on failure.
+ *Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
* @public */ ErrorTopic?: string | undefined; /** - *The Amazon SNS topics where you want the inference response to be included.
- *The inference response is included only if the response size is less than or equal - * to 128 KB.
- *The Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker - * uses to encrypt the asynchronous inference output in Amazon S3.
- * + *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
* @public */ KmsKeyId?: string | undefined; @@ -5369,8 +3009,7 @@ export interface AsyncInferenceOutputConfig { S3OutputPath?: string | undefined; /** - *Specifies the configuration for notifications of inference results for asynchronous - * inference.
+ *Specifies the configuration for notifications of inference results for asynchronous inference.
* @public */ NotificationConfig?: AsyncInferenceNotificationConfig | undefined; @@ -5388,8 +3027,7 @@ export interface AsyncInferenceOutputConfig { */ export interface AsyncInferenceConfig { /** - *Configures the behavior of the client used by SageMaker to interact with the model - * container during asynchronous inference.
+ *Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
* @public */ ClientConfig?: AsyncInferenceClientConfig | undefined; @@ -5470,8 +3108,7 @@ export interface AthenaDatasetDefinition { OutputS3Uri: string | undefined; /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker - * uses to encrypt data generated from an Athena query execution.
+ *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
* @public */ KmsKeyId?: string | undefined; @@ -5531,103 +3168,12 @@ export const AutoMLAlgorithm = { export type AutoMLAlgorithm = (typeof AutoMLAlgorithm)[keyof typeof AutoMLAlgorithm]; /** - *The selection of algorithms trained on your dataset to generate the model candidates for - * an Autopilot job.
+ *The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
* @public */ export interface AutoMLAlgorithmConfig { /** - *The selection of algorithms trained on your dataset to generate the model candidates for - * an Autopilot job.
- *
- * For the tabular problem type
- * TabularJobConfig:
- *
Selected algorithms must belong to the list corresponding to the training mode
- * set in AutoMLJobConfig.Mode (ENSEMBLING or
- * HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
"catboost"
- *"extra-trees"
- *"fastai"
- *"lightgbm"
- *"linear-learner"
- *"nn-torch"
- *"randomforest"
- *"xgboost"
- *In HYPERPARAMETER_TUNING mode:
"linear-learner"
- *"mlp"
- *"xgboost"
- *
- * For the time-series forecasting problem type
- * TimeSeriesForecastingJobConfig:
- *
Choose your algorithms from this list.
- *"cnn-qr"
- *"deepar"
- *"prophet"
- *"arima"
- *"npts"
- *"ets"
- *The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
For the tabular problem type TabularJobConfig:
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING or HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
"catboost"
"extra-trees"
"fastai"
"lightgbm"
"linear-learner"
"nn-torch"
"randomforest"
"xgboost"
In HYPERPARAMETER_TUNING mode:
"linear-learner"
"mlp"
"xgboost"
For the time-series forecasting problem type TimeSeriesForecastingJobConfig:
Choose your algorithms from this list.
"cnn-qr"
"deepar"
"prophet"
"arima"
"npts"
"ets"
The Amazon S3 prefix to the explainability artifacts generated for the AutoML - * candidate.
+ *The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
* @public */ Explainability: string | undefined; /** - *The Amazon S3 prefix to the model insight artifacts generated for the AutoML - * candidate.
+ *The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
* @public */ ModelInsights?: string | undefined; /** - *The Amazon S3 prefix to the accuracy metrics and the inference results observed - * over the testing window. Available only for the time-series forecasting problem - * type.
+ *The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
* @public */ BacktestResults?: string | undefined; @@ -5755,12 +3297,7 @@ export interface MetricDatum { MetricName?: AutoMLMetricEnum | undefined; /** - *The name of the standard metric.
- *For definitions of the standard metrics, see
- * Autopilot candidate metrics
- * .
The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics .
The name of the metric with the best result. For a description of the possible objective - * metrics, see AutoMLJobObjective$MetricName.
+ *The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
* @public */ MetricName: AutoMLMetricEnum | undefined; @@ -5891,8 +3427,7 @@ export interface FinalAutoMLJobObjectiveMetric { Value: number | undefined; /** - *The name of the standard metric. For a description of the standard metrics, see Autopilot - * candidate metrics.
+ *The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
* @public */ StandardMetricName?: AutoMLMetricEnum | undefined; @@ -5913,30 +3448,24 @@ export const AutoMLProcessingUnit = { export type AutoMLProcessingUnit = (typeof AutoMLProcessingUnit)[keyof typeof AutoMLProcessingUnit]; /** - *A list of container definitions that describe the different containers that make up an - * AutoML candidate. For more information, see - * ContainerDefinition.
+ *A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
* @public */ export interface AutoMLContainerDefinition { /** - *The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more - * information, see - * ContainerDefinition.
+ *The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
* @public */ Image: string | undefined; /** - *The location of the model artifacts. For more information, see - * ContainerDefinition.
+ *The location of the model artifacts. For more information, see ContainerDefinition.
* @public */ ModelDataUrl: string | undefined; /** - *The environment variables to set in the container. For more information, see - * ContainerDefinition.
+ *The environment variables to set in the container. For more information, see ContainerDefinition.
* @public */ Environment?: RecordInformation about a candidate produced by an AutoML training job, including its status, - * steps, and other properties.
+ *Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
* @public */ export interface AutoMLCandidate { @@ -6030,10 +3558,7 @@ export interface AutoMLCandidate { CandidateProperties?: CandidateProperties | undefined; /** - *The mapping of all supported processing unit (CPU, GPU, etc...) to inference container
- * definitions for the candidate. This field is populated for the AutoML jobs V2 (for example,
- * for jobs created by calling CreateAutoMLJobV2) related to image or text
- * classification problem types only.
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2) related to image or text classification problem types only.
A URL to the Amazon S3 data source containing selected features from the input
- * data source to run an Autopilot job. You can input FeatureAttributeNames
- * (optional) in JSON format as shown below:
- * \{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown - * below:
- *
- * \{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
- *
These column keys may not include the target column.
- *In ensembling mode, Autopilot only supports the following data types: numeric,
- * categorical, text, and datetime. In HPO mode,
- * Autopilot can support numeric, categorical, text,
- * datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1,
- * col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are
- * provided, then the column keys should be a subset of the column names provided in
- * FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in
- * ["col1", "col2", ...] are case sensitive and should be a list of strings
- * containing unique values that are a subset of the column names in the input data. The list
- * of columns provided must not include the target column.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:
\{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown below:
\{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Stores the configuration information for the selection of algorithms trained on tabular - * data.
- *The list of available algorithms to choose from depends on the training mode set in
- *
- * TabularJobConfig.Mode
- * .
- * AlgorithmsConfig should not be set if the training mode is set on
- * AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms
- * attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is
- * empty, CandidateGenerationConfig uses the full set of algorithms for the
- * given training mode.
When AlgorithmsConfig is not provided,
- * CandidateGenerationConfig uses the full set of algorithms for the
- * given training mode.
For the list of all algorithms per problem type and training mode, see - * AutoMLAlgorithmConfig.
- *For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
+ *Stores the configuration information for the selection of algorithms trained on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .
AlgorithmsConfig should not be set if the training mode is set on AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
* @public */ AlgorithmsConfig?: AutoMLAlgorithmConfig[] | undefined; @@ -6144,60 +3617,13 @@ export type AutoMLS3DataType = (typeof AutoMLS3DataType)[keyof typeof AutoMLS3Da */ export interface AutoMLS3DataSource { /** - *The data type.
- *If you choose S3Prefix, S3Uri identifies a key name
- * prefix. SageMaker AI uses all objects that match the specified key name prefix
- * for model training.
The S3Prefix should have the following format:
- * s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
- *
If you choose ManifestFile, S3Uri identifies an object
- * that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.
A ManifestFile should have the format shown below:
- * [ \{"prefix":
- * "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"\},
- *
- * "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
- *
- * "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
- *
- * ... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
- *
If you choose AugmentedManifestFile, S3Uri identifies an
- * object that is an augmented manifest file in JSON lines format. This file contains
- * the data you want to use for model training. AugmentedManifestFile is
- * available for V2 API jobs only (for example, for jobs created by calling
- * CreateAutoMLJobV2).
Here is a minimal, single-record example of an
- * AugmentedManifestFile:
- * \{"source-ref":
- * "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
- *
- * "label-metadata": \{"class-name": "cat" \}
For more information on AugmentedManifestFile, see Provide
- * Dataset Metadata to Training Jobs with an Augmented Manifest File.
The data type.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker AI uses all objects that match the specified key name prefix for model training.
The S3Prefix should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.
A ManifestFile should have the format shown below:
[ \{"prefix": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"\},
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",
"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",
... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).
Here is a minimal, single-record example of an AugmentedManifestFile:
\{"source-ref": "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",
"label-metadata": \{"class-name": "cat" \}
For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 - * prefix or ManifestFile depending on the data type.
+ *The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
* @public */ S3Uri: string | undefined; @@ -6216,13 +3642,7 @@ export interface AutoMLDataSource { } /** - *A channel is a named input source that training algorithms can consume. The validation - * dataset size is limited to less than 2 GB. The training dataset size must be less than 100 - * GB. For more information, see Channel.
- *A validation dataset must contain the same headers as the training dataset.
- *A channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
You can use Gzip or None. The default value is
- * None.
You can use Gzip or None. The default value is None.
The name of the target variable in supervised learning, usually represented by - * 'y'.
+ *The name of the target variable in supervised learning, usually represented by 'y'.
* @public */ TargetAttributeName: string | undefined; /** - *The content type of the data from the input source. You can use
- * text/csv;header=present or x-application/vnd.amazon+parquet.
- * The default value is text/csv;header=present.
The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The channel type (optional) is an enum string. The default value is
- * training. Channels for training and validation must share the same
- * ContentType and TargetAttributeName. For information on
- * specifying training and validation channel types, see How to specify training and validation datasets.
The channel type (optional) is an enum string. The default value is training. Channels for training and validation must share the same ContentType and TargetAttributeName. For information on specifying training and validation channel types, see How to specify training and validation datasets.
If specified, this column name indicates which column of the dataset should be treated - * as sample weights for use by the objective metric during the training, evaluation, and the - * selection of the best model. This column is not considered as a predictive feature. For - * more information on Autopilot metrics, see Metrics and - * validation.
- *Sample weights should be numeric, non-negative, with larger values indicating which rows - * are more important than others. Data points that have invalid or no weight value are - * excluded.
- *Support for sample weights is available in Ensembling - * mode only.
+ *If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
* @public */ SampleWeightAttributeName?: string | undefined; } /** - *This data type is intended for use exclusively by SageMaker Canvas and cannot be used in - * other contexts at the moment.
- *Specifies the compute configuration for the EMR Serverless job.
+ *This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for the EMR Serverless job.
* @public */ export interface EmrServerlessComputeConfig { /** - *The ARN of the IAM role granting the AutoML job V2 the necessary - * permissions access policies to list, connect to, or manage EMR Serverless jobs. For - * detailed information about the required permissions of this role, see "How to configure - * AutoML to initiate a remote job on EMR Serverless for large datasets" in Create a regression or classification job for tabular data using the AutoML API - * or Create an AutoML job for time-series forecasting using the API.
+ *The ARN of the IAM role granting the AutoML job V2 the necessary permissions access policies to list, connect to, or manage EMR Serverless jobs. For detailed information about the required permissions of this role, see "How to configure AutoML to initiate a remote job on EMR Serverless for large datasets" in Create a regression or classification job for tabular data using the AutoML API or Create an AutoML job for time-series forecasting using the API.
* @public */ ExecutionRoleARN: string | undefined; } /** - *This data type is intended for use exclusively by SageMaker Canvas and cannot be used in - * other contexts at the moment.
- *Specifies the compute configuration for an AutoML job V2.
+ *This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for an AutoML job V2.
* @public */ export interface AutoMLComputeConfig { /** - *The configuration for using EMR Serverless - * to run the AutoML job V2.
- *To allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless
- * when additional compute resources are needed to process large datasets, you need to provide
- * an EmrServerlessComputeConfig object, which includes an
- * ExecutionRoleARN attribute, to the AutoMLComputeConfig of the
- * AutoML job V2 input request.
By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle - * datasets that would otherwise exceed the initially provisioned resources, without any - * manual intervention from you.
- *EMR Serverless is available for the tabular and time series problem types. We - * recommend setting up this option for tabular datasets larger than 5 GB and time series - * datasets larger than 30 GB.
+ *The configuration for using EMR Serverless to run the AutoML job V2.
To allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless when additional compute resources are needed to process large datasets, you need to provide an EmrServerlessComputeConfig object, which includes an ExecutionRoleARN attribute, to the AutoMLComputeConfig of the AutoML job V2 input request.
By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle datasets that would otherwise exceed the initially provisioned resources, without any manual intervention from you.
EMR Serverless is available for the tabular and time series problem types. We recommend setting up this option for tabular datasets larger than 5 GB and time series datasets larger than 30 GB.
* @public */ EmrServerlessComputeConfig?: EmrServerlessComputeConfig | undefined; } /** - *This structure specifies how to split the data into train and validation - * datasets.
- *The validation and training datasets must contain the same headers. For jobs created by
- * calling CreateAutoMLJob, the validation dataset must be less than 2 GB in
- * size.
This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
The validation fraction (optional) is a float that specifies the portion of the training - * dataset to be used for validation. The default value is 0.2, and values must be greater - * than 0 and less than 1. We recommend setting this value to be less than 0.5.
+ *The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
* @public */ ValidationFraction?: number | undefined; @@ -6364,62 +3738,24 @@ export interface AutoMLJobArtifacts { } /** - *A channel is a named input source that training algorithms can consume. This channel is - * used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
+ *A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
* @public */ export interface AutoMLJobChannel { /** - *The type of channel. Defines whether the data are used for training or validation. The
- * default value is training. Channels for training and
- * validation must share the same ContentType
- *
The type of channel defaults to training for the time-series forecasting
- * problem type.
The type of channel. Defines whether the data are used for training or validation. The default value is training. Channels for training and validation must share the same ContentType
The type of channel defaults to training for the time-series forecasting problem type.
The content type of the data from the input source. The following are the allowed - * content types for different problems:
- *For tabular problem types: text/csv;header=present or
- * x-application/vnd.amazon+parquet. The default value is
- * text/csv;header=present.
For image classification: image/png, image/jpeg, or
- * image/*. The default value is image/*.
For text classification: text/csv;header=present or
- * x-application/vnd.amazon+parquet. The default value is
- * text/csv;header=present.
For time-series forecasting: text/csv;header=present or
- * x-application/vnd.amazon+parquet. The default value is
- * text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or
- * x-application/vnd.amazon+parquet. The default value is
- * text/csv;header=present.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For image classification: image/png, image/jpeg, or image/*. The default value is image/*.
For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The allowed compression types depend on the input format and problem type. We allow the
- * compression type Gzip for S3Prefix inputs on tabular data only.
- * For all other inputs, the compression type should be None. If no compression
- * type is provided, we default to None.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression type should be None. If no compression type is provided, we default to None.
How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ export interface AutoMLJobCompletionCriteria { /** - *The maximum number of times a training job is allowed to run.
- *For text and image classification, time-series forecasting, as well as text generation - * (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the - * maximum value is 750.
+ *The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
* @public */ MaxCandidates?: number | undefined; /** - *The maximum time, in seconds, that each training job executed inside hyperparameter - * tuning is allowed to run as part of a hyperparameter tuning job. For more information, see - * the StoppingCondition - * used by the CreateHyperParameterTuningJob action.
- *For job V2s (jobs created by calling CreateAutoMLJobV2), this field
- * controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours - * (259200 seconds).
+ *The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2), this field controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours (259200 seconds).
* @public */ MaxRuntimePerTrainingJobInSeconds?: number | undefined; /** - *The maximum runtime, in seconds, an AutoML job has to complete.
- *If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its - * processing is ended gracefully. The AutoML job identifies the best model whose training was - * completed and marks it as the best-performing model. Any unfinished steps of the job, such - * as automatic one-click Autopilot model deployment, are not completed.
+ *The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
* @public */ MaxAutoMLJobRuntimeInSeconds?: number | undefined; @@ -6486,24 +3807,18 @@ export const AutoMLMode = { export type AutoMLMode = (typeof AutoMLMode)[keyof typeof AutoMLMode]; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ export interface VpcConfig { /** - *The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security
- * groups for the VPC that is specified in the Subnets field.
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your training job or - * model. For information about the availability of specific instance types, see Supported - * Instance Types and Availability Zones.
+ *The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
* @public */ Subnets: string[] | undefined; @@ -6539,8 +3854,7 @@ export interface AutoMLSecurityConfig { */ export interface AutoMLJobConfig { /** - *How long an AutoML job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; @@ -6558,29 +3872,13 @@ export interface AutoMLJobConfig { CandidateGenerationConfig?: AutoMLCandidateGenerationConfig | undefined; /** - *The configuration for splitting the input training dataset.
- *Type: AutoMLDataSplitConfig
+ *The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
* @public */ DataSplitConfig?: AutoMLDataSplitConfig | undefined; /** - *The method that Autopilot uses to train the data. You can either specify the mode manually
- * or let Autopilot choose for you based on the dataset size by selecting AUTO. In
- * AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than
- * 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict
- * classification and regression tasks directly from your dataset. This machine learning mode
- * combines several base models to produce an optimal predictive model. It then uses a
- * stacking ensemble method to combine predictions from contributing members. A multi-stack
- * ensemble model can provide better performance over a single model by combining the
- * predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by
- * ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train
- * the best version of a model. HPO automatically selects an algorithm for the type of problem
- * you want to solve. Then HPO finds the best hyperparameters according to your objective
- * metric. See Autopilot algorithm support for a list of algorithms supported by
- * HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
The name of the objective metric used to measure the predictive quality of a machine - * learning system. During training, the model's parameters are updated iteratively to - * optimize its performance based on the feedback provided by the objective metric when - * evaluating the model on the validation dataset.
- *The list of available metrics supported by Autopilot and the default metric applied when you - * do not specify a metric name explicitly depend on the problem type.
- *For tabular problem types:
- *List of available metrics:
- * Regression: MAE, MSE, R2,
- * RMSE
- *
Binary classification: Accuracy, AUC,
- * BalancedAccuracy, F1,
- * Precision, Recall
- *
Multiclass classification: Accuracy,
- * BalancedAccuracy, F1macro,
- * PrecisionMacro, RecallMacro
- *
For a description of each metric, see Autopilot metrics for classification and regression.
- *Default objective metrics:
- *Regression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
- *List of available metrics: Accuracy
- *
For a description of each metric, see Autopilot metrics for text and image classification.
- *Default objective metrics: Accuracy
- *
For time-series forecasting problem types:
- *List of available metrics: RMSE, wQL,
- * Average wQL, MASE, MAPE,
- * WAPE
- *
For a description of each metric, see Autopilot metrics for - * time-series forecasting.
- *Default objective metrics: AverageWeightedQuantileLoss
- *
For text generation problem types (LLMs fine-tuning):
- * Fine-tuning language models in Autopilot does not
- * require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs
- * without requiring multiple candidates to be trained and evaluated.
- * Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a
- * default objective metric, the cross-entropy loss. After fine-tuning a language model,
- * you can evaluate the quality of its generated text using different metrics.
- * For a list of the available metrics, see Metrics for
- * fine-tuning LLMs in Autopilot.
The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: MAE, MSE, R2, RMSE
Binary classification: Accuracy, AUC, BalancedAccuracy, F1, Precision, Recall
Multiclass classification: Accuracy, BalancedAccuracy, F1macro, PrecisionMacro, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE, wQL, Average wQL, MASE, MAPE, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
The collection of settings used by an AutoML job V2 for the image classification problem - * type.
+ *The collection of settings used by an AutoML job V2 for the image classification problem type.
* @public */ export interface ImageClassificationJobConfig { /** - *How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; } /** - *Stores the configuration information for how model candidates are generated using an - * AutoML job V2.
+ *Stores the configuration information for how model candidates are generated using an AutoML job V2.
* @public */ export interface CandidateGenerationConfig { /** - *Your Autopilot job trains a default set of algorithms on your dataset. For tabular and - * time-series data, you can customize the algorithm list by selecting a subset of algorithms - * for your problem type.
- *
- * AlgorithmsConfig stores the customized selection of algorithms to train on
- * your data.
- * For the tabular problem type
- * TabularJobConfig, the list of available algorithms to
- * choose from depends on the training mode set in
- * AutoMLJobConfig.Mode
- * .
- * AlgorithmsConfig should not be set when the training mode
- * AutoMLJobConfig.Mode is set to AUTO.
When AlgorithmsConfig is provided, one
- * AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for
- * AutoMLAlgorithms is empty,
- * CandidateGenerationConfig uses the full set of algorithms for
- * the given training mode.
When AlgorithmsConfig is not provided,
- * CandidateGenerationConfig uses the full set of algorithms for
- * the given training mode.
For the list of all algorithms per training mode, see - * AlgorithmConfig.
- *For more information on each algorithm, see the Algorithm support section in the Autopilot developer guide.
- *
- * For the time-series forecasting problem type
- * TimeSeriesForecastingJobConfig, choose your algorithms
- * from the list provided in
- * AlgorithmConfig.
For more information on each algorithm, see the Algorithms - * support for time-series forecasting section in the Autopilot developer - * guide.
- *When AlgorithmsConfig is provided, one
- * AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for
- * AutoMLAlgorithms is empty,
- * CandidateGenerationConfig uses the full set of algorithms for
- * time-series forecasting.
When AlgorithmsConfig is not provided,
- * CandidateGenerationConfig uses the full set of algorithms for
- * time-series forecasting.
Your Autopilot job trains a default set of algorithms on your dataset. For tabular and time-series data, you can customize the algorithm list by selecting a subset of algorithms for your problem type.
AlgorithmsConfig stores the customized selection of algorithms to train on your data.
For the tabular problem type TabularJobConfig, the list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .
AlgorithmsConfig should not be set when the training mode AutoMLJobConfig.Mode is set to AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in the Autopilot developer guide.
For the time-series forecasting problem type TimeSeriesForecastingJobConfig, choose your algorithms from the list provided in AlgorithmConfig.
For more information on each algorithm, see the Algorithms support for time-series forecasting section in the Autopilot developer guide.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for time-series forecasting.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for time-series forecasting.
How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; /** - *A URL to the Amazon S3 data source containing selected features from the input
- * data source to run an Autopilot job V2. You can input FeatureAttributeNames
- * (optional) in JSON format as shown below:
- * \{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown - * below:
- *
- * \{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
- *
These column keys may not include the target column.
- *In ensembling mode, Autopilot only supports the following data types: numeric,
- * categorical, text, and datetime. In HPO mode,
- * Autopilot can support numeric, categorical, text,
- * datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1,
- * col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are
- * provided, then the column keys should be a subset of the column names provided in
- * FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in
- * ["col1", "col2", ...] are case sensitive and should be a list of strings
- * containing unique values that are a subset of the column names in the input data. The list
- * of columns provided must not include the target column.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames (optional) in JSON format as shown below:
\{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown below:
\{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in ["col1", "col2", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The method that Autopilot uses to train the data. You can either specify the mode manually
- * or let Autopilot choose for you based on the dataset size by selecting AUTO. In
- * AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than
- * 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict
- * classification and regression tasks directly from your dataset. This machine learning mode
- * combines several base models to produce an optimal predictive model. It then uses a
- * stacking ensemble method to combine predictions from contributing members. A multi-stack
- * ensemble model can provide better performance over a single model by combining the
- * predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by
- * ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train
- * the best version of a model. HPO automatically selects an algorithm for the type of problem
- * you want to solve. Then HPO finds the best hyperparameters according to your objective
- * metric. See Autopilot algorithm support for a list of algorithms supported by
- * HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
Generates possible candidates without training the models. A model candidate is a - * combination of data preprocessors, algorithms, and algorithm parameter settings.
+ *Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
* @public */ GenerateCandidateDefinitionsOnly?: boolean | undefined; /** - *The type of supervised learning problem available for the model candidates of the AutoML - * job V2. For more information, see - * SageMaker Autopilot problem types.
- *You must either specify the type of supervised learning problem in
- * ProblemType and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType and provide the AutoMLJobObjective metric, or none at all.
The name of the target variable in supervised learning, usually represented by - * 'y'.
+ *The name of the target variable in supervised learning, usually represented by 'y'.
* @public */ TargetAttributeName: string | undefined; /** - *If specified, this column name indicates which column of the dataset should be treated - * as sample weights for use by the objective metric during the training, evaluation, and the - * selection of the best model. This column is not considered as a predictive feature. For - * more information on Autopilot metrics, see Metrics and - * validation.
- *Sample weights should be numeric, non-negative, with larger values indicating which rows - * are more important than others. Data points that have invalid or no weight value are - * excluded.
- *Support for sample weights is available in Ensembling - * mode only.
+ *If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
* @public */ SampleWeightAttributeName?: string | undefined; } /** - *The collection of settings used by an AutoML job V2 for the text classification problem - * type.
+ *The collection of settings used by an AutoML job V2 for the text classification problem type.
* @public */ export interface TextClassificationJobConfig { /** - *How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; /** - *The name of the column used to provide the sentences to be classified. It should not be - * the same as the target column.
+ *The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
* @public */ ContentColumn: string | undefined; /** - *The name of the column used to provide the class labels. It should not be same as the - * content column.
+ *The name of the column used to provide the class labels. It should not be same as the content column.
* @public */ TargetLabelColumn: string | undefined; } /** - *The collection of settings used by an AutoML job V2 for the text generation problem - * type.
- *The text generation models that support fine-tuning in Autopilot are currently accessible - * exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported - * Regions.
- *The collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
How long a fine-tuning job is allowed to run. For TextGenerationJobConfig
- * problem types, the MaxRuntimePerTrainingJobInSeconds attribute of
- * AutoMLJobCompletionCriteria defaults to 72h (259200s).
How long a fine-tuning job is allowed to run. For TextGenerationJobConfig problem types, the MaxRuntimePerTrainingJobInSeconds attribute of AutoMLJobCompletionCriteria defaults to 72h (259200s).
The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large
- * language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no
- * BaseModelName is provided, the default model used is Falcon7BInstruct.
The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName is provided, the default model used is Falcon7BInstruct.
The hyperparameters used to configure and optimize the learning process of the base - * model. You can set any combination of the following hyperparameters for all base models. - * For more information on each supported hyperparameter, see Optimize - * the learning process of your text generation models with hyperparameters.
- *
- * "epochCount": The number of times the model goes through the entire
- * training dataset. Its value should be a string containing an integer value within the
- * range of "1" to "10".
- * "batchSize": The number of data samples used in each iteration of
- * training. Its value should be a string containing an integer value within the range
- * of "1" to "64".
- * "learningRate": The step size at which a model's parameters are
- * updated during training. Its value should be a string containing a floating-point
- * value within the range of "0" to "1".
- * "learningRateWarmupSteps": The number of training steps during which
- * the learning rate gradually increases before reaching its target or maximum value.
- * Its value should be a string containing an integer value within the range of "0" to
- * "250".
Here is an example where all four hyperparameters are configured.
- *
- * \{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32",
- * "learningRateWarmupSteps": "10" \}
- *
The hyperparameters used to configure and optimize the learning process of the base model. You can set any combination of the following hyperparameters for all base models. For more information on each supported hyperparameter, see Optimize the learning process of your text generation models with hyperparameters.
"epochCount": The number of times the model goes through the entire training dataset. Its value should be a string containing an integer value within the range of "1" to "10".
"batchSize": The number of data samples used in each iteration of training. Its value should be a string containing an integer value within the range of "1" to "64".
"learningRate": The step size at which a model's parameters are updated during training. Its value should be a string containing a floating-point value within the range of "0" to "1".
"learningRateWarmupSteps": The number of training steps during which the learning rate gradually increases before reaching its target or maximum value. Its value should be a string containing an integer value within the range of "0" to "250".
Here is an example where all four hyperparameters are configured.
\{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32", "learningRateWarmupSteps": "10" \}
The access configuration file to control access to the ML model. You can explicitly accept the model
- * end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
- *If you are an AutoML user, see the Optional Parameters section of - * Create an AutoML job to fine-tune text generation models using the - * API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML - * API.
- *The access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
Stores the holiday featurization attributes applicable to each item of time-series - * datasets during the training of a forecasting model. This allows the model to identify - * patterns associated with specific holidays.
+ *Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
* @public */ export interface HolidayConfigAttributes { /** - *The country code for the holiday calendar.
- *For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your - * choice.
+ *The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
* @public */ CountryCode?: string | undefined; @@ -7193,29 +4211,25 @@ export interface HolidayConfigAttributes { */ export interface TimeSeriesConfig { /** - *The name of the column representing the target variable that you want to predict for - * each item in your dataset. The data type of the target variable must be numerical.
+ *The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
* @public */ TargetAttributeName: string | undefined; /** - *The name of the column indicating a point in time at which the target value of a given - * item is recorded.
+ *The name of the column indicating a point in time at which the target value of a given item is recorded.
* @public */ TimestampAttributeName: string | undefined; /** - *The name of the column that represents the set of item identifiers for which you want to - * predict the target value.
+ *The name of the column that represents the set of item identifiers for which you want to predict the target value.
* @public */ ItemIdentifierAttributeName: string | undefined; /** - *A set of columns names that can be grouped with the item identifier column to create a - * composite key for which a target value is predicted.
+ *A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
* @public */ GroupingAttributeNames?: string[] | undefined; @@ -7242,158 +4256,60 @@ export const FillingType = { export type FillingType = (typeof FillingType)[keyof typeof FillingType]; /** - *Transformations allowed on the dataset. Supported transformations are
- * Filling and Aggregation. Filling specifies how to
- * add values to missing values in the dataset. Aggregation defines how to
- * aggregate data that does not align with forecast frequency.
Transformations allowed on the dataset. Supported transformations are Filling and Aggregation. Filling specifies how to add values to missing values in the dataset. Aggregation defines how to aggregate data that does not align with forecast frequency.
A key value pair defining the filling method for a column, where the key is the column - * name and the value is an object which defines the filling logic. You can specify multiple - * filling methods for a single column.
- *The supported filling methods and their corresponding options are:
- *
- * frontfill: none (Supported only for target
- * column)
- * middlefill: zero, value,
- * median, mean, min, max
- *
- * backfill: zero, value, median,
- * mean, min, max
- *
- * futurefill: zero, value,
- * median, mean, min, max
- *
To set a filling method to a specific value, set the fill parameter to the chosen
- * filling method value (for example "backfill" : "value"), and define the
- * filling value in an additional parameter prefixed with "_value". For example, to set
- * backfill to a value of 2, you must include two parameters:
- * "backfill": "value" and "backfill_value":"2".
A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill: none (Supported only for target column)
middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example "backfill" : "value"), and define the filling value in an additional parameter prefixed with "_value". For example, to set backfill to a value of 2, you must include two parameters: "backfill": "value" and "backfill_value":"2".
A key value pair defining the aggregation method for a column, where the key is the - * column name and the value is the aggregation method.
- *The supported aggregation methods are sum (default), avg,
- * first, min, max.
Aggregation is only supported for the target column.
- *A key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum (default), avg, first, min, max.
Aggregation is only supported for the target column.
The collection of settings used by an AutoML job V2 for the time-series forecasting - * problem type.
+ *The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
* @public */ export interface TimeSeriesForecastingJobConfig { /** - *A URL to the Amazon S3 data source containing additional selected features that
- * complement the target, itemID, timestamp, and grouped columns set in
- * TimeSeriesConfig. When not provided, the AutoML job V2 includes all the
- * columns from the original dataset that are not already declared in
- * TimeSeriesConfig. If provided, the AutoML job V2 only considers these
- * additional columns as a complement to the ones declared in
- * TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown
- * below:
- * \{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown - * below:
- *
- * \{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
- *
Autopilot supports the following data types: numeric, categorical,
- * text, and datetime.
These column keys must not include any column set in
- * TimeSeriesConfig.
A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown below:
\{ "FeatureAttributeNames":["col1", "col2", ...] \}.
You can also specify the data type of the feature (optional) in the format shown below:
\{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ... \} \}
Autopilot supports the following data types: numeric, categorical, text, and datetime.
These column keys must not include any column set in TimeSeriesConfig.
How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; /** - *The frequency of predictions in a forecast.
- *Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H
- * (Hour), and min (Minute). For example, 1D indicates every day and
- * 15min indicates every 15 minutes. The value of a frequency must not overlap
- * with the next larger frequency. For example, you must use a frequency of 1H
- * instead of 60min.
The valid values for each frequency are the following:
- *Minute - 1-59
- *Hour - 1-23
- *Day - 1-6
- *Week - 1-4
- *Month - 1-11
- *Year - 1
- *The frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called - * the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 - * of the time-steps in the dataset.
+ *The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
* @public */ ForecastHorizon: number | undefined; /** - *The quantiles used to train the model for forecasts at a specified quantile. You can
- * specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of
- * 0.01 or higher. Up to five forecast quantiles can be specified. When
- * ForecastQuantiles is not provided, the AutoML job uses the quantiles p10,
- * p50, and p90 as default.
The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
The transformations modifying specific attributes of the time-series, such as filling - * strategies for missing values.
+ *The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
* @public */ Transformations?: TimeSeriesTransformations | undefined; @@ -7405,23 +4321,20 @@ export interface TimeSeriesForecastingJobConfig { TimeSeriesConfig: TimeSeriesConfig | undefined; /** - *The collection of holiday featurization attributes used to incorporate national holiday - * information into your forecasting model.
+ *The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
* @public */ HolidayConfig?: HolidayConfigAttributes[] | undefined; /** - *Stores the configuration information for how model candidates are generated using an - * AutoML job V2.
+ *Stores the configuration information for how model candidates are generated using an AutoML job V2.
* @public */ CandidateGenerationConfig?: CandidateGenerationConfig | undefined; } /** - *A collection of settings specific to the problem type used to configure an AutoML job V2. - * There must be one and only one config of the following type.
+ *A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
* @public */ export type AutoMLProblemTypeConfig = @@ -7437,8 +4350,7 @@ export type AutoMLProblemTypeConfig = */ export namespace AutoMLProblemTypeConfig { /** - *Settings used to configure an AutoML job V2 for the image classification problem - * type.
+ *Settings used to configure an AutoML job V2 for the image classification problem type.
* @public */ export interface ImageClassificationJobConfigMember { @@ -7451,8 +4363,7 @@ export namespace AutoMLProblemTypeConfig { } /** - *Settings used to configure an AutoML job V2 for the text classification problem - * type.
+ *Settings used to configure an AutoML job V2 for the text classification problem type.
* @public */ export interface TextClassificationJobConfigMember { @@ -7465,8 +4376,7 @@ export namespace AutoMLProblemTypeConfig { } /** - *Settings used to configure an AutoML job V2 for the time-series forecasting problem - * type.
+ *Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
* @public */ export interface TimeSeriesForecastingJobConfigMember { @@ -7479,8 +4389,7 @@ export namespace AutoMLProblemTypeConfig { } /** - *Settings used to configure an AutoML job V2 for the tabular problem type (regression, - * classification).
+ *Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
* @public */ export interface TabularJobConfigMember { @@ -7493,13 +4402,7 @@ export namespace AutoMLProblemTypeConfig { } /** - *Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) - * problem type.
- *The text generation models that support fine-tuning in Autopilot are currently accessible - * exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported - * Regions.
- *Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The type of supervised learning problem available for the model candidates of the AutoML - * job V2 (Binary Classification, Multiclass Classification, Regression). For more - * information, see - * SageMaker Autopilot problem types.
+ *The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see SageMaker Autopilot problem types.
* @public */ ProblemType?: ProblemType | undefined; @@ -7660,8 +4560,7 @@ export interface AutoMLResolvedAttributes { AutoMLJobObjective?: AutoMLJobObjective | undefined; /** - *How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; @@ -7718,9 +4617,7 @@ export const AutoMountHomeEFS = { export type AutoMountHomeEFS = (typeof AutoMountHomeEFS)[keyof typeof AutoMountHomeEFS]; /** - *The name and an example value of the hyperparameter that you want to use in Autotune. - * If Automatic model tuning (AMT) determines that your hyperparameter is eligible for - * Autotune, an optimal hyperparameter range is selected for you.
+ *The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
* @public */ export interface AutoParameter { @@ -7738,15 +4635,12 @@ export interface AutoParameter { } /** - *Automatic rollback configuration for handling endpoint deployment failures and - * recovery.
+ *Automatic rollback configuration for handling endpoint deployment failures and recovery.
* @public */ export interface AutoRollbackConfig { /** - *List of CloudWatch alarms in your account that are configured to monitor metrics on an - * endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the - * deployment.
+ *List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
* @public */ Alarms?: Alarm[] | undefined; @@ -7766,43 +4660,7 @@ export const AutotuneMode = { export type AutotuneMode = (typeof AutotuneMode)[keyof typeof AutotuneMode]; /** - *A flag to indicate if you want to use Autotune to automatically find optimal values - * for the following fields:
- *- * ParameterRanges: The names and ranges of parameters that a - * hyperparameter tuning job can optimize.
- *- * ResourceLimits: The maximum resources that can be used for a - * training job. These resources include the maximum number of training jobs, the - * maximum runtime of a tuning job, and the maximum number of training jobs to run - * at the same time.
- *- * TrainingJobEarlyStoppingType: A flag that specifies whether or not - * to use early stopping for training jobs launched by a hyperparameter tuning - * job.
- *- * RetryStrategy: The number of times to retry a training job.
- *- * Strategy: Specifies how hyperparameter tuning chooses the - * combinations of hyperparameter values to use for the training jobs that it - * launches.
- *- * ConvergenceDetected: A flag to indicate that Automatic model tuning - * (AMT) has detected model convergence.
- *A flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on - * the storage volume attached to the ML compute instance that hosts the batch transform job.
- *The KmsKeyId can be any of the following formats:
- *Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
A list of node IDs to be deleted from the specified cluster.
- *For SageMaker HyperPod clusters using the Slurm workload manager, you cannot remove - * instances that are configured as Slurm controller nodes.
- *If you need to delete more than 99 instances, contact Support for assistance.
- *A list of node IDs to be deleted from the specified cluster.
For SageMaker HyperPod clusters using the Slurm workload manager, you cannot remove instances that are configured as Slurm controller nodes.
If you need to delete more than 99 instances, contact Support for assistance.
The error code associated with the error encountered when deleting a node.
- *The code provides information about the specific issue encountered, such as the node not - * being found, the node's status being invalid for deletion, or the node ID being in use by - * another process.
+ *The error code associated with the error encountered when deleting a node.
The code provides information about the specific issue encountered, such as the node not being found, the node's status being invalid for deletion, or the node ID being in use by another process.
* @public */ Code: BatchDeleteClusterNodesErrorCode | undefined; @@ -7979,13 +4801,13 @@ export interface BatchDescribeModelPackageInput { */ export interface BatchDescribeModelPackageError { /** - * + * * @public */ ErrorCode: string | undefined; /** - * + * * @public */ ErrorResponse: string | undefined; @@ -8003,18 +4825,13 @@ export interface InferenceSpecification { Containers: ModelPackageContainerDefinition[] | undefined; /** - *A list of the instance types on which a transformation job can be run or on which an - * endpoint can be deployed.
- *This parameter is required for unversioned models, and optional for versioned - * models.
+ *A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
* @public */ SupportedTransformInstanceTypes?: TransformInstanceType[] | undefined; /** - *A list of the instance types that are used to generate inferences in real-time.
- *This parameter is required for unversioned models, and optional for versioned - * models.
+ *A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
* @public */ SupportedRealtimeInferenceInstanceTypes?: ProductionVariantInstanceType[] | undefined; @@ -8129,8 +4946,7 @@ export interface BatchDescribeModelPackageOutput { ModelPackageSummaries?: RecordA map of the resource and BatchDescribeModelPackageError objects reporting the error - * associated with describing the model package.
+ *A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
* @public */ BatchDescribeModelPackageErrorMap?: RecordWhether the Pipe or File is used as the input mode for
- * transferring data for the monitoring job. Pipe mode is recommended for large
- * datasets. File mode is useful for small files that fit in memory. Defaults to
- * File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key.
- * Defaults to FullyReplicated
- *
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
If specified, monitoring jobs substract this time from the start time. For information - * about using offsets for scheduling monitoring jobs, see Schedule Model - * Quality Monitoring Jobs.
+ *If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
* @public */ StartTimeOffset?: string | undefined; /** - *If specified, monitoring jobs subtract this time from the end time. For information - * about using offsets for scheduling monitoring jobs, see Schedule Model - * Quality Monitoring Jobs.
+ *If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
* @public */ EndTimeOffset?: string | undefined; @@ -8307,15 +5114,12 @@ export interface BatchTransformInput { } /** - *A structure that keeps track of which training jobs launched by your hyperparameter - * tuning job are not improving model performance as evaluated against an objective - * function.
+ *A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
* @public */ export interface BestObjectiveNotImproving { /** - *The number of training jobs that have failed to improve model performance by 1% or - * greater over prior training jobs as evaluated against an objective function.
+ *The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
* @public */ MaxNumberOfTrainingJobsNotImproving?: number | undefined; @@ -8384,36 +5188,18 @@ export const CapacitySizeType = { export type CapacitySizeType = (typeof CapacitySizeType)[keyof typeof CapacitySizeType]; /** - *Specifies the type and size of the endpoint capacity to activate for a blue/green - * deployment, a rolling deployment, or a rollback strategy. You can specify your batches - * as either instance count or the overall percentage or your fleet.
- *For a rollback strategy, if you don't specify the fields in this object, or if you set
- * the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls
- * all traffic back to the blue fleet.
Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don't specify the fields in this object, or if you set the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Specifies the endpoint capacity type.
- *
- * INSTANCE_COUNT: The endpoint activates based on the number of
- * instances.
- * CAPACITY_PERCENT: The endpoint activates based on the specified
- * percentage of capacity.
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity - * percentage.
+ *Defines the capacity size, either as a number of instances or a capacity percentage.
* @public */ Value: number | undefined; @@ -8435,86 +5221,54 @@ export const TrafficRoutingConfigType = { export type TrafficRoutingConfigType = (typeof TrafficRoutingConfigType)[keyof typeof TrafficRoutingConfigType]; /** - *Defines the traffic routing strategy during an endpoint deployment to shift traffic - * from the old fleet to the new fleet.
+ *Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
* @public */ export interface TrafficRoutingConfig { /** - *Traffic routing strategy type.
- *
- * ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single
- * step.
- * CANARY: Endpoint traffic shifts to the new fleet in two steps.
- * The first step is the canary, which is a small portion of the traffic. The
- * second step is the remainder of the traffic.
- * LINEAR: Endpoint traffic shifts to the new fleet in n steps of a
- * configurable size.
Traffic routing strategy type.
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step.
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
The waiting time (in seconds) between incremental steps to turn on traffic on the new - * endpoint fleet.
+ *The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
* @public */ WaitIntervalInSeconds: number | undefined; /** - *Batch size for the first step to turn on traffic on the new endpoint fleet.
- * Value must be less than or equal to 50% of the variant's total instance
- * count.
Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant's total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet.
- * Value must be 10-50% of the variant's total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant's total instance count.
Update policy for a blue/green deployment. If this update policy is specified, SageMaker - * creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips - * traffic to the new fleet according to the specified traffic routing configuration. Only - * one update policy should be used in the deployment configuration. If no update policy is - * specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting - * by default.
+ *Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
* @public */ export interface BlueGreenUpdatePolicy { /** - *Defines the traffic routing strategy to shift traffic from the old fleet to the new - * fleet during an endpoint deployment.
+ *Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
* @public */ TrafficRoutingConfiguration: TrafficRoutingConfig | undefined; /** - *Additional waiting time in seconds after the completion of an endpoint deployment - * before terminating the old endpoint fleet. Default is 0.
+ *Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
* @public */ TerminationWaitInSeconds?: number | undefined; /** - *Maximum execution timeout for the deployment. Note that the timeout value should be
- * larger than the total waiting time specified in TerminationWaitInSeconds
- * and WaitIntervalInSeconds.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds.
The model deployment settings for the SageMaker Canvas application.
- *In order to enable model deployment for Canvas, the SageMaker Domain's or user profile's Amazon Web Services IAM
- * execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also
- * turn on model deployment permissions through the SageMaker Domain's or user profile's settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain's or user profile's Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also turn on model deployment permissions through the SageMaker Domain's or user profile's settings in the SageMaker console.
The Amazon Resource Name (ARN) of the Amazon Web Services IAM role that is assumed for - * running Amazon EMR Serverless jobs in SageMaker Canvas. This role should have the necessary - * permissions to read and write data attached and a trust relationship with - * EMR Serverless.
+ *The Amazon Resource Name (ARN) of the Amazon Web Services IAM role that is assumed for running Amazon EMR Serverless jobs in SageMaker Canvas. This role should have the necessary permissions to read and write data attached and a trust relationship with EMR Serverless.
* @public */ ExecutionRoleArn?: string | undefined; /** - *Describes whether Amazon EMR Serverless job capabilities are enabled or disabled in the SageMaker - * Canvas application.
+ *Describes whether Amazon EMR Serverless job capabilities are enabled or disabled in the SageMaker Canvas application.
* @public */ Status?: FeatureStatus | undefined; } /** - *The generative AI settings for the SageMaker Canvas application.
- *Configure these settings for Canvas users starting chats with generative AI foundation models. - * For more information, see - * Use generative AI with foundation models.
+ *The generative AI settings for the SageMaker Canvas application.
Configure these settings for Canvas users starting chats with generative AI foundation models. For more information, see Use generative AI with foundation models.
* @public */ export interface GenerativeAiSettings { /** - *The ARN of an Amazon Web Services IAM role that allows fine-tuning of large language models (LLMs) in
- * Amazon Bedrock. The IAM role should have Amazon S3 read and write permissions, as well as a trust relationship that
- * establishes bedrock.amazonaws.com as a service principal.
The ARN of an Amazon Web Services IAM role that allows fine-tuning of large language models (LLMs) in Amazon Bedrock. The IAM role should have Amazon S3 read and write permissions, as well as a trust relationship that establishes bedrock.amazonaws.com as a service principal.
The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external - * data source, such as Snowflake.
+ *The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
* @public */ export interface IdentityProviderOAuthSetting { @@ -8686,29 +5425,25 @@ export interface IdentityProviderOAuthSetting { DataSourceName?: DataSourceName | undefined; /** - *Describes whether OAuth for a data source is enabled or disabled in the Canvas - * application.
+ *Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
* @public */ Status?: FeatureStatus | undefined; /** - *The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your - * identity provider, such as the client ID and secret, authorization URL, and token URL.
+ *The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
* @public */ SecretArn?: string | undefined; } /** - *The Amazon SageMaker Canvas application setting where you configure - * document querying.
+ *The Amazon SageMaker Canvas application setting where you configure document querying.
* @public */ export interface KendraSettings { /** - *Describes whether the document querying feature is enabled - * or disabled in the Canvas application.
+ *Describes whether the document querying feature is enabled or disabled in the Canvas application.
* @public */ Status?: FeatureStatus | undefined; @@ -8720,16 +5455,13 @@ export interface KendraSettings { */ export interface ModelRegisterSettings { /** - *Describes whether the integration to the model registry is enabled or disabled in the - * Canvas application.
+ *Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
* @public */ Status?: FeatureStatus | undefined; /** - *The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions - * created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services - * account in which SageMaker model registry is set up.
+ *The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
* @public */ CrossAccountModelRegisterRoleArn?: string | undefined; @@ -8741,21 +5473,13 @@ export interface ModelRegisterSettings { */ export interface TimeSeriesForecastingSettings { /** - *Describes whether time series forecasting is enabled or disabled in the Canvas - * application.
+ *Describes whether time series forecasting is enabled or disabled in the Canvas application.
* @public */ Status?: FeatureStatus | undefined; /** - *The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default,
- * Canvas uses the execution role specified in the UserProfile that launches the
- * Canvas application. If an execution role is not specified in the UserProfile,
- * Canvas uses the execution role specified in the Domain that owns the
- * UserProfile. To allow time series forecasting, this IAM role should have the
- * AmazonSageMakerCanvasForecastAccess policy attached and
- * forecast.amazonaws.com added in the trust relationship as a service
- * principal.
The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile that launches the Canvas application. If an execution role is not specified in the UserProfile, Canvas uses the execution role specified in the Domain that owns the UserProfile. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com added in the trust relationship as a service principal.
The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts - * existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users - * must log out and log back in to apply the new location.
+ *The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
* @public */ S3ArtifactPath?: string | undefined; @@ -8850,9 +5572,7 @@ export const NodeUnavailabilityType = { export type NodeUnavailabilityType = (typeof NodeUnavailabilityType)[keyof typeof NodeUnavailabilityType]; /** - *The configuration of the size measurements of the AMI update. Using this - * configuration, you can specify whether SageMaker should update your instance group - * by an amount or percentage of instances.
+ *The configuration of the size measurements of the AMI update. Using this configuration, you can specify whether SageMaker should update your instance group by an amount or percentage of instances.
* @public */ export interface CapacitySizeConfig { @@ -8870,21 +5590,18 @@ export interface CapacitySizeConfig { } /** - *Configuration specifying how to treat different headers. If no headers are specified - * Amazon SageMaker AI will by default base64 encode when capturing the data.
+ *Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker AI will by default base64 encode when capturing the data.
* @public */ export interface CaptureContentTypeHeader { /** - *The list of all content type headers that Amazon SageMaker AI will treat as CSV and - * capture accordingly.
+ *The list of all content type headers that Amazon SageMaker AI will treat as CSV and capture accordingly.
* @public */ CsvContentTypes?: string[] | undefined; /** - *The list of all content type headers that SageMaker AI will treat as JSON and - * capture accordingly.
+ *The list of all content type headers that SageMaker AI will treat as JSON and capture accordingly.
* @public */ JsonContentTypes?: string[] | undefined; @@ -8961,9 +5678,7 @@ export interface CategoricalParameterRange { Name: string | undefined; /** - *A list of the categories - * for - * the hyperparameter.
+ *A list of the categories for the hyperparameter.
* @public */ Values: string[] | undefined; @@ -9017,42 +5732,32 @@ export interface ChannelSpecification { SupportedCompressionTypes?: CompressionType[] | undefined; /** - *The allowed input mode, either FILE or PIPE.
- *In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon - * Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This - * is the most commonly used input mode.
- *In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm - * without using the EBS volume.
+ *The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
* @public */ SupportedInputModes: TrainingInputMode[] | undefined; } /** - *Contains information about the output location for managed spot training checkpoint - * data.
+ *Contains information about the output location for managed spot training checkpoint data.
* @public */ export interface CheckpointConfig { /** - *Identifies the S3 path where you want SageMaker to store checkpoints. For example,
- * s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix.
(Optional) The local directory where checkpoints are written. The default directory is
- * /opt/ml/checkpoints/.
(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/.
The container for the metadata for the ClarifyCheck step. For more information, see - * the topic on ClarifyCheck step in the Amazon SageMaker Developer - * Guide.
+ *The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
* @public */ export interface ClarifyCheckStepMetadata { @@ -9087,27 +5792,19 @@ export interface ClarifyCheckStepMetadata { ViolationReport?: string | undefined; /** - *The Amazon Resource Name (ARN) of the check processing job that was run by this step's - * execution.
+ *The Amazon Resource Name (ARN) of the check processing job that was run by this step's execution.
* @public */ CheckJobArn?: string | undefined; /** - *This flag indicates if the drift check against the previous baseline will be skipped
- * or not. If it is set to False, the previous baseline of the configured
- * check type must be available.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step
- * properties BaselineUsedForDriftCheckConstraints and
- * BaselineUsedForDriftCheckStatistics. If it is set to
- * False, the previous baseline of the configured check type must also be
- * available. These can be accessed through the
- * BaselineUsedForDriftCheckConstraints property.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints property.
Provides the JMESPath expression to extract the features from a model container input
- * in JSON Lines format. For example, if FeaturesAttribute is the JMESPath
- * expression 'myfeatures', it extracts a list of features
- * [1,2,3] from request data '\{"myfeatures":[1,2,3]\}'.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '\{"myfeatures":[1,2,3]\}'.
A template string used to format a JSON record into an acceptable model container
- * input. For example, a ContentTemplate string
- * '\{"myfeatures":$features\}' will format a list of features
- * [1,2,3] into the record string '\{"myfeatures":[1,2,3]\}'.
- * Required only when the model container input is in JSON Lines format.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '\{"myfeatures":$features\}' will format a list of features [1,2,3] into the record string '\{"myfeatures":[1,2,3]\}'. Required only when the model container input is in JSON Lines format.
The maximum number of records in a request that the model container can process when
- * querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be
- * made on, for example, a single line in CSV data. If MaxRecordCount is
- * 1, the model container expects one record per request. A value of 2 or
- * greater means that the model expects batch requests, which can reduce overhead and speed
- * up the inferencing process. If this parameter is not provided, the explainer will tune
- * the record count per request according to the model container's capacity at
- * runtime.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
The maximum payload size (MB) allowed of a request from the explainer to the model
- * container. Defaults to 6 MB.
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
A zero-based index used to extract a probability value (score) or list from model - * container output in CSV format. If this value is not provided, the entire model - * container output will be treated as a probability value (score) or list.
- *
- * Example for a single class model: If the model
- * container output consists of a string-formatted prediction label followed by its
- * probability: '1,0.6', set ProbabilityIndex to 1
- * to select the probability value 0.6.
- * Example for a multiclass model: If the model
- * container output consists of a string-formatted prediction label followed by its
- * probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set
- * ProbabilityIndex to 1 to select the probability values
- * [0.1,0.6,0.3].
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
A zero-based index used to extract a label header or list of label headers from model - * container output in CSV format.
- *
- * Example for a multiclass model: If the model
- * container output consists of label headers followed by probabilities:
- * '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set
- * LabelIndex to 0 to select the label headers
- * ['cat','dog','fish'].
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
A JMESPath expression used to extract the probability (or score) from the model - * container output if the model container is in JSON Lines format.
- *
- * Example: If the model container output of a single
- * request is '\{"predicted_label":1,"probability":0.6\}', then set
- * ProbabilityAttribute to 'probability'.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is '\{"predicted_label":1,"probability":0.6\}', then set ProbabilityAttribute to 'probability'.
A JMESPath expression used to locate the list of label headers in the model container - * output.
- *
- * Example: If the model container output of a batch
- * request is '\{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]\}',
- * then set LabelAttribute to 'labels' to extract the list of
- * label headers ["cat","dog","fish"]
- *
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is '\{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]\}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"]
For multiclass classification problems, the label headers are the names of the
- * classes. Otherwise, the label header is the name of the predicted label. These are used
- * to help readability for the output of the InvokeEndpoint API. See the
- * response section under Invoke the endpoint
- * in the Developer Guide for more information. If there are no label headers in the model
- * container output, provide them manually using this parameter.
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
The names of the features. If provided, these are included in the endpoint response
- * payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint
- * in the Developer Guide for more information.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP
- * explainability. If provided, FeatureTypes must have at least one
- * 'text' string (for example, ['text']). If
- * FeatureTypes is not provided, the explainer infers the feature types
- * based on the baseline data. The feature types are included in the endpoint response
- * payload. For additional information see the response section under Invoke the endpoint
- * in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
The configuration for the SHAP - * baseline (also called the background or reference dataset) of the Kernal - * SHAP algorithm.
- *The number of records in the baseline data determines the size of the - * synthetic dataset, which has an impact on latency of explainability - * requests. For more information, see the Synthetic - * data of Configure and create an endpoint.
- *
- * ShapBaseline and ShapBaselineUri are mutually
- * exclusive parameters. One or the either is required to configure a SHAP
- * baseline.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline and ShapBaselineUri are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The MIME type of the baseline data. Choose from 'text/csv' or
- * 'application/jsonlines'. Defaults to 'text/csv'.
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
The inline SHAP baseline data in string format. ShapBaseline can have one
- * or multiple records to be used as the baseline dataset. The format of the SHAP baseline
- * file should be the same format as the training dataset. For example, if the training
- * dataset is in CSV format and each record contains four features, and all features are
- * numerical, then the format of the baseline data should also share these characteristics.
- * For natural language processing (NLP) of text columns, the baseline value should be the
- * value used to replace the unit of text specified by the Granularity of the
- * TextConfig parameter. The size limit for ShapBasline is 4
- * KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB
- * of baseline data.
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is
- * stored. The format of the SHAP baseline file should be the same format as the format of
- * the training dataset. For example, if the training dataset is in CSV format, and each
- * record in the training dataset has four features, and all features are numerical, then
- * the baseline file should also have this same format. Each record should contain only the
- * features. If you are using a virtual private cloud (VPC), the
- * ShapBaselineUri should be accessible to the VPC. For more information
- * about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to
- * Resources in your Amazon Virtual Private Cloud.
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
A parameter used to configure the SageMaker Clarify explainer to treat text features as text so - * that explanations are provided for individual units of text. Required only for natural - * language processing (NLP) explainability.
+ *A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
* @public */ export interface ClarifyTextConfig { /** - *Specifies the language of the text features in ISO 639-1 or - * ISO 639-3 code of a - * supported language.
- *For a mix of multiple languages, use code 'xx'.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code 'xx'.
The unit of granularity for the analysis of text features. For example, if the unit is
- * 'token', then each token (like a word in English) of the text is
- * treated as a feature. SHAP values are computed for each unit/feature.
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
The number of samples to be used for analysis by the Kernal SHAP algorithm.
- *The number of samples determines the size of the synthetic dataset, which has an - * impact on latency of explainability requests. For more information, see the - * Synthetic data of Configure and create an endpoint.
- *The number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds - * units (false) for model predictions. Defaults to false.
+ *A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
* @public */ UseLogit?: boolean | undefined; /** - *The starting value used to initialize the random number generator in the explainer. - * Provide a value for this parameter to obtain a deterministic SHAP result.
+ *The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
* @public */ Seed?: number | undefined; /** - *A parameter that indicates if text features are treated as text and explanations are - * provided for individual units of text. Required for natural language processing (NLP) - * explainability only.
+ *A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
* @public */ TextConfig?: ClarifyTextConfig | undefined; @@ -9485,10 +6068,7 @@ export interface ClarifyShapConfig { */ export interface ClarifyExplainerConfig { /** - *A JMESPath boolean expression used to filter which records to explain. Explanations
- * are activated by default. See
- * EnableExplanations
- * for additional information.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations for additional information.
Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS) - * volume to each instance of the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
+ *Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS) volume to each instance of the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
* @public */ export interface ClusterEbsVolumeConfig { /** - *The size in gigabytes (GB) of the additional EBS volume to be attached to the instances
- * in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each
- * instance within the SageMaker HyperPod cluster instance group and mounted to
- * /opt/sagemaker.
The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to /opt/sagemaker.
Defines the configuration for attaching additional storage to the instances in the - * SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
+ *Defines the configuration for attaching additional storage to the instances in the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
* @public */ export type ClusterInstanceStorageConfig = @@ -9536,10 +6111,7 @@ export type ClusterInstanceStorageConfig = */ export namespace ClusterInstanceStorageConfig { /** - *Defines the configuration for attaching additional Amazon Elastic Block Store (EBS)
- * volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is
- * attached to each instance within the SageMaker HyperPod cluster instance group and mounted to
- * /opt/sagemaker.
Defines the configuration for attaching additional Amazon Elastic Block Store (EBS) volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to /opt/sagemaker.
An Amazon S3 bucket path where your lifecycle scripts are stored.
- *Make sure that the S3 bucket path starts with s3://sagemaker-. The
- * IAM role for SageMaker HyperPod has the managed
- * AmazonSageMakerClusterInstanceRolePolicy
- * attached, which
- * allows access to S3 buckets with the specific prefix sagemaker-.
An Amazon S3 bucket path where your lifecycle scripts are stored.
Make sure that the S3 bucket path starts with s3://sagemaker-. The IAM role for SageMaker HyperPod has the managed AmazonSageMakerClusterInstanceRolePolicy attached, which allows access to S3 buckets with the specific prefix sagemaker-.
The file name of the entrypoint script of lifecycle scripts under
- * SourceS3Uri. This entrypoint script runs during cluster creation.
The file name of the entrypoint script of lifecycle scripts under SourceS3Uri. This entrypoint script runs during cluster creation.
The number of instances that are currently in the instance group of a SageMaker HyperPod - * cluster.
+ *The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
* @public */ CurrentCount?: number | undefined; /** - *The number of instances you specified to add to the instance group of a SageMaker HyperPod - * cluster.
+ *The number of instances you specified to add to the instance group of a SageMaker HyperPod cluster.
* @public */ TargetCount?: number | undefined; @@ -9852,84 +6414,43 @@ export interface ClusterInstanceGroupDetails { ExecutionRole?: string | undefined; /** - *The number you specified to TreadsPerCore in CreateCluster for
- * enabling or disabling multithreading. For instance types that support multithreading, you
- * can specify 1 for disabling multithreading and 2 for enabling multithreading. For more
- * information, see the reference table of CPU cores and
- * threads per CPU core per instance type in the Amazon Elastic Compute Cloud User
- * Guide.
The number you specified to TreadsPerCore in CreateCluster for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
The additional storage configurations for the instances in the SageMaker HyperPod cluster instance - * group.
+ *The additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
* @public */ InstanceStorageConfigs?: ClusterInstanceStorageConfig[] | undefined; /** - *A flag indicating whether deep health checks should be performed when the cluster - * instance group is created or updated.
+ *A flag indicating whether deep health checks should be performed when the cluster instance group is created or updated.
* @public */ OnStartDeepHealthChecks?: DeepHealthCheckType[] | undefined; /** - *The current status of the cluster instance group.
- *
- * InService: The instance group is active and healthy.
- * Creating: The instance group is being provisioned.
- * Updating: The instance group is being updated.
- * Failed: The instance group has failed to provision or is no longer
- * healthy.
- * Degraded: The instance group is degraded, meaning that some instances
- * have failed to provision or are no longer healthy.
- * Deleting: The instance group is being deleted.
The current status of the cluster instance group.
InService: The instance group is active and healthy.
Creating: The instance group is being provisioned.
Updating: The instance group is being updated.
Failed: The instance group has failed to provision or is no longer healthy.
Degraded: The instance group is degraded, meaning that some instances have failed to provision or are no longer healthy.
Deleting: The instance group is being deleted.
The Amazon Resource Name (ARN); of the training plan associated with this cluster instance group.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
The Amazon Resource Name (ARN); of the training plan associated with this cluster instance group.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The current status of the training plan associated with this cluster instance - * group.
+ *The current status of the training plan associated with this cluster instance group.
* @public */ TrainingPlanStatus?: string | undefined; /** - *The customized Amazon VPC configuration at the instance group level that - * overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
+ *The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
* @public */ OverrideVpcConfig?: VpcConfig | undefined; @@ -9947,8 +6468,7 @@ export interface ClusterInstanceGroupDetails { */ export interface ClusterInstanceGroupSpecification { /** - *Specifies the number of instances to add to the instance group of a SageMaker HyperPod - * cluster.
+ *Specifies the number of instances to add to the instance group of a SageMaker HyperPod cluster.
* @public */ InstanceCount: number | undefined; @@ -9978,75 +6498,31 @@ export interface ClusterInstanceGroupSpecification { ExecutionRole: string | undefined; /** - *Specifies the value for Threads per core. For instance
- * types that support multithreading, you can specify 1 for disabling
- * multithreading and 2 for enabling multithreading. For instance types that
- * doesn't support multithreading, specify 1. For more information, see the
- * reference table of CPU cores and
- * threads per CPU core per instance type in the Amazon Elastic Compute Cloud User
- * Guide.
Specifies the value for Threads per core. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For instance types that doesn't support multithreading, specify 1. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
Specifies the additional storage configurations for the instances in the SageMaker HyperPod cluster - * instance group.
+ *Specifies the additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
* @public */ InstanceStorageConfigs?: ClusterInstanceStorageConfig[] | undefined; /** - *A flag indicating whether deep health checks should be performed when the cluster - * instance group is created or updated.
+ *A flag indicating whether deep health checks should be performed when the cluster instance group is created or updated.
* @public */ OnStartDeepHealthChecks?: DeepHealthCheckType[] | undefined; /** - *The Amazon Resource Name (ARN); of the training plan to use for this cluster instance group.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
The Amazon Resource Name (ARN); of the training plan to use for this cluster instance group.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
To configure multi-AZ deployments, customize the Amazon VPC configuration at the - * instance group level. You can specify different subnets and security groups across - * different AZs in the instance group specification to override a SageMaker HyperPod cluster's default - * Amazon VPC configuration. For more information about deploying a cluster in - * multiple AZs, see Setting up SageMaker HyperPod clusters across multiple AZs.
- *When your Amazon VPC and subnets support IPv6, network communications differ - * based on the cluster orchestration platform:
- *Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and - * IPv4 addresses, allowing immediate IPv6 network communications.
- *In Amazon EKS-orchestrated clusters, nodes receive dual-stack - * addressing, but pods can only use IPv6 when the Amazon EKS cluster is - * explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
- *Additional resources for IPv6 configuration:
- *For information about adding IPv6 support to your VPC, see to IPv6 - * Support for VPC.
- *For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
- *To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
- *To configure multi-AZ deployments, customize the Amazon VPC configuration at the instance group level. You can specify different subnets and security groups across different AZs in the instance group specification to override a SageMaker HyperPod cluster's default Amazon VPC configuration. For more information about deploying a cluster in multiple AZs, see Setting up SageMaker HyperPod clusters across multiple AZs.
When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:
Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.
In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
Additional resources for IPv6 configuration:
For information about adding IPv6 support to your VPC, see to IPv6 Support for VPC.
For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
Specifies the placement details for the node in the SageMaker HyperPod cluster, including the - * Availability Zone and the unique identifier (ID) of the Availability Zone.
+ *Specifies the placement details for the node in the SageMaker HyperPod cluster, including the Availability Zone and the unique identifier (ID) of the Availability Zone.
* @public */ export interface ClusterInstancePlacement { @@ -10071,8 +6546,7 @@ export interface ClusterInstancePlacement { AvailabilityZone?: string | undefined; /** - *The unique identifier (ID) of the Availability Zone where the node in the SageMaker HyperPod cluster - * is launched.
+ *The unique identifier (ID) of the Availability Zone where the node in the SageMaker HyperPod cluster is launched.
* @public */ AvailabilityZoneId?: string | undefined; @@ -10115,8 +6589,7 @@ export interface ClusterInstanceStatusDetails { } /** - *Details of an instance (also called a node interchangeably) in a - * SageMaker HyperPod cluster.
+ *Details of an instance (also called a node interchangeably) in a SageMaker HyperPod cluster.
* @public */ export interface ClusterNodeDetails { @@ -10163,22 +6636,19 @@ export interface ClusterNodeDetails { LifeCycleConfig?: ClusterLifeCycleConfig | undefined; /** - *The customized Amazon VPC configuration at the instance group level that - * overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
+ *The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
* @public */ OverrideVpcConfig?: VpcConfig | undefined; /** - *The number of threads per CPU core you specified under
- * CreateCluster.
The number of threads per CPU core you specified under CreateCluster.
The configurations of additional storage specified to the instance group where the - * instance (node) is launched.
+ *The configurations of additional storage specified to the instance group where the instance (node) is launched.
* @public */ InstanceStorageConfigs?: ClusterInstanceStorageConfig[] | undefined; @@ -10190,9 +6660,7 @@ export interface ClusterNodeDetails { PrivatePrimaryIp?: string | undefined; /** - *The private primary IPv6 address of the SageMaker HyperPod cluster node when configured with an - * Amazon VPC that supports IPv6 and includes subnets with IPv6 addressing enabled - * in either the cluster Amazon VPC configuration or the instance group Amazon VPC configuration.
+ *The private primary IPv6 address of the SageMaker HyperPod cluster node when configured with an Amazon VPC that supports IPv6 and includes subnets with IPv6 addressing enabled in either the cluster Amazon VPC configuration or the instance group Amazon VPC configuration.
* @public */ PrivatePrimaryIpv6?: string | undefined; @@ -10225,8 +6693,7 @@ export const ClusterNodeRecovery = { export type ClusterNodeRecovery = (typeof ClusterNodeRecovery)[keyof typeof ClusterNodeRecovery]; /** - *Lists a summary of the properties of an instance (also called a - * node interchangeably) of a SageMaker HyperPod cluster.
+ *Lists a summary of the properties of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
* @public */ export interface ClusterNodeSummary { @@ -10268,14 +6735,12 @@ export interface ClusterNodeSummary { } /** - *The configuration settings for the Amazon EKS cluster used as the orchestrator for the - * SageMaker HyperPod cluster.
+ *The configuration settings for the Amazon EKS cluster used as the orchestrator for the SageMaker HyperPod cluster.
* @public */ export interface ClusterOrchestratorEksConfig { /** - *The Amazon Resource Name (ARN) of the Amazon EKS cluster associated with the SageMaker HyperPod - * cluster.
+ *The Amazon Resource Name (ARN) of the Amazon EKS cluster associated with the SageMaker HyperPod cluster.
* @public */ ClusterArn: string | undefined; @@ -10434,20 +6899,14 @@ export interface ClusterSummary { ClusterStatus: ClusterStatus | undefined; /** - *A list of Amazon Resource Names (ARNs) of the training plans associated with this - * cluster.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
A list of Amazon Resource Names (ARNs) of the training plans associated with this cluster.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
A custom SageMaker AI image. For more information, see - * Bring your own SageMaker AI image.
+ *A custom SageMaker AI image. For more information, see Bring your own SageMaker AI image.
* @public */ export interface CustomImage { @@ -10471,18 +6930,12 @@ export interface CustomImage { } /** - *The Code Editor application settings.
- *For more information about Code Editor, see Get started with Code - * Editor in Amazon SageMaker.
+ *The Code Editor application settings.
For more information about Code Editor, see Get started with Code Editor in Amazon SageMaker.
* @public */ export interface CodeEditorAppSettings { /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The Amazon Resource Name (ARN) of the Code Editor application - * lifecycle configuration.
+ *The Amazon Resource Name (ARN) of the Code Editor application lifecycle configuration.
* @public */ LifecycleConfigArns?: string[] | undefined; /** - *Settings that are used to configure and manage the lifecycle of CodeEditor - * applications.
+ *Settings that are used to configure and manage the lifecycle of CodeEditor applications.
* @public */ AppLifecycleManagement?: AppLifecycleManagement | undefined; /** - *The lifecycle configuration that runs before the default lifecycle configuration. It can - * override changes made in the default lifecycle configuration.
+ *The lifecycle configuration that runs before the default lifecycle configuration. It can override changes made in the default lifecycle configuration.
* @public */ BuiltInLifecycleConfigArn?: string | undefined; } /** - *A Git repository that SageMaker AI automatically displays to users for cloning in the - * JupyterServer application.
+ *A Git repository that SageMaker AI automatically displays to users for cloning in the JupyterServer application.
* @public */ export interface CodeRepository { @@ -10558,8 +7007,7 @@ export const CodeRepositorySortOrder = { export type CodeRepositorySortOrder = (typeof CodeRepositorySortOrder)[keyof typeof CodeRepositorySortOrder]; /** - *Specifies configuration details for a Git repository in your Amazon Web Services - * account.
+ *Specifies configuration details for a Git repository in your Amazon Web Services account.
* @public */ export interface GitConfig { @@ -10576,13 +7024,7 @@ export interface GitConfig { Branch?: string | undefined; /** - *The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that
- * contains the credentials used to access the git repository. The secret must have a
- * staging label of AWSCURRENT and must be in the following format:
- * \{"username": UserName, "password":
- * Password\}
- *
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
\{"username": UserName, "password": Password\}
Configuration details for the Git repository, including the URL where it is located - * and the ARN of the Amazon Web Services Secrets Manager secret that contains the - * credentials used to access the repository.
+ *Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
* @public */ GitConfig?: GitConfig | undefined; } /** - *Use this parameter to configure your Amazon Cognito workforce. - * A single Cognito workforce is created using and corresponds to a single - * - * Amazon Cognito user pool.
+ *Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
* @public */ export interface CognitoConfig { /** - *A - * user pool is a user directory in Amazon Cognito. - * With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. - * Your users can also sign in through social identity providers like - * Google, Facebook, Amazon, or Apple, and through SAML identity providers.
+ *A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
* @public */ UserPool: string | undefined; @@ -10652,14 +7085,12 @@ export interface CognitoConfig { } /** - *Identifies a Amazon Cognito user group. A user group can be used in on or more work - * teams.
+ *Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
* @public */ export interface CognitoMemberDefinition { /** - *An identifier for a user pool. The user pool must be in the same region as the service - * that you are calling.
+ *An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
* @public */ UserPool: string | undefined; @@ -10671,8 +7102,7 @@ export interface CognitoMemberDefinition { UserGroup: string | undefined; /** - *An identifier for an application client. You must create the app client ID using - * Amazon Cognito.
+ *An identifier for an application client. You must create the app client ID using Amazon Cognito.
* @public */ ClientId: string | undefined; @@ -10701,13 +7131,7 @@ export type CollectionConfig = CollectionConfig.VectorConfigMember | CollectionC */ export namespace CollectionConfig { /** - *Configuration for your vector collection type.
- *
- * Dimension: The number of elements in your vector.
Configuration for your vector collection type.
Dimension: The number of elements in your vector.
Parameter values for the tensor collection. The allowed parameters are
- * "name", "include_regex", "reduction_config",
- * "save_config", "tensor_names", and
- * "save_histogram".
Parameter values for the tensor collection. The allowed parameters are "name", "include_regex", "reduction_config", "save_config", "tensor_names", and "save_histogram".
The type of device that the model will run on after the compilation job has - * completed.
+ *The type of device that the model will run on after the compilation job has completed.
* @public */ CompilationTargetDevice?: TargetDevice | undefined; /** - *The type of OS that the model will run on after the compilation job has - * completed.
+ *The type of OS that the model will run on after the compilation job has completed.
* @public */ CompilationTargetPlatformOs?: TargetPlatformOs | undefined; /** - *The type of architecture that the model will run on after the compilation job has - * completed.
+ *The type of architecture that the model will run on after the compilation job has completed.
* @public */ CompilationTargetPlatformArch?: TargetPlatformArch | undefined; /** - *The type of accelerator that the model will run on after the compilation job has - * completed.
+ *The type of accelerator that the model will run on after the compilation job has completed.
* @public */ CompilationTargetPlatformAccelerator?: TargetPlatformAccelerator | undefined; @@ -10986,8 +7403,7 @@ export interface ComputeQuotaResourceConfig { InstanceType: ClusterInstanceType | undefined; /** - *The number of instances to add to the instance group of a SageMaker HyperPod - * cluster.
+ *The number of instances to add to the instance group of a SageMaker HyperPod cluster.
* @public */ Count: number | undefined; @@ -11028,41 +7444,20 @@ export type ResourceSharingStrategy = (typeof ResourceSharingStrategy)[keyof typ */ export interface ResourceSharingConfig { /** - *The strategy of how idle compute is shared within the cluster. The following are the - * options of strategies.
- *
- * DontLend: entities do not lend idle compute.
- * Lend: entities can lend idle compute to entities that can
- * borrow.
- * LendandBorrow: entities can lend idle compute and borrow idle compute
- * from other entities.
Default is LendandBorrow.
The strategy of how idle compute is shared within the cluster. The following are the options of strategies.
DontLend: entities do not lend idle compute.
Lend: entities can lend idle compute to entities that can borrow.
LendandBorrow: entities can lend idle compute and borrow idle compute from other entities.
Default is LendandBorrow.
The limit on how much idle compute can be borrowed.The values can be 1 - 500 percent of - * idle compute that the team is allowed to borrow.
- *Default is 50.
The limit on how much idle compute can be borrowed.The values can be 1 - 500 percent of idle compute that the team is allowed to borrow.
Default is 50.
Configuration of the compute allocation definition for an entity. This includes the - * resource sharing option and the setting to preempt low priority tasks.
+ *Configuration of the compute allocation definition for an entity. This includes the resource sharing option and the setting to preempt low priority tasks.
* @public */ export interface ComputeQuotaConfig { @@ -11073,17 +7468,13 @@ export interface ComputeQuotaConfig { ComputeQuotaResources?: ComputeQuotaResourceConfig[] | undefined; /** - *Resource sharing configuration. This defines how an entity can lend and borrow idle - * compute with other entities within the cluster.
+ *Resource sharing configuration. This defines how an entity can lend and borrow idle compute with other entities within the cluster.
* @public */ ResourceSharingConfig?: ResourceSharingConfig | undefined; /** - *Allows workloads from within an entity to preempt same-team workloads. When set to
- * LowerPriority, the entity's lower priority tasks are preempted by their own
- * higher priority tasks.
Default is LowerPriority.
Allows workloads from within an entity to preempt same-team workloads. When set to LowerPriority, the entity's lower priority tasks are preempted by their own higher priority tasks.
Default is LowerPriority.
Assigned entity fair-share weight. Idle compute will be shared across entities based on
- * these assigned weights. This weight is only used when FairShare is
- * enabled.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the - * default.
+ *Assigned entity fair-share weight. Idle compute will be shared across entities based on these assigned weights. This weight is only used when FairShare is enabled.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the default.
* @public */ FairShareWeight?: number | undefined; @@ -11153,8 +7540,7 @@ export interface ComputeQuotaSummary { ClusterArn?: string | undefined; /** - *Configuration of the compute allocation definition. This includes the resource sharing - * option, and the setting to preempt low priority tasks.
+ *Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
* @public */ ComputeQuotaConfig?: ComputeQuotaConfig | undefined; @@ -11166,9 +7552,7 @@ export interface ComputeQuotaSummary { ComputeQuotaTarget: ComputeQuotaTarget | undefined; /** - *The state of the compute allocation being described. Use to enable or disable compute - * allocation.
- *Default is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
There was a conflict when you attempted to modify a SageMaker entity such as an
- * Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
Specifies an authentication configuration for the private docker registry where your
- * model image is hosted. Specify a value for this property only if you specified
- * Vpc as the value for the RepositoryAccessMode field of the
- * ImageConfig object that you passed to a call to
- * CreateModel and the private Docker registry where the model image is
- * hosted requires authentication.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the ImageConfig object that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides - * credentials to authenticate to the private Docker registry where your model image is - * hosted. For information about how to create an Amazon Web Services Lambda function, see - * Create a Lambda function - * with the console in the Amazon Web Services Lambda Developer - * Guide.
+ *The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
* @public */ RepositoryCredentialsProviderArn: string | undefined; } /** - *Specifies whether the model container is in Amazon ECR or a private Docker registry - * accessible from your Amazon Virtual Private Cloud (VPC).
+ *Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
* @public */ export interface ImageConfig { /** - *Set this to one of the following values:
- *
- * Platform - The model image is hosted in Amazon ECR.
- * Vpc - The model image is hosted in a private Docker registry in
- * your VPC.
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
(Optional) Specifies an authentication configuration for the private docker registry
- * where your model image is hosted. Specify a value for this property only if you
- * specified Vpc as the value for the RepositoryAccessMode field,
- * and the private Docker registry where the model image is hosted requires
- * authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints
- * cache models so that a model does not have to be loaded into memory each time it is
- * invoked. Some use cases do not benefit from model caching. For example, if an endpoint
- * hosts a large number of models that are each invoked infrequently, the endpoint might
- * perform better if you disable model caching. To disable model caching, set the value of
- * this parameter to Disabled.
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
This parameter is ignored for models that contain only a
- * PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of
- * the parameter uniquely identifies the container for the purposes of logging and metrics.
- * For information, see Use Logs and Metrics
- * to Monitor an Inference Pipeline. If you don't specify a value for this
- * parameter for a ContainerDefinition that is part of an inference pipeline,
- * a unique name is automatically assigned based on the position of the
- * ContainerDefinition in the pipeline. If you specify a value for the
- * ContainerHostName for any ContainerDefinition that is part
- * of an inference pipeline, you must specify a value for the
- * ContainerHostName parameter of every ContainerDefinition
- * in that pipeline.
This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a
- * Docker registry that is accessible from the same VPC that you configure for your
- * endpoint. If you are using your own custom algorithm instead of an algorithm provided by
- * SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both
- * registry/repository[:tag] and registry/repository[@digest]
- * image path formats. For more information, see Using Your Own Algorithms with
- * Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container - * in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are - * creating.
- *The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
Specifies whether the model container is in Amazon ECR or a private Docker registry - * accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a - * private Docker registry, see Use a - * Private Docker Registry for Real-Time Inference Containers.
- *The model artifacts in an Amazon S3 bucket and the Docker image for inference container - * in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are - * creating.
- *Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The S3 path where the model artifacts, which result from model training, are stored. - * This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 - * path is required for SageMaker built-in algorithms, but not if you use your own algorithms. - * For more information on built-in algorithms, see Common - * Parameters.
- *The model artifacts must be in an S3 bucket that is in the same region as the - * model or endpoint you are creating.
- *If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token - * Service to download model artifacts from the S3 path you provide. Amazon Web Services STS - * is activated in your Amazon Web Services account by default. If you previously - * deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and - * Deactivating Amazon Web Services STS in an Amazon Web Services Region in the - * Amazon Web Services Identity and Access Management User - * Guide.
- *If you use a built-in algorithm to create a model, SageMaker requires that you provide
- * a S3 path to the model artifacts in ModelDataUrl.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl.
Specifies the location of ML model data to deploy.
- *Currently you cannot use ModelDataSource in conjunction with SageMaker
- * batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker
- * Marketplace.
Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
The environment variables to set in the Docker container. Don't include any - * sensitive data in your environment variables.
- *The maximum length of each key and value in the Environment map is
- * 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If
- * you pass multiple containers to a CreateModel request, then the maximum
- * length of all of their maps, combined, is also 32 KB.
The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables.
The maximum length of each key and value in the Environment map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a CreateModel request, then the maximum length of all of their maps, combined, is also 32 KB.
The name or Amazon Resource Name (ARN) of the model package to use to create the - * model.
+ *The name or Amazon Resource Name (ARN) of the model package to use to create the model.
* @public */ ModelPackageName?: string | undefined; @@ -269,8 +208,7 @@ export interface ContextSource { } /** - *Lists a summary of the properties of a context. A context provides a logical grouping - * of other entities.
+ *Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
* @public */ export interface ContextSummary { @@ -339,50 +277,19 @@ export interface ContinuousParameterRange { Name: string | undefined; /** - *The minimum value for the hyperparameter.
- * The
- * tuning job uses floating-point values between this value and MaxValuefor
- * tuning.
The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values
- * between MinValue value and this value for tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.
The scale that hyperparameter tuning uses to search the hyperparameter range. For - * information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
- *SageMaker hyperparameter tuning chooses the best scale for the - * hyperparameter.
- *Hyperparameter tuning searches the values in the hyperparameter range by - * using a linear scale.
- *Hyperparameter tuning searches the values in the hyperparameter range by - * using a logarithmic scale.
- *Logarithmic scaling works only for ranges that have only values greater - * than 0.
- *Hyperparameter tuning searches the values in the hyperparameter range by - * using a reverse logarithmic scale.
- *Reverse logarithmic scaling works only for ranges that are entirely within - * the range 0<=x<1.0.
- *The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
A flag to indicating that automatic model tuning (AMT) has detected model convergence, - * defined as a lack of significant improvement (1% or less) against an objective - * metric.
+ *A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
* @public */ export interface ConvergenceDetected { @@ -533,28 +438,24 @@ export interface IntegerParameterRangeSpecification { } /** - *Defines the possible values for categorical, continuous, and integer hyperparameters - * to be used by an algorithm.
+ *Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
* @public */ export interface ParameterRange { /** - *A IntegerParameterRangeSpecification object that defines the possible
- * values for an integer hyperparameter.
A IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.
A ContinuousParameterRangeSpecification object that defines the possible
- * values for a continuous hyperparameter.
A ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.
A CategoricalParameterRangeSpecification object that defines the possible
- * values for a categorical hyperparameter.
A CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.
The type of this hyperparameter. The valid types are Integer,
- * Continuous, Categorical, and FreeText.
The type of this hyperparameter. The valid types are Integer, Continuous, Categorical, and FreeText.
Indicates whether this hyperparameter is tunable in a hyperparameter tuning - * job.
+ *Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
* @public */ IsTunable?: boolean | undefined; @@ -620,8 +519,7 @@ export interface HyperParameterSpecification { IsRequired?: boolean | undefined; /** - *The default value for this hyperparameter. If a default value is specified, a - * hyperparameter cannot be required.
+ *The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
* @public */ DefaultValue?: string | undefined; @@ -643,11 +541,7 @@ export type HyperParameterTuningJobObjectiveType = (typeof HyperParameterTuningJobObjectiveType)[keyof typeof HyperParameterTuningJobObjectiveType]; /** - *Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning
- * uses the value of this metric to evaluate the training jobs it launches, and returns the
- * training job that results in either the highest or lowest value for this metric,
- * depending on the value you specify for the Type parameter. If you want to
- * define a custom objective metric, see Define metrics and environment variables.
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
The - * name of the metric to use for the objective metric.
+ *The name of the metric to use for the objective metric.
* @public */ MetricName: string | undefined; @@ -671,23 +564,19 @@ export interface HyperParameterTuningJobObjective { */ export interface TrainingSpecification { /** - *The Amazon ECR registry path of the Docker image that contains the training - * algorithm.
+ *The Amazon ECR registry path of the Docker image that contains the training algorithm.
* @public */ TrainingImage: string | undefined; /** - *An MD5 hash of the training algorithm that identifies the Docker image used for - * training.
+ *An MD5 hash of the training algorithm that identifies the Docker image used for training.
* @public */ TrainingImageDigest?: string | undefined; /** - *A list of the HyperParameterSpecification objects, that define the
- * supported hyperparameters. This is required if the algorithm supports automatic model
- * tuning.>
A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Indicates whether the algorithm supports distributed training. If set to false, buyers - * can't request more than one instance during training.
+ *Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
* @public */ SupportsDistributedTraining?: boolean | undefined; /** - *A list of MetricDefinition objects, which are used for parsing metrics
- * generated by the algorithm.
A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
A list of ChannelSpecification objects, which specify the input sources
- * to be used by the algorithm.
A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
A list of the metrics that the algorithm emits that can be used as the objective - * metric in a hyperparameter tuning job.
+ *A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
* @public */ SupportedTuningJobObjectiveMetrics?: HyperParameterTuningJobObjective[] | undefined; @@ -750,79 +635,31 @@ export interface CreateAlgorithmInput { AlgorithmDescription?: string | undefined; /** - *Specifies details about training jobs run by this algorithm, including the - * following:
- *The Amazon ECR path of the container and the version digest of the - * algorithm.
- *The hyperparameters that the algorithm supports.
- *The instance types that the algorithm supports for training.
- *Whether the algorithm supports distributed training.
- *The metrics that the algorithm emits to Amazon CloudWatch.
- *Which metrics that the algorithm emits can be used as the objective metric for - * hyperparameter tuning jobs.
- *The input channels that the algorithm supports for training data. For example,
- * an algorithm might support train, validation, and
- * test channels.
Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.
Specifies details about inference jobs that the algorithm runs, including the - * following:
- *The Amazon ECR paths of containers that contain the inference code and model - * artifacts.
- *The instance types that the algorithm supports for transform jobs and - * real-time endpoints used for inference.
- *The input and output content formats that the algorithm supports for - * inference.
- *Specifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies configurations for one or more training jobs and that SageMaker runs to test the - * algorithm's training code and, optionally, one or more batch transform jobs that SageMaker - * runs to test the algorithm's inference code.
+ *Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.
* @public */ ValidationSpecification?: AlgorithmValidationSpecification | undefined; /** - *Whether to certify the algorithm so that it can be listed in Amazon Web Services - * Marketplace.
+ *Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
* @public */ CertifyForMarketplace?: boolean | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -850,15 +687,13 @@ export interface CreateAppRequest { DomainId: string | undefined; /** - *The user profile name. If this value is not set, then SpaceName must be
- * set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be
- * set.
The name of the space. If this value is not set, then UserProfileName must be set.
Each tag consists of a key and an optional value. Tag keys must be unique per - * resource.
+ *Each tag consists of a key and an optional value. Tag keys must be unique per resource.
* @public */ Tags?: Tag[] | undefined; /** - *The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image - * created on the instance.
- *The value of InstanceType passed as part of the ResourceSpec
- * in the CreateApp call overrides the value passed as part of the
- * ResourceSpec configured for the user profile or the domain. If
- * InstanceType is not specified in any of those three ResourceSpec
- * values for a KernelGateway app, the CreateApp call fails with a
- * request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.
The KernelGatewayImageConfig. You can only specify one image kernel in the - * AppImageConfig API. This kernel will be shown to users before the - * image starts. Once the image runs, all kernels are visible in JupyterLab.
+ *The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
* @public */ KernelGatewayImageConfig?: KernelGatewayImageConfig | undefined; @@ -968,9 +791,7 @@ export interface CreateAppImageConfigRequest { JupyterLabAppImageConfig?: JupyterLabAppImageConfig | undefined; /** - *The CodeEditorAppImageConfig. You can only specify one image kernel
- * in the AppImageConfig API. This kernel is shown to users before the image starts.
- * After the image runs, all kernels are visible in Code Editor.
The CodeEditorAppImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in Code Editor.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model - * deployment.
+ *Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
* @public */ export interface ModelDeployConfig { /** - *Set to True to automatically generate an endpoint name for a one-click
- * Autopilot model deployment; set to False otherwise. The default value is
- * False.
If you set AutoGenerateEndpointName to True, do not specify
- * the EndpointName; otherwise a 400 error is thrown.
Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False otherwise. The default value is False.
If you set AutoGenerateEndpointName to True, do not specify the EndpointName; otherwise a 400 error is thrown.
Specifies the endpoint name to use for a one-click Autopilot model deployment if the - * endpoint name is not generated automatically.
- *Specify the EndpointName if and only if you set
- * AutoGenerateEndpointName to False; otherwise a 400 error is
- * thrown.
Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName if and only if you set AutoGenerateEndpointName to False; otherwise a 400 error is thrown.
Identifies an Autopilot job. The name must be unique to your account and is case - * insensitive.
+ *Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
* @public */ AutoMLJobName: string | undefined; /** - *An array of channel objects that describes the input data and its location. Each channel
- * is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A
- * minimum of 500 rows is required for the training dataset. There is not a minimum number of
- * rows required for the validation dataset.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Provides information about encryption and the Amazon S3 output path needed to - * store artifacts from an AutoML job. Format(s) supported: CSV.
+ *Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
* @public */ OutputDataConfig: AutoMLOutputDataConfig | undefined; /** - *Defines the type of supervised learning problem available for the candidates. For more - * information, see - * SageMaker Autopilot problem types.
+ *Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.
* @public */ ProblemType?: ProblemType | undefined; /** - *Specifies a metric to minimize or maximize as the objective of a job. If not specified, - * the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
+ *Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
* @public */ AutoMLJobObjective?: AutoMLJobObjective | undefined; @@ -1125,24 +925,19 @@ export interface CreateAutoMLJobRequest { RoleArn: string | undefined; /** - *Generates possible candidates without training the models. A candidate is a combination - * of data preprocessors, algorithms, and algorithm parameter settings.
+ *Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
* @public */ GenerateCandidateDefinitionsOnly?: boolean | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per - * resource.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
* @public */ Tags?: Tag[] | undefined; /** - *Specifies how to generate the endpoint name for an automatic one-click Autopilot model - * deployment.
+ *Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
* @public */ ModelDeployConfig?: ModelDeployConfig | undefined; @@ -1164,42 +959,19 @@ export interface CreateAutoMLJobResponse { */ export interface CreateAutoMLJobV2Request { /** - *Identifies an Autopilot job. The name must be unique to your account and is case - * insensitive.
+ *Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
* @public */ AutoMLJobName: string | undefined; /** - *An array of channel objects describing the input data and their location. Each channel
- * is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters.
- * The supported formats depend on the problem type:
For tabular problem types: S3Prefix,
- * ManifestFile.
For image classification: S3Prefix, ManifestFile,
- * AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix, ManifestFile.
For image classification: S3Prefix, ManifestFile, AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
Provides information about encryption and the Amazon S3 output path needed to - * store artifacts from an AutoML job.
+ *Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
* @public */ OutputDataConfig: AutoMLOutputDataConfig | undefined; @@ -1217,10 +989,7 @@ export interface CreateAutoMLJobV2Request { RoleArn: string | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, such as by purpose, owner, or environment. For more - * information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per - * resource.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
* @public */ Tags?: Tag[] | undefined; @@ -1232,51 +1001,19 @@ export interface CreateAutoMLJobV2Request { SecurityConfig?: AutoMLSecurityConfig | undefined; /** - *Specifies a metric to minimize or maximize as the objective of a job. If not specified, - * the default objective metric depends on the problem type. For the list of default values - * per problem type, see AutoMLJobObjective.
- *For tabular problem types: You must either provide both the
- * AutoMLJobObjective and indicate the type of supervised learning
- * problem in AutoMLProblemTypeConfig
- * (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning):
- * Fine-tuning language models in Autopilot does not
- * require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs
- * without requiring multiple candidates to be trained and evaluated.
- * Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a
- * default objective metric, the cross-entropy loss. After fine-tuning a language model,
- * you can evaluate the quality of its generated text using different metrics.
- * For a list of the available metrics, see Metrics for
- * fine-tuning LLMs in Autopilot.
Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model - * deployment.
+ *Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
* @public */ ModelDeployConfig?: ModelDeployConfig | undefined; /** - *This structure specifies how to split the data into train and validation - * datasets.
- *The validation and training datasets must contain the same headers. For jobs created by
- * calling CreateAutoMLJob, the validation dataset must be less than 2 GB in
- * size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot - * automatically splits the input dataset into training and validation sets.
- *This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You - * can control access to and from your resources by configuring your VPC. For more - * information, see Give SageMaker access to resources - * in your Amazon VPC.
- *When your Amazon VPC and subnets support IPv6, network communications differ - * based on the cluster orchestration platform:
- *Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and - * IPv4 addresses, allowing immediate IPv6 network communications.
- *In Amazon EKS-orchestrated clusters, nodes receive dual-stack - * addressing, but pods can only use IPv6 when the Amazon EKS cluster is - * explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
- *Additional resources for IPv6 configuration:
- *For information about adding IPv6 support to your VPC, see to IPv6 - * Support for VPC.
- *For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
- *To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
- *Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You can control access to and from your resources by configuring your VPC. For more information, see Give SageMaker access to resources in your Amazon VPC.
When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:
Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.
In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
Additional resources for IPv6 configuration:
For information about adding IPv6 support to your VPC, see to IPv6 Support for VPC.
For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can - * add tags to your cluster in the same way you add them in other Amazon Web Services services - * that support tagging. To learn more about tagging Amazon Web Services resources in general, - * see Tagging - * Amazon Web Services Resources User Guide.
+ *Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see Tagging Amazon Web Services Resources User Guide.
* @public */ Tags?: Tag[] | undefined; /** - *The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, the only supported
- * value is "eks", which is to use an Amazon Elastic Kubernetes Service (EKS)
- * cluster as the orchestrator.
The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, the only supported value is "eks", which is to use an Amazon Elastic Kubernetes Service (EKS) cluster as the orchestrator.
The node recovery mode for the SageMaker HyperPod cluster. When set to Automatic,
- * SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set
- * to None, cluster administrators will need to manually manage any faulty
- * cluster instances.
The node recovery mode for the SageMaker HyperPod cluster. When set to Automatic, SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set to None, cluster administrators will need to manually manage any faulty cluster instances.
Priority class configuration. When included in PriorityClasses, these class
- * configurations define how tasks are queued.
Priority class configuration. When included in PriorityClasses, these class configurations define how tasks are queued.
Weight of the priority class. The value is within a range from 0 to 100, where 0 is the - * default.
- *A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the - * default.
+ *Weight of the priority class. The value is within a range from 0 to 100, where 0 is the default.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the default.
* @public */ Weight: number | undefined; } /** - *Cluster policy configuration. This policy is used for task prioritization and fair-share - * allocation. This helps prioritize critical workloads and distributes idle compute - * across entities.
+ *Cluster policy configuration. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
* @public */ export interface SchedulerConfig { /** - *List of the priority classes, PriorityClass, of the cluster policy. When
- * specified, these class configurations define how tasks are queued.
List of the priority classes, PriorityClass, of the cluster policy. When specified, these class configurations define how tasks are queued.
When enabled, entities borrow idle compute based on their assigned
- * FairShareWeight.
When disabled, entities borrow idle compute based on a first-come first-serve - * basis.
- *Default is Enabled.
When enabled, entities borrow idle compute based on their assigned FairShareWeight.
When disabled, entities borrow idle compute based on a first-come first-serve basis.
Default is Enabled.
The name of the Git repository. The name must have 1 to 63 characters. Valid - * characters are a-z, A-Z, 0-9, and - (hyphen).
+ *The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
* @public */ CodeRepositoryName: string | undefined; /** - *Specifies details about the repository, including the URL where the repository is - * located, the default branch, and credentials to use to access the repository.
+ *Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
* @public */ GitConfig: GitConfig | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -1564,739 +1246,108 @@ export const Framework = { export type Framework = (typeof Framework)[keyof typeof Framework]; /** - *Contains information about the location of input model artifacts, the name and - * shape - * of the expected data inputs, and the framework in which the model was trained.
+ *Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
* @public */ export interface InputConfig { /** - *The S3 path where the model artifacts, which result from model training, are stored. - * This path must point to a single gzip compressed tar archive (.tar.gz suffix).
+ *The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
* @public */ S3Uri: string | undefined; /** - *Specifies the name and shape of the expected data inputs for your trained model with a
- * JSON dictionary form. The data inputs are Framework specific.
- * TensorFlow: You must specify the name and shape (NHWC format) of
- * the expected data inputs using a dictionary format for your trained model. The
- * dictionary formats required for the console and CLI are different.
Examples for one input:
- *If using the console,
- * \{"input":[1,1024,1024,3]\}
- *
If using the CLI,
- * \{\"input\":[1,1024,1024,3]\}
- *
Examples for two inputs:
- *If using the console, \{"data1": [1,28,28,1],
- * "data2":[1,28,28,1]\}
- *
If using the CLI, \{\"data1\": [1,28,28,1],
- * \"data2\":[1,28,28,1]\}
- *
- * KERAS: You must specify the name and shape (NCHW format) of
- * expected data inputs using a dictionary format for your trained model. Note that
- * while Keras model artifacts should be uploaded in NHWC (channel-last) format,
- * DataInputConfig should be specified in NCHW (channel-first)
- * format. The dictionary formats required for the console and CLI are
- * different.
Examples for one input:
- *If using the console,
- * \{"input_1":[1,3,224,224]\}
- *
If using the CLI,
- * \{\"input_1\":[1,3,224,224]\}
- *
Examples for two inputs:
- *If using the console, \{"input_1": [1,3,224,224],
- * "input_2":[1,3,224,224]\}
- *
If using the CLI, \{\"input_1\": [1,3,224,224],
- * \"input_2\":[1,3,224,224]\}
- *
- * MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW
- * format) of the expected data inputs in order using a dictionary format for your
- * trained model. The dictionary formats required for the console and CLI are
- * different.
Examples for one input:
- *If using the console,
- * \{"data":[1,3,1024,1024]\}
- *
If using the CLI,
- * \{\"data\":[1,3,1024,1024]\}
- *
Examples for two inputs:
- *If using the console, \{"var1": [1,1,28,28],
- * "var2":[1,1,28,28]\}
- *
If using the CLI, \{\"var1\": [1,1,28,28],
- * \"var2\":[1,1,28,28]\}
- *
- * PyTorch: You can either specify the name and shape (NCHW format)
- * of expected data inputs in order using a dictionary format for your trained
- * model or you can specify the shape only using a list format. The dictionary
- * formats required for the console and CLI are different. The list formats for the
- * console and CLI are the same.
Examples for one input in dictionary format:
- *If using the console,
- * \{"input0":[1,3,224,224]\}
- *
If using the CLI,
- * \{\"input0\":[1,3,224,224]\}
- *
Example for one input in list format:
- * [[1,3,224,224]]
- *
Examples for two inputs in dictionary format:
- *If using the console, \{"input0":[1,3,224,224],
- * "input1":[1,3,224,224]\}
- *
If using the CLI, \{\"input0\":[1,3,224,224],
- * \"input1\":[1,3,224,224]\}
- *
Example for two inputs in list format: [[1,3,224,224],
- * [1,3,224,224]]
- *
- * XGBOOST: input data name and shape are not needed.
- * DataInputConfig supports the following parameters for CoreML
- * TargetDevice (ML Model format):
- * shape: Input shape, for example \{"input_1": \{"shape":
- * [1,224,224,3]\}\}. In addition to static input shapes, CoreML converter
- * supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know
- * the input shape will be within some specific interval in that dimension,
- * for example: \{"input_1": \{"shape": ["1..10", 224, 224,
- * 3]\}\}
- *
Enumerated shapes. Sometimes, the models are trained to work only on a
- * select set of inputs. You can enumerate all supported input shapes, for
- * example: \{"input_1": \{"shape": [[1, 224, 224, 3], [1, 160, 160,
- * 3]]\}\}
- *
- * default_shape: Default input shape. You can set a default shape
- * during conversion for both Range Dimension and Enumerated Shapes. For example
- * \{"input_1": \{"shape": ["1..10", 224, 224, 3], "default_shape": [1,
- * 224, 224, 3]\}\}
- *
- * type: Input type. Allowed values: Image and
- * Tensor. By default, the converter generates an ML Model with
- * inputs of type Tensor (MultiArray). User can set input type to be Image. Image
- * input type requires additional input parameters such as bias and
- * scale.
- * bias: If the input type is an Image, you need to provide the bias
- * vector.
- * scale: If the input type is an Image, you need to provide a scale
- * factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig
- * CompilerOptions. CoreML converter supports Tensorflow and PyTorch models.
- * CoreML conversion examples:
Tensor type input:
- *
- * "DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3],
- * [1,160,160,3]], "default_shape": [1,224,224,3]\}\}
- *
Tensor type input without input name (PyTorch):
- *
- * "DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]],
- * "default_shape": [1,3,224,224]\}]
- *
Image type input:
- *
- * "DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3],
- * [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image",
- * "bias": [-1,-1,-1], "scale": 0.007843137255\}\}
- *
- * "CompilerOptions": \{"class_labels":
- * "imagenet_labels_1000.txt"\}
- *
Image type input without input name (PyTorch):
- *
- * "DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]],
- * "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1],
- * "scale": 0.007843137255\}]
- *
- * "CompilerOptions": \{"class_labels":
- * "imagenet_labels_1000.txt"\}
- *
Depending on the model format, DataInputConfig requires the following
- * parameters for ml_eia2
- * OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names
- * from signature_def_key and the input model shapes for
- * DataInputConfig. Specify the signature_def_key in
- *
- * OutputConfig:CompilerOptions
- * if the model does not
- * use TensorFlow's default signature def key. For example:
- * "DataInputConfig": \{"inputs": [1, 224, 224, 3]\}
- *
- * "CompilerOptions": \{"signature_def_key":
- * "serving_custom"\}
- *
For TensorFlow models saved as a frozen graph, specify the input tensor names
- * and shapes in DataInputConfig and the output tensor names for
- * output_names in
- * OutputConfig:CompilerOptions
- * . For
- * example:
- * "DataInputConfig": \{"input_tensor:0": [1, 224, 224,
- * 3]\}
- *
- * "CompilerOptions": \{"output_names":
- * ["output_tensor:0"]\}
- *
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework specific.
TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, \{"input":[1,1024,1024,3]\}
If using the CLI, \{\"input\":[1,1024,1024,3]\}
Examples for two inputs:
If using the console, \{"data1": [1,28,28,1], "data2":[1,28,28,1]\}
If using the CLI, \{\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]\}
KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, \{"input_1":[1,3,224,224]\}
If using the CLI, \{\"input_1\":[1,3,224,224]\}
Examples for two inputs:
If using the console, \{"input_1": [1,3,224,224], "input_2":[1,3,224,224]\}
If using the CLI, \{\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]\}
MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, \{"data":[1,3,1024,1024]\}
If using the CLI, \{\"data\":[1,3,1024,1024]\}
Examples for two inputs:
If using the console, \{"var1": [1,1,28,28], "var2":[1,1,28,28]\}
If using the CLI, \{\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]\}
PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, \{"input0":[1,3,224,224]\}
If using the CLI, \{\"input0\":[1,3,224,224]\}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, \{"input0":[1,3,224,224], "input1":[1,3,224,224]\}
If using the CLI, \{\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]\}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST: input data name and shape are not needed.
DataInputConfig supports the following parameters for CoreML TargetDevice (ML Model format):
shape: Input shape, for example \{"input_1": \{"shape": [1,224,224,3]\}\}. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: \{"input_1": \{"shape": ["1..10", 224, 224, 3]\}\}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: \{"input_1": \{"shape": [[1, 224, 224, 3], [1, 160, 160, 3]]\}\}
default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example \{"input_1": \{"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224, 3]\}\}
type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.
bias: If the input type is an Image, you need to provide the bias vector.
scale: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
"DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3]\}\}
Tensor type input without input name (PyTorch):
"DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224]\}]
Image type input:
"DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3], [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255\}\}
"CompilerOptions": \{"class_labels": "imagenet_labels_1000.txt"\}
Image type input without input name (PyTorch):
"DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape": [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255\}]
"CompilerOptions": \{"class_labels": "imagenet_labels_1000.txt"\}
Depending on the model format, DataInputConfig requires the following parameters for ml_eia2 OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key and the input model shapes for DataInputConfig. Specify the signature_def_key in OutputConfig:CompilerOptions if the model does not use TensorFlow's default signature def key. For example:
"DataInputConfig": \{"inputs": [1, 224, 224, 3]\}
"CompilerOptions": \{"signature_def_key": "serving_custom"\}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig and the output tensor names for output_names in OutputConfig:CompilerOptions . For example:
"DataInputConfig": \{"input_tensor:0": [1, 224, 224, 3]\}
"CompilerOptions": \{"output_names": ["output_tensor:0"]\}
Identifies the framework in which the model was trained. For example: - * TENSORFLOW.
+ *Identifies the framework in which the model was trained. For example: TENSORFLOW.
* @public */ Framework: Framework | undefined; /** - *Specifies the framework version to use. This API field is only supported for the - * MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
- *For information about framework versions supported for cloud targets and edge devices, - * see Cloud - * Supported Instance Types and Frameworks and Edge Supported - * Frameworks.
+ *Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
* @public */ FrameworkVersion?: string | undefined; } /** - *Contains information about a target platform that you want your model to run on, such
- * as OS, architecture, and accelerators. It is an alternative of
- * TargetDevice.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
Specifies a target platform OS.
- *
- * LINUX: Linux-based operating systems.
- * ANDROID: Android operating systems. Android API level can be
- * specified using the ANDROID_PLATFORM compiler option. For example,
- * "CompilerOptions": \{'ANDROID_PLATFORM': 28\}
- *
Specifies a target platform OS.
LINUX: Linux-based operating systems.
ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, "CompilerOptions": \{'ANDROID_PLATFORM': 28\}
Specifies a target platform architecture.
- *
- * X86_64: 64-bit version of the x86 instruction set.
- * X86: 32-bit version of the x86 instruction set.
- * ARM64: ARMv8 64-bit CPU.
- * ARM_EABIHF: ARMv7 32-bit, Hard Float.
- * ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM
- * platform.
Specifies a target platform architecture.
X86_64: 64-bit version of the x86 instruction set.
X86: 32-bit version of the x86 instruction set.
ARM64: ARMv8 64-bit CPU.
ARM_EABIHF: ARMv7 32-bit, Hard Float.
ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
Specifies a target platform accelerator (optional).
- *
- * NVIDIA: Nvidia graphics processing unit. It also requires
- * gpu-code, trt-ver, cuda-ver compiler
- * options
- * MALI: ARM Mali graphics processor
- * INTEL_GRAPHICS: Integrated Intel graphics
Specifies a target platform accelerator (optional).
NVIDIA: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler options
MALI: ARM Mali graphics processor
INTEL_GRAPHICS: Integrated Intel graphics
Contains information about the output location for the compiled model and the target
- * device that the model runs on. TargetDevice and TargetPlatform
- * are mutually exclusive, so you need to choose one between the two to specify your target
- * device or platform. If you cannot find your device you want to use from the
- * TargetDevice list, use TargetPlatform to describe the
- * platform of your edge device and CompilerOptions if there are specific
- * settings that are required or recommended to use for particular TargetPlatform.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For
- * example, s3://bucket-name/key-name-prefix.
Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
Identifies the target device or the machine learning instance that you want to run
- * your model on after the compilation has completed. Alternatively, you can specify OS,
- * architecture, and accelerator using TargetPlatform
- * fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region,
- * and ml_inf2 is available only in US East (Ohio) Region.
Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region, and ml_inf2 is available only in US East (Ohio) Region.
Contains information about a target platform that you want your model to run on, such
- * as OS, architecture, and accelerators. It is an alternative of
- * TargetDevice.
The following examples show how to configure the TargetPlatform and
- * CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
- *
- * "TargetPlatform": \{"Os": "LINUX", "Arch": "ARM_EABIHF"\},
- *
- * "CompilerOptions": \{'mattr': ['+neon']\}
- *
Jetson TX2
- *
- * "TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", "Accelerator":
- * "NVIDIA"\},
- *
- * "CompilerOptions": \{'gpu-code': 'sm_62', 'trt-ver': '6.0.1',
- * 'cuda-ver': '10.0'\}
- *
EC2 m5.2xlarge instance OS
- *
- * "TargetPlatform": \{"Os": "LINUX", "Arch": "X86_64", "Accelerator":
- * "NVIDIA"\},
- *
- * "CompilerOptions": \{'mcpu': 'skylake-avx512'\}
- *
RK3399
- *
- * "TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", "Accelerator":
- * "MALI"\}
- *
ARMv7 phone (CPU)
- *
- * "TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM_EABI"\},
- *
- * "CompilerOptions": \{'ANDROID_PLATFORM': 25, 'mattr':
- * ['+neon']\}
- *
ARMv8 phone (CPU)
- *
- * "TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM64"\},
- *
- * "CompilerOptions": \{'ANDROID_PLATFORM': 29\}
- *
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM_EABIHF"\},
"CompilerOptions": \{'mattr': ['+neon']\}
Jetson TX2
"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"\},
"CompilerOptions": \{'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'\}
EC2 m5.2xlarge instance OS
"TargetPlatform": \{"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"\},
"CompilerOptions": \{'mcpu': 'skylake-avx512'\}
RK3399
"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"\}
ARMv7 phone (CPU)
"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM_EABI"\},
"CompilerOptions": \{'ANDROID_PLATFORM': 25, 'mattr': ['+neon']\}
ARMv8 phone (CPU)
"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM64"\},
"CompilerOptions": \{'ANDROID_PLATFORM': 29\}
Specifies additional parameters for compiler options in JSON format. The compiler
- * options are TargetPlatform specific. It is required for NVIDIA accelerators
- * and highly recommended for CPU compilations. For any other cases, it is optional to
- * specify CompilerOptions.
- *
- * DTYPE: Specifies the data type for the input. When compiling for
- * ml_* (except for ml_inf) instances using PyTorch
- * framework, provide the data type (dtype) of the model's input.
- * "float32" is used if "DTYPE" is not specified.
- * Options for data type are:
float32: Use either "float" or
- * "float32".
int64: Use either "int64" or "long".
For example, \{"dtype" : "float32"\}.
- * CPU: Compilation for CPU supports the following compiler
- * options.
- * mcpu: CPU micro-architecture. For example, \{'mcpu':
- * 'skylake-avx512'\}
- *
- * mattr: CPU flags. For example, \{'mattr': ['+neon',
- * '+vfpv4']\}
- *
- * ARM: Details of ARM CPU compilations.
- * NEON: NEON is an implementation of the Advanced SIMD
- * extension used in ARMv7 processors.
For example, add \{'mattr': ['+neon']\} to the compiler
- * options if compiling for ARM 32-bit platform with the NEON
- * support.
- * NVIDIA: Compilation for NVIDIA GPU supports the following
- * compiler options.
- * gpu_code: Specifies the targeted architecture.
- * trt-ver: Specifies the TensorRT versions in x.y.z.
- * format.
- * cuda-ver: Specifies the CUDA version in x.y
- * format.
For example, \{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver':
- * '10.1'\}
- *
- * ANDROID: Compilation for the Android OS supports the following
- * compiler options:
- * ANDROID_PLATFORM: Specifies the Android API levels.
- * Available levels range from 21 to 29. For example,
- * \{'ANDROID_PLATFORM': 28\}.
- * mattr: Add \{'mattr': ['+neon']\} to compiler
- * options if compiling for ARM 32-bit platform with NEON support.
- * INFERENTIA: Compilation for target ml_inf1 uses compiler options
- * passed in as a JSON string. For example, "CompilerOptions": "\"--verbose 1
- * --num-neuroncores 2 -O2\"".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
- *
- * CoreML: Compilation for the CoreML OutputConfig
- * TargetDevice supports the following compiler options:
- * class_labels: Specifies the classification labels file
- * name inside input tar.gz file. For example, \{"class_labels":
- * "imagenet_labels_1000.txt"\}. Labels inside the txt file
- * should be separated by newlines.
Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model's input. "float32" is used if "DTYPE" is not specified. Options for data type are:
float32: Use either "float" or "float32".
int64: Use either "int64" or "long".
For example, \{"dtype" : "float32"\}.
CPU: Compilation for CPU supports the following compiler options.
mcpu: CPU micro-architecture. For example, \{'mcpu': 'skylake-avx512'\}
mattr: CPU flags. For example, \{'mattr': ['+neon', '+vfpv4']\}
ARM: Details of ARM CPU compilations.
NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add \{'mattr': ['+neon']\} to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code: Specifies the targeted architecture.
trt-ver: Specifies the TensorRT versions in x.y.z. format.
cuda-ver: Specifies the CUDA version in x.y format.
For example, \{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'\}
ANDROID: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, \{'ANDROID_PLATFORM': 28\}.
mattr: Add \{'mattr': ['+neon']\} to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, "CompilerOptions": "\"--verbose 1 --num-neuroncores 2 -O2\"".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML: Compilation for the CoreML OutputConfig TargetDevice supports the following compiler options:
class_labels: Specifies the classification labels file name inside input tar.gz file. For example, \{"class_labels": "imagenet_labels_1000.txt"\}. Labels inside the txt file should be separated by newlines.
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker AI - * uses to encrypt your output models with Amazon S3 server-side encryption after compilation - * job. If you don't provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your - * role's account. For more information, see KMS-Managed Encryption - * Keys in the Amazon Simple Storage Service Developer - * Guide. - *
- *The KmsKeyId can be any of the following formats:
- *Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker AI uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The VpcConfig configuration object that specifies the VPC that you want the - * compilation jobs to connect to. For more information on controlling access to your Amazon S3 - * buckets used for compilation job, see Give Amazon SageMaker AI Compilation Jobs Access to - * Resources in Your Amazon VPC.
+ *The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker AI Compilation Jobs Access to Resources in Your Amazon VPC.
* @public */ export interface NeoVpcConfig { /** - *The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the
- * security groups for the VPC that is specified in the Subnets field.
The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC that you want to connect the compilation job to for - * accessing the model in Amazon S3.
+ *The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
* @public */ Subnets: string[] | undefined; @@ -2313,75 +1364,43 @@ export interface CreateCompilationJobRequest { CompilationJobName: string | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on - * your behalf.
- *During model compilation, Amazon SageMaker AI needs your permission to:
- *Read input data from an S3 bucket
- *Write model artifacts to an S3 bucket
- *Write logs to Amazon CloudWatch Logs
- *Publish metrics to Amazon CloudWatch
- *You grant permissions for all of these tasks to an IAM role. To pass this role to
- * Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For
- * more information, see Amazon SageMaker AI
- * Roles.
- *
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model compilation, Amazon SageMaker AI needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
The Amazon Resource Name (ARN) of a versioned model package. Provide either a
- * ModelPackageVersionArn or an InputConfig object in the
- * request syntax. The presence of both objects in the CreateCompilationJob
- * request will return an exception.
The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
Provides information about the location of input model artifacts, the name and shape - * of the expected data inputs, and the framework in which the model was trained.
+ *Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
* @public */ InputConfig?: InputConfig | undefined; /** - *Provides information about the output location for the compiled model and the target - * device the model runs on.
+ *Provides information about the output location for the compiled model and the target device the model runs on.
* @public */ OutputConfig: OutputConfig | undefined; /** - *A VpcConfig object that specifies the VPC that you want your compilation job - * to connect to. Control access to your models by configuring the VPC. For more - * information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
+ *A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: NeoVpcConfig | undefined; /** - *Specifies a limit to how long a model compilation job can run. When the job reaches - * the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training - * costs.
+ *Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
* @public */ StoppingCondition: StoppingCondition | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -2392,15 +1411,7 @@ export interface CreateCompilationJobRequest { */ export interface CreateCompilationJobResponse { /** - *If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns - * the following data in JSON format:
- *
- * CompilationJobArn: The Amazon Resource Name (ARN) of the compiled
- * job.
If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns the following data in JSON format:
CompilationJobArn: The Amazon Resource Name (ARN) of the compiled job.
Configuration of the compute allocation definition. This includes the resource sharing - * option, and the setting to preempt low priority tasks.
+ *Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
* @public */ ComputeQuotaConfig: ComputeQuotaConfig | undefined; @@ -2442,9 +1452,7 @@ export interface CreateComputeQuotaRequest { ComputeQuotaTarget: ComputeQuotaTarget | undefined; /** - *The state of the compute allocation being described. Use to enable or disable compute - * allocation.
- *Default is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
An Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use - * the converted data. Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
* @public */ RecordPreprocessorSourceUri?: string | undefined; /** - *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable - * only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
* @public */ PostAnalyticsProcessorSourceUri?: string | undefined; @@ -2595,9 +1600,7 @@ export interface MonitoringStatisticsResource { } /** - *Configuration for monitoring constraints and monitoring statistics. These baseline resources are - * compared against the results of the current job from the series of jobs scheduled to collect data - * periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
* @public */ export interface DataQualityBaselineConfig { @@ -2626,8 +1629,7 @@ export interface DataQualityBaselineConfig { */ export interface EndpointInput { /** - *An endpoint in customer's account which has enabled DataCaptureConfig
- * enabled.
An endpoint in customer's account which has enabled DataCaptureConfig enabled.
Whether the Pipe or File is used as the input mode for
- * transferring data for the monitoring job. Pipe mode is recommended for large
- * datasets. File mode is useful for small files that fit in memory. Defaults to
- * File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an
- * Amazon S3 key. Defaults to FullyReplicated
- *
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
If specified, monitoring jobs substract this time from the start time. For information - * about using offsets for scheduling monitoring jobs, see Schedule Model - * Quality Monitoring Jobs.
+ *If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
* @public */ StartTimeOffset?: string | undefined; /** - *If specified, monitoring jobs substract this time from the end time. For information - * about using offsets for scheduling monitoring jobs, see Schedule Model - * Quality Monitoring Jobs.
+ *If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
* @public */ EndTimeOffset?: string | undefined; @@ -2703,8 +1696,7 @@ export interface EndpointInput { } /** - *The input for the data quality monitoring job. Currently endpoints are supported for - * input.
+ *The input for the data quality monitoring job. Currently endpoints are supported for input.
* @public */ export interface DataQualityJobInput { @@ -2736,29 +1728,24 @@ export const ProcessingS3UploadMode = { export type ProcessingS3UploadMode = (typeof ProcessingS3UploadMode)[keyof typeof ProcessingS3UploadMode]; /** - *Information about where and how you want to store the results of a monitoring - * job.
+ *Information about where and how you want to store the results of a monitoring job.
* @public */ export interface MonitoringS3Output { /** - *A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI - * saves the results of a monitoring job.
+ *A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job.
* @public */ S3Uri: string | undefined; /** - *The local path to the Amazon S3 storage location where Amazon SageMaker AI - * saves the results of a monitoring job. LocalPath is an absolute path for the output - * data.
+ *The local path to the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job. LocalPath is an absolute path for the output data.
* @public */ LocalPath: string | undefined; /** - *Whether to upload the results of the monitoring job continuously or after the job - * completes.
+ *Whether to upload the results of the monitoring job continuously or after the job completes.
* @public */ S3UploadMode?: ProcessingS3UploadMode | undefined; @@ -2770,8 +1757,7 @@ export interface MonitoringS3Output { */ export interface MonitoringOutput { /** - *The Amazon S3 storage location where the results of a monitoring job are - * saved.
+ *The Amazon S3 storage location where the results of a monitoring job are saved.
* @public */ S3Output: MonitoringS3Output | undefined; @@ -2783,15 +1769,13 @@ export interface MonitoringOutput { */ export interface MonitoringOutputConfig { /** - *Monitoring outputs for monitoring jobs. This is where the output of the periodic - * monitoring jobs is uploaded.
+ *Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
* @public */ MonitoringOutputs: MonitoringOutput[] | undefined; /** - *The Key Management Service (KMS) key that Amazon SageMaker AI uses to - * encrypt the model artifacts at rest using Amazon S3 server-side encryption.
+ *The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
* @public */ KmsKeyId?: string | undefined; @@ -2908,8 +1892,7 @@ export type ProcessingInstanceType = (typeof ProcessingInstanceType)[keyof typeo */ export interface MonitoringClusterConfig { /** - *The number of ML compute instances to use in the model monitoring job. For distributed - * processing jobs, specify a value greater than 1. The default value is 1.
+ *The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
* @public */ InstanceCount: number | undefined; @@ -2921,16 +1904,13 @@ export interface MonitoringClusterConfig { InstanceType: ProcessingInstanceType | undefined; /** - *The size of the ML storage volume, in gigabytes, that you want to provision. You must - * specify sufficient ML storage for your scenario.
+ *The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
* @public */ VolumeSizeInGB: number | undefined; /** - *The Key Management Service (KMS) key that Amazon SageMaker AI uses to - * encrypt data on the storage volume attached to the ML compute instance(s) that run the - * model monitoring job.
+ *The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
* @public */ VolumeKmsKeyId?: string | undefined; @@ -2954,25 +1934,19 @@ export interface MonitoringResources { */ export interface MonitoringNetworkConfig { /** - *Whether to encrypt all communications between the instances used for the monitoring
- * jobs. Choose True to encrypt communications. Encryption provides greater
- * security for distributed jobs, but the processing might take longer.
Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for - * the monitoring job.
+ *Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
* @public */ EnableNetworkIsolation?: boolean | undefined; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; @@ -2984,13 +1958,7 @@ export interface MonitoringNetworkConfig { */ export interface MonitoringStoppingCondition { /** - *The maximum runtime allowed in seconds.
- *The MaxRuntimeInSeconds cannot exceed the frequency of the job. For data
- * quality and model explainability, this can be up to 3600 seconds for an hourly schedule.
- * For model bias and model quality hourly schedules, this can be up to 1800
- * seconds.
The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
A list of inputs for the monitoring job. Currently endpoints are supported as monitoring - * inputs.
+ *A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
* @public */ DataQualityJobInput: DataQualityJobInput | undefined; @@ -3044,8 +2011,7 @@ export interface CreateDataQualityJobDefinitionRequest { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -3057,9 +2023,7 @@ export interface CreateDataQualityJobDefinitionRequest { StoppingCondition?: MonitoringStoppingCondition | undefined; /** - *(Optional) An array of key-value pairs. For more information, see - * - * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -3101,54 +2065,19 @@ export interface EdgeOutputConfig { S3OutputLocation: string | undefined; /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. - * If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
+ *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
* @public */ KmsKeyId?: string | undefined; /** - *The deployment type SageMaker Edge Manager will create. - * Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
+ *The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
* @public */ PresetDeploymentType?: EdgePresetDeploymentType | undefined; /** - *The configuration used to create deployment artifacts. - * Specify configuration options with a JSON string. The available configuration options for each type are:
- *
- * ComponentName (optional) - Name of the GreenGrass V2 component. If not specified,
- * the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager
- * packaging job.
- * ComponentDescription (optional) - Description of the component.
- * ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a - * major.minor.patch number system. For example, version 1.0.0 represents the first - * major release for a component. For more information, see the semantic version specification.
- *
- * PlatformOS (optional) - The name of the operating system for the platform.
- * Supported platforms include Windows and Linux.
- * PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
- *Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
- *The configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of "SagemakerEdgeManager" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription (optional) - Description of the component.
ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. - * The name of the role alias generated will match this pattern: - * "SageMakerEdge-\{DeviceFleetName\}".
- *For example, if your device fleet is called "demo-fleet", the name of - * the role alias will be "SageMakerEdge-demo-fleet".
+ *Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-\{DeviceFleetName\}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
* @public */ EnableIotRoleAlias?: boolean | undefined; } /** - *The settings for assigning a custom Amazon EFS file system to a user profile or - * space for an Amazon SageMaker AI Domain.
+ *The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker AI Domain.
* @public */ export interface EFSFileSystemConfig { @@ -3212,16 +2136,14 @@ export interface EFSFileSystemConfig { FileSystemId: string | undefined; /** - *The path to the file system directory that is accessible in Amazon SageMaker AI Studio. - * Permitted users can access only this directory and below.
+ *The path to the file system directory that is accessible in Amazon SageMaker AI Studio. Permitted users can access only this directory and below.
* @public */ FileSystemPath?: string | undefined; } /** - *The settings for assigning a custom Amazon FSx for Lustre file system to a user profile or space for an - * Amazon SageMaker Domain.
+ *The settings for assigning a custom Amazon FSx for Lustre file system to a user profile or space for an Amazon SageMaker Domain.
* @public */ export interface FSxLustreFileSystemConfig { @@ -3232,16 +2154,14 @@ export interface FSxLustreFileSystemConfig { FileSystemId: string | undefined; /** - *The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted - * users can access only this directory and below.
+ *The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.
* @public */ FileSystemPath?: string | undefined; } /** - *The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI - * Studio.
+ *The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
* @public */ export type CustomFileSystemConfig = @@ -3315,31 +2235,18 @@ export interface CustomPosixUserConfig { } /** - *The configuration parameters that specify the IAM roles assumed by the execution role of - * SageMaker (assumable roles) and the cluster instances or job execution environments - * (execution roles or runtime roles) to manage and access resources required for running Amazon EMR - * clusters or Amazon EMR Serverless applications.
+ *The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
* @public */ export interface EmrSettings { /** - *An array of Amazon Resource Names (ARNs) of the IAM roles that the execution role of - * SageMaker can assume for performing operations or tasks related to Amazon EMR clusters or Amazon EMR - * Serverless applications. These roles define the permissions and access policies required - * when performing Amazon EMR-related operations, such as listing, connecting to, or terminating - * Amazon EMR clusters or Amazon EMR Serverless applications. They are typically used in - * cross-account access scenarios, where the Amazon EMR resources (clusters or serverless - * applications) are located in a different Amazon Web Services account than the SageMaker - * domain.
+ *An array of Amazon Resource Names (ARNs) of the IAM roles that the execution role of SageMaker can assume for performing operations or tasks related to Amazon EMR clusters or Amazon EMR Serverless applications. These roles define the permissions and access policies required when performing Amazon EMR-related operations, such as listing, connecting to, or terminating Amazon EMR clusters or Amazon EMR Serverless applications. They are typically used in cross-account access scenarios, where the Amazon EMR resources (clusters or serverless applications) are located in a different Amazon Web Services account than the SageMaker domain.
* @public */ AssumableRoleArns?: string[] | undefined; /** - *An array of Amazon Resource Names (ARNs) of the IAM roles used by the Amazon EMR cluster instances - * or job execution environments to access other Amazon Web Services services and resources needed during the - * runtime of your Amazon EMR or Amazon EMR Serverless workloads, such as Amazon S3 for data access, Amazon CloudWatch for logging, or other - * Amazon Web Services services based on the particular workload requirements.
+ *An array of Amazon Resource Names (ARNs) of the IAM roles used by the Amazon EMR cluster instances or job execution environments to access other Amazon Web Services services and resources needed during the runtime of your Amazon EMR or Amazon EMR Serverless workloads, such as Amazon S3 for data access, Amazon CloudWatch for logging, or other Amazon Web Services services based on the particular workload requirements.
* @public */ ExecutionRoleArns?: string[] | undefined; @@ -3351,11 +2258,7 @@ export interface EmrSettings { */ export interface JupyterLabAppSettings { /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The configuration parameters that specify the IAM roles assumed by the execution role of - * SageMaker (assumable roles) and the cluster instances or job execution environments - * (execution roles or runtime roles) to manage and access resources required for running Amazon EMR - * clusters or Amazon EMR Serverless applications.
+ *The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
* @public */ EmrSettings?: EmrSettings | undefined; /** - *The lifecycle configuration that runs before the default lifecycle configuration. It can - * override changes made in the default lifecycle configuration.
+ *The lifecycle configuration that runs before the default lifecycle configuration. It can override changes made in the default lifecycle configuration.
* @public */ BuiltInLifecycleConfigArn?: string | undefined; @@ -3407,27 +2306,19 @@ export interface JupyterLabAppSettings { */ export interface JupyterServerAppSettings { /** - *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the JupyterServer app. If you use the
- * LifecycleConfigArns parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the
- * JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is
- * also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty
- * list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of Git repositories that SageMaker AI automatically displays to users for - * cloning in the JupyterServer application.
+ *A list of Git repositories that SageMaker AI automatically displays to users for cloning in the JupyterServer application.
* @public */ CodeRepositories?: CodeRepository[] | undefined; @@ -3439,42 +2330,19 @@ export interface JupyterServerAppSettings { */ export interface KernelGatewayAppSettings { /** - *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the KernelGateway app.
- *The Amazon SageMaker AI Studio UI does not use the default instance type value set - * here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not - * passed.
- *The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the KernelGateway app.
The Amazon SageMaker AI Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not passed.
A list of custom SageMaker AI images that are configured to run as a KernelGateway - * app.
- *The maximum number of custom images are as follows.
- *On a domain level: 200
- *On a space level: 5
- *On a user profile level: 5
- *A list of custom SageMaker AI images that are configured to run as a KernelGateway app.
The maximum number of custom images are as follows.
On a domain level: 200
On a space level: 5
On a user profile level: 5
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user - * profile or domain.
- *To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty
- * list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
The default settings for shared spaces that users create in the domain.
- *SageMaker applies these settings only to shared spaces. It doesn't apply them to private - * spaces.
+ *The default settings for shared spaces that users create in the domain.
SageMaker applies these settings only to shared spaces. It doesn't apply them to private spaces.
* @public */ export interface DefaultSpaceSettings { @@ -3524,8 +2390,7 @@ export interface DefaultSpaceSettings { ExecutionRole?: string | undefined; /** - *The security group IDs for the Amazon VPC that the space uses for - * communication.
+ *The security group IDs for the Amazon VPC that the space uses for communication.
* @public */ SecurityGroups?: string[] | undefined; @@ -3561,8 +2426,7 @@ export interface DefaultSpaceSettings { CustomPosixUserConfig?: CustomPosixUserConfig | undefined; /** - *The settings for assigning a custom file system to a domain. Permitted users can access - * this file system in Amazon SageMaker AI Studio.
+ *The settings for assigning a custom file system to a domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
* @public */ CustomFileSystemConfigs?: CustomFileSystemConfig[] | undefined; @@ -3574,18 +2438,13 @@ export interface DefaultSpaceSettings { */ export interface RSessionAppSettings { /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
A list of custom SageMaker AI images that are configured to run as a RSession - * app.
+ *A list of custom SageMaker AI images that are configured to run as a RSession app.
* @public */ CustomImages?: CustomImage[] | undefined; @@ -3621,22 +2480,18 @@ export const RStudioServerProUserGroup = { export type RStudioServerProUserGroup = (typeof RStudioServerProUserGroup)[keyof typeof RStudioServerProUserGroup]; /** - *A collection of settings that configure user interaction with the
- * RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
Indicates whether the current user has access to the RStudioServerPro
- * app.
Indicates whether the current user has access to the RStudioServerPro app.
The level of permissions that the user has within the RStudioServerPro app.
- * This value defaults to `User`. The `Admin` value allows the user access to the RStudio
- * Administrative Dashboard.
The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
Specifies options for sharing Amazon SageMaker AI Studio notebooks. These settings are
- * specified as part of DefaultUserSettings when the CreateDomain API
- * is called, and as part of UserSettings when the CreateUserProfile
- * API is called. When SharingSettings is not specified, notebook sharing isn't
- * allowed.
Specifies options for sharing Amazon SageMaker AI Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn't allowed.
Whether to include the notebook cell output when sharing the notebook. The default is
- * Disabled.
Whether to include the notebook cell output when sharing the notebook. The default is Disabled.
When NotebookOutputOption is Allowed, the Amazon S3
- * bucket used to store the shared notebook snapshots.
When NotebookOutputOption is Allowed, the Amazon S3 bucket used to store the shared notebook snapshots.
When NotebookOutputOption is Allowed, the Amazon Web Services Key
- * Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the
- * Amazon S3 bucket.
When NotebookOutputOption is Allowed, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
The SageMaker images that are hidden from the Studio user interface. You must specify the SageMaker - * image name and version aliases.
+ *The SageMaker images that are hidden from the Studio user interface. You must specify the SageMaker image name and version aliases.
* @public */ export interface HiddenSageMakerImage { @@ -3767,8 +2613,7 @@ export interface HiddenSageMakerImage { } /** - *Studio settings. If these settings are applied on a user level, they take priority over - * the settings applied on a domain level.
+ *Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
* @public */ export interface StudioWebPortalSettings { @@ -3779,8 +2624,7 @@ export interface StudioWebPortalSettings { HiddenMlTools?: MlTools[] | undefined; /** - *The Applications supported in Studio that are hidden from the Studio left navigation - * pane.
+ *The Applications supported in Studio that are hidden from the Studio left navigation pane.
* @public */ HiddenAppTypes?: AppType[] | undefined; @@ -3804,42 +2648,25 @@ export interface StudioWebPortalSettings { */ export interface TensorBoardAppSettings { /** - *The default instance type and the Amazon Resource Name (ARN) of the SageMaker AI - * image created on the instance.
+ *The default instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
* @public */ DefaultResourceSpec?: ResourceSpec | undefined; } /** - *A collection of settings that apply to users in a domain. These settings are specified
- * when the CreateUserProfile API is called, and as DefaultUserSettings
- * when the CreateDomain API is called.
- * SecurityGroups is aggregated when specified in both calls. For all other
- * settings in UserSettings, the values specified in CreateUserProfile
- * take precedence over those specified in CreateDomain.
A collection of settings that apply to users in a domain. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the CreateDomain API is called.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
The execution role for the user.
- *SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
+ *The execution role for the user.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
* @public */ ExecutionRole?: string | undefined; /** - *The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for - * communication.
- *Optional when the CreateDomain.AppNetworkAccessType parameter is set to
- * PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to
- * VpcOnly, unless specified as part of the DefaultUserSettings for
- * the domain.
Amazon SageMaker AI adds a security group to allow NFS traffic from Amazon SageMaker AI Studio. Therefore, the number of security groups that you can specify is one less than the - * maximum number shown.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.
Amazon SageMaker AI adds a security group to allow NFS traffic from Amazon SageMaker AI Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ SecurityGroups?: string[] | undefined; @@ -3869,8 +2696,7 @@ export interface UserSettings { TensorBoardAppSettings?: TensorBoardAppSettings | undefined; /** - *A collection of settings that configure user interaction with the
- * RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
The Canvas app settings.
- *SageMaker applies these settings only to private spaces that SageMaker creates for the Canvas - * app.
+ *The Canvas app settings.
SageMaker applies these settings only to private spaces that SageMaker creates for the Canvas app.
* @public */ CanvasAppSettings?: CanvasAppSettings | undefined; /** - *The Code Editor application settings.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *The Code Editor application settings.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ CodeEditorAppSettings?: CodeEditorAppSettings | undefined; /** - *The settings for the JupyterLab application.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *The settings for the JupyterLab application.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ JupyterLabAppSettings?: JupyterLabAppSettings | undefined; /** - *The storage settings for a space.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *The storage settings for a space.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ SpaceStorageSettings?: DefaultSpaceStorageSettings | undefined; /** - *The default experience that the user is directed to when accessing the domain. The - * supported values are:
- *
- * studio::: Indicates that Studio is the default experience. This value can
- * only be passed if StudioWebPortal is set to ENABLED.
- * app:JupyterServer:: Indicates that Studio Classic is the default
- * experience.
The default experience that the user is directed to when accessing the domain. The supported values are:
studio::: Indicates that Studio is the default experience. This value can only be passed if StudioWebPortal is set to ENABLED.
app:JupyterServer:: Indicates that Studio Classic is the default experience.
Whether the user can access Studio. If this value is set to DISABLED, the
- * user cannot access Studio, even if that is the default experience for the domain.
Whether the user can access Studio. If this value is set to DISABLED, the user cannot access Studio, even if that is the default experience for the domain.
Details about the POSIX identity that is used for file system operations.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *Details about the POSIX identity that is used for file system operations.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ CustomPosixUserConfig?: CustomPosixUserConfig | undefined; /** - *The settings for assigning a custom file system to a user profile. Permitted users can - * access this file system in Amazon SageMaker AI Studio.
- *SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
+ *The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker AI Studio.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
* @public */ CustomFileSystemConfigs?: CustomFileSystemConfig[] | undefined; /** - *Studio settings. If these settings are applied on a user level, they take priority over - * the settings applied on a domain level.
+ *Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
* @public */ StudioWebPortalSettings?: StudioWebPortalSettings | undefined; /** - *Indicates whether auto-mounting of an EFS volume is supported for the user profile. The
- * DefaultAsDomain value is only supported for user profiles. Do not use the
- * DefaultAsDomain value when setting this parameter for a domain.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
+ *Indicates whether auto-mounting of an EFS volume is supported for the user profile. The DefaultAsDomain value is only supported for user profiles. Do not use the DefaultAsDomain value when setting this parameter for a domain.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
* @public */ AutoMountHomeEFS?: AutoMountHomeEFS | undefined; @@ -3980,8 +2780,7 @@ export interface DockerSettings { EnableDockerAccess?: FeatureStatus | undefined; /** - *The list of Amazon Web Services accounts that are trusted when the domain is created in - * VPC-only mode.
+ *The list of Amazon Web Services accounts that are trusted when the domain is created in VPC-only mode.
* @public */ VpcOnlyTrustedAccounts?: string[] | undefined; @@ -4003,14 +2802,12 @@ export type ExecutionRoleIdentityConfig = (typeof ExecutionRoleIdentityConfig)[keyof typeof ExecutionRoleIdentityConfig]; /** - *A collection of settings that configure the RStudioServerPro Domain-level
- * app.
A collection of settings that configure the RStudioServerPro Domain-level app.
The ARN of the execution role for the RStudioServerPro Domain-level
- * app.
The ARN of the execution role for the RStudioServerPro Domain-level app.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The settings that apply to an Amazon SageMaker AI domain when you use it in Amazon - * SageMaker Unified Studio.
+ *The settings that apply to an Amazon SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
* @public */ export interface UnifiedStudioSettings { /** - *Sets whether you can access the domain in Amazon SageMaker Studio:
- *You can access the domain in Amazon SageMaker Studio. If you migrate the domain to - * Amazon SageMaker Unified Studio, you can access it in both studio interfaces.
- *You can't access the domain in Amazon SageMaker Studio. If you migrate the domain to - * Amazon SageMaker Unified Studio, you can access it only in that studio interface.
- *To migrate a domain to Amazon SageMaker Unified Studio, you specify the - * UnifiedStudioSettings data type when you use the UpdateDomain action.
+ *Sets whether you can access the domain in Amazon SageMaker Studio:
You can access the domain in Amazon SageMaker Studio. If you migrate the domain to Amazon SageMaker Unified Studio, you can access it in both studio interfaces.
You can't access the domain in Amazon SageMaker Studio. If you migrate the domain to Amazon SageMaker Unified Studio, you can access it only in that studio interface.
To migrate a domain to Amazon SageMaker Unified Studio, you specify the UnifiedStudioSettings data type when you use the UpdateDomain action.
* @public */ StudioWebPortalAccess?: FeatureStatus | undefined; /** - *The ID of the Amazon Web Services account that has the Amazon SageMaker Unified Studio - * domain. The default value, if you don't specify an ID, is the ID of the account that has the - * Amazon SageMaker AI domain.
+ *The ID of the Amazon Web Services account that has the Amazon SageMaker Unified Studio domain. The default value, if you don't specify an ID, is the ID of the account that has the Amazon SageMaker AI domain.
* @public */ DomainAccountId?: string | undefined; /** - *The Amazon Web Services Region where the domain is located in Amazon SageMaker Unified - * Studio. The default value, if you don't specify a Region, is the Region where the Amazon SageMaker AI domain is located.
+ *The Amazon Web Services Region where the domain is located in Amazon SageMaker Unified Studio. The default value, if you don't specify a Region, is the Region where the Amazon SageMaker AI domain is located.
* @public */ DomainRegion?: string | undefined; @@ -4086,50 +2861,43 @@ export interface UnifiedStudioSettings { DomainId?: string | undefined; /** - *The ID of the Amazon SageMaker Unified Studio project that corresponds to the - * domain.
+ *The ID of the Amazon SageMaker Unified Studio project that corresponds to the domain.
* @public */ ProjectId?: string | undefined; /** - *The ID of the environment that Amazon SageMaker Unified Studio associates with the - * domain.
+ *The ID of the environment that Amazon SageMaker Unified Studio associates with the domain.
* @public */ EnvironmentId?: string | undefined; /** - *The location where Amazon S3 stores temporary execution data and other artifacts - * for the project that corresponds to the domain.
+ *The location where Amazon S3 stores temporary execution data and other artifacts for the project that corresponds to the domain.
* @public */ ProjectS3Path?: string | undefined; } /** - *A collection of settings that apply to the SageMaker Domain. These settings
- * are specified through the CreateDomain API call.
A collection of settings that apply to the SageMaker Domain. These settings are specified through the CreateDomain API call.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for
- * communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
A collection of settings that configure the RStudioServerPro Domain-level
- * app.
A collection of settings that configure the RStudioServerPro Domain-level app.
The configuration for attaching a SageMaker AI user profile name to the execution - * role as a sts:SourceIdentity key.
+ *The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key.
* @public */ ExecutionRoleIdentityConfig?: ExecutionRoleIdentityConfig | undefined; @@ -4141,15 +2909,13 @@ export interface DomainSettings { DockerSettings?: DockerSettings | undefined; /** - *A collection of settings that configure the Amazon Q experience within the domain. The
- * AuthMode that you use to create the domain must be SSO.
A collection of settings that configure the Amazon Q experience within the domain. The AuthMode that you use to create the domain must be SSO.
The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker - * Unified Studio.
+ *The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
* @public */ UnifiedStudioSettings?: UnifiedStudioSettings | undefined; @@ -4186,12 +2952,7 @@ export interface CreateDomainRequest { AuthMode: AuthMode | undefined; /** - *The default settings to use to create a user profile when UserSettings isn't
- * specified in the call to the CreateUserProfile API.
- * SecurityGroups is aggregated when specified in both calls. For all other
- * settings in UserSettings, the values specified in CreateUserProfile
- * take precedence over those specified in CreateDomain.
The default settings to use to create a user profile when UserSettings isn't specified in the call to the CreateUserProfile API.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag
- * keys must be unique per resource. Tags are searchable using the Search
- * API.
Tags that you specify for the Domain are also added to all Apps that the Domain - * launches.
+ *Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
* @public */ Tags?: Tag[] | undefined; /** - *Specifies the VPC used for non-EFS traffic. The default value is
- * PublicInternetOnly.
- * PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
- * VpcOnly - All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
VpcOnly - All traffic is through the specified VPC and subnets
SageMaker AI uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to - * the domain with an Amazon Web Services managed key by default. For more control, specify a - * customer managed key.
+ *SageMaker AI uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
* @public */ KmsKeyId?: string | undefined; /** - *The entity that creates and manages the required security groups for inter-app
- * communication in VPCOnly mode. Required when
- * CreateDomain.AppNetworkAccessType is VPCOnly and
- * DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is
- * provided. If setting up the domain for use with RStudio, this value must be set to
- * Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
Indicates whether custom tag propagation is supported for the domain. Defaults to
- * DISABLED.
Indicates whether custom tag propagation is supported for the domain. Defaults to DISABLED.
Toggle that determines whether to rollback to previous configuration if the current - * deployment fails. By default this is turned on. You may turn this off if you want to - * investigate the errors yourself.
+ *Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
* @public */ FailureHandlingPolicy: FailureHandlingPolicy | undefined; @@ -4443,8 +3179,7 @@ export interface CreateEdgeDeploymentPlanRequest { DeviceFleetName: string | undefined; /** - *List of stages of the edge deployment plan. The number of stages is limited to 10 per - * deployment.
+ *List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
* @public */ Stages?: DeploymentStage[] | undefined; @@ -4543,16 +3278,13 @@ export interface CreateEdgePackagingJobRequest { */ export interface RollingUpdatePolicy { /** - *Batch size for each rolling step to provision capacity and turn on traffic on the new - * endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between - * 5% to 50% of the variant's total instance count.
+ *Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant's total instance count.
* @public */ MaximumBatchSize: CapacitySize | undefined; /** - *The length of the baking period, during which SageMaker monitors alarms for each batch on - * the new fleet.
+ *The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
* @public */ WaitIntervalInSeconds: number | undefined; @@ -4564,29 +3296,19 @@ export interface RollingUpdatePolicy { MaximumExecutionTimeoutInSeconds?: number | undefined; /** - *Batch size for rollback to the old endpoint fleet. Each rolling step to provision - * capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the - * new endpoint fleet. If this field is absent, the default value will be set to 100% of - * total capacity which means to bring up the whole capacity of the old fleet at once - * during rollback.
+ *Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
* @public */ RollbackMaximumBatchSize?: CapacitySize | undefined; } /** - *The deployment configuration for an endpoint, which contains the desired deployment - * strategy and rollback configurations.
+ *The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
* @public */ export interface DeploymentConfig { /** - *Update policy for a blue/green deployment. If this update policy is specified, SageMaker - * creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips - * traffic to the new fleet according to the specified traffic routing configuration. Only - * one update policy should be used in the deployment configuration. If no update policy is - * specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting - * by default.
+ *Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
* @public */ BlueGreenUpdatePolicy?: BlueGreenUpdatePolicy | undefined; @@ -4598,8 +3320,7 @@ export interface DeploymentConfig { RollingUpdatePolicy?: RollingUpdatePolicy | undefined; /** - *Automatic rollback configuration for handling endpoint deployment failures and - * recovery.
+ *Automatic rollback configuration for handling endpoint deployment failures and recovery.
* @public */ AutoRollbackConfiguration?: AutoRollbackConfig | undefined; @@ -4610,9 +3331,7 @@ export interface DeploymentConfig { */ export interface CreateEndpointInput { /** - *The name of the endpoint.The name must be unique within an Amazon Web Services
- * Region in your Amazon Web Services account. The name is case-insensitive in
- * CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
The deployment configuration for an endpoint, which contains the desired deployment - * strategy and rollback configurations.
+ *The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
* @public */ DeploymentConfig?: DeploymentConfig | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -4662,8 +3378,7 @@ export interface DataCaptureConfig { EnableCapture?: boolean | undefined; /** - *The percentage of requests SageMaker AI will capture. A lower value is recommended - * for Endpoints with high traffic.
+ *The percentage of requests SageMaker AI will capture. A lower value is recommended for Endpoints with high traffic.
* @public */ InitialSamplingPercentage: number | undefined; @@ -4675,44 +3390,19 @@ export interface DataCaptureConfig { DestinationS3Uri: string | undefined; /** - *The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI - * uses to encrypt the captured data at rest using Amazon S3 server-side - * encryption.
- *The KmsKeyId can be any of the following formats:
- *Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Specifies data Model Monitor will capture. You can configure whether to collect only - * input, only output, or both
+ *Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
* @public */ CaptureOptions: CaptureOption[] | undefined; /** - *Configuration specifying how to treat different headers. If no headers are specified - * SageMaker AI will by default base64 encode when capturing the data.
+ *Configuration specifying how to treat different headers. If no headers are specified SageMaker AI will by default base64 encode when capturing the data.
* @public */ CaptureContentTypeHeader?: CaptureContentTypeHeader | undefined; @@ -4724,8 +3414,7 @@ export interface DataCaptureConfig { */ export interface ExplainerConfig { /** - *A member of ExplainerConfig that contains configuration parameters for
- * the SageMaker Clarify explainer.
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
Specifies configuration for a core dump from the model container when the process - * crashes.
+ *Specifies configuration for a core dump from the model container when the process crashes.
* @public */ export interface ProductionVariantCoreDumpConfig { @@ -4763,49 +3451,7 @@ export interface ProductionVariantCoreDumpConfig { DestinationS3Uri: string | undefined; /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker
- * uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The
- * KmsKeyId can be any of the following formats:
// KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// KMS Key Alias
- *
- * "alias/ExampleAlias"
- *
// Amazon Resource Name (ARN) of a KMS Key Alias
- *
- * "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
- *
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must
- * include permissions to call kms:Encrypt. If you don't provide a KMS key ID,
- * SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side
- * encryption with KMS-managed keys for OutputDataConfig. If you use a bucket
- * policy with an s3:PutObject permission that only allows objects with
- * server-side encryption, set the condition key of
- * s3:x-amz-server-side-encryption to "aws:kms". For more
- * information, see KMS-Managed Encryption
- * Keys in the Amazon Simple Storage Service Developer Guide.
- *
The KMS key policy must grant permission to the IAM role that you specify in your
- * CreateEndpoint and UpdateEndpoint requests. For more
- * information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management
- * Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
Settings that control the range in the number of instances that the endpoint provisions - * as it scales up or down to accommodate traffic.
+ *Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
* @public */ export interface ProductionVariantManagedInstanceScaling { @@ -4856,15 +3501,13 @@ export interface ProductionVariantManagedInstanceScaling { Status?: ManagedInstanceScalingStatus | undefined; /** - *The minimum number of instances that the endpoint must retain when it scales down to - * accommodate a decrease in traffic.
+ *The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic.
* @public */ MinInstanceCount?: number | undefined; /** - *The maximum number of instances that the endpoint can provision when it scales up to - * accommodate an increase in traffic.
+ *The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic.
* @public */ MaxInstanceCount?: number | undefined; @@ -4885,25 +3528,12 @@ export const RoutingStrategy = { export type RoutingStrategy = (typeof RoutingStrategy)[keyof typeof RoutingStrategy]; /** - *Settings that control how the endpoint routes incoming traffic to the instances that the - * endpoint hosts.
+ *Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
* @public */ export interface ProductionVariantRoutingConfig { /** - *Sets how the endpoint routes incoming traffic:
- *
- * LEAST_OUTSTANDING_REQUESTS: The endpoint routes requests to the
- * specific instances that have more capacity to process them.
- * RANDOM: The endpoint routes each request to a randomly chosen
- * instance.
Sets how the endpoint routes incoming traffic:
LEAST_OUTSTANDING_REQUESTS: The endpoint routes requests to the specific instances that have more capacity to process them.
RANDOM: The endpoint routes each request to a randomly chosen instance.
The amount of provisioned concurrency to allocate for the serverless endpoint.
- * Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. - * For more information about creating an Inference Recommender job, see - * CreateInferenceRecommendationsJobs.
- *The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
Identifies a model that you want to host and the resources chosen to deploy for - * hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic - * among the models by specifying variant weights. For more information on production - * variants, check Production variants. - *
+ *Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
* @public */ export interface ProductionVariant { @@ -4955,8 +3575,7 @@ export interface ProductionVariant { VariantName: string | undefined; /** - *The name of the model that you want to host. This is the name that you specified - * when creating the model.
+ *The name of the model that you want to host. This is the name that you specified when creating the model.
* @public */ ModelName?: string | undefined; @@ -4974,27 +3593,19 @@ export interface ProductionVariant { InstanceType?: ProductionVariantInstanceType | undefined; /** - *Determines initial traffic distribution among all of the models that you specify in
- * the endpoint configuration. The traffic to a production variant is determined by the
- * ratio of the VariantWeight to the sum of all VariantWeight
- * values across all ProductionVariants. If unspecified, it defaults to 1.0.
- *
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify the size of the EI instance to use for the - * production variant.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify the size of the EI instance to use for the production variant.
* @public */ AcceleratorType?: ProductionVariantAcceleratorType | undefined; /** - *Specifies configuration for a core dump from the model container when the process - * crashes.
+ *Specifies configuration for a core dump from the model container when the process crashes.
* @public */ CoreDumpConfig?: ProductionVariantCoreDumpConfig | undefined; @@ -5006,122 +3617,43 @@ export interface ProductionVariant { ServerlessConfig?: ProductionVariantServerlessConfig | undefined; /** - *The size, in GB, of the ML storage volume attached to individual inference instance - * associated with the production variant. Currently only Amazon EBS gp2 storage volumes are - * supported.
+ *The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
* @public */ VolumeSizeInGB?: number | undefined; /** - *The timeout value, in seconds, to download and extract the model that you want to host - * from Amazon S3 to the individual inference instance associated with this production - * variant.
+ *The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
* @public */ ModelDataDownloadTimeoutInSeconds?: number | undefined; /** - *The timeout value, in seconds, for your inference container to pass health check by - * SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
+ *The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
* @public */ ContainerStartupHealthCheckTimeoutInSeconds?: number | undefined; /** - * You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM)
- * access for a production variant behind an endpoint. By default, SSM access is disabled
- * for all production variants behind an endpoint. You can turn on or turn off SSM access
- * for a production variant behind an existing endpoint by creating a new endpoint
- * configuration and calling UpdateEndpoint.
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
Settings that control the range in the number of instances that the endpoint provisions - * as it scales up or down to accommodate traffic.
+ *Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
* @public */ ManagedInstanceScaling?: ProductionVariantManagedInstanceScaling | undefined; /** - *Settings that control how the endpoint routes incoming traffic to the instances that the - * endpoint hosts.
+ *Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
* @public */ RoutingConfig?: ProductionVariantRoutingConfig | undefined; /** - *Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) - * images. Each image is configured by Amazon Web Services with a set of software and driver - * versions. Amazon Web Services optimizes these configurations for different machine - * learning workloads.
- *By selecting an AMI version, you can ensure that your inference environment is - * compatible with specific software requirements, such as CUDA driver versions, Linux - * kernel versions, or Amazon Web Services Neuron driver versions.
- *The AMI version names, and their configurations, are the following:
- *Accelerator: GPU
- *NVIDIA driver version: 535
- *CUDA version: 12.2
- *Accelerator: GPU
- *NVIDIA driver version: 535
- *CUDA version: 12.2
- *NVIDIA Container Toolkit with disabled CUDA-compat mounting
- *Accelerator: GPU
- *NVIDIA driver version: 550
- *CUDA version: 12.4
- *NVIDIA Container Toolkit with disabled CUDA-compat mounting
- *Accelerator: Inferentia2 and Trainium
- *Neuron driver version: 2.19
- *Specifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions. Amazon Web Services optimizes these configurations for different machine learning workloads.
By selecting an AMI version, you can ensure that your inference environment is compatible with specific software requirements, such as CUDA driver versions, Linux kernel versions, or Amazon Web Services Neuron driver versions.
The AMI version names, and their configurations, are the following:
Accelerator: GPU
NVIDIA driver version: 535
CUDA version: 12.2
Accelerator: GPU
NVIDIA driver version: 535
CUDA version: 12.2
NVIDIA Container Toolkit with disabled CUDA-compat mounting
Accelerator: GPU
NVIDIA driver version: 550
CUDA version: 12.4
NVIDIA Container Toolkit with disabled CUDA-compat mounting
Accelerator: Inferentia2 and Trainium
Neuron driver version: 2.19
An array of ProductionVariant objects, one for each model that you want
- * to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; /** - *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that - * SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that - * hosts the endpoint.
- *The KmsKeyId can be any of the following formats:
- *Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
- *
Key ARN:
- * arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
- *
Alias name: alias/ExampleAlias
- *
Alias name ARN:
- * arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
- *
The KMS key policy must grant permission to the IAM role that you specify in your
- * CreateEndpoint, UpdateEndpoint requests. For more
- * information, refer to the Amazon Web Services Key Management Service section Using Key
- * Policies in Amazon Web Services KMS
- *
Certain Nitro-based instances include local storage, dependent on the instance
- * type. Local storage volumes are encrypted using a hardware module on the instance.
- * You can't request a KmsKeyId when using an instance type with local
- * storage. If any of the models that you specify in the
- * ProductionVariants parameter use nitro-based instances with local
- * storage, do not specify a value for the KmsKeyId parameter. If you
- * specify a value for KmsKeyId when using any nitro-based instances with
- * local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
- *For more information about local instance storage encryption, see SSD - * Instance Store Volumes.
- *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
Specifies configuration for how an endpoint performs asynchronous inference. This is a - * required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
+ *Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
* @public */ AsyncInferenceConfig?: AsyncInferenceConfig | undefined; @@ -5219,38 +3706,25 @@ export interface CreateEndpointConfigInput { ExplainerConfig?: ExplainerConfig | undefined; /** - *An array of ProductionVariant objects, one for each model that you want
- * to host at this endpoint in shadow mode with production traffic replicated from the
- * model specified on ProductionVariants. If you use this field, you can only
- * specify one variant for ProductionVariants and one variant for
- * ShadowProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI - * Roles.
- *To be able to pass this role to Amazon SageMaker AI, the caller of this action must
- * have the iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.
To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Sets whether all model containers deployed to the endpoint are isolated. If they are, no - * inbound or outbound network calls can be made to or from the model containers.
+ *Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
* @public */ EnableNetworkIsolation?: boolean | undefined; @@ -5272,16 +3746,13 @@ export interface CreateEndpointConfigOutput { */ export interface CreateExperimentRequest { /** - *The name of the experiment. The name must be unique in your Amazon Web Services account and is not - * case-sensitive.
+ *The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
* @public */ ExperimentName: string | undefined; /** - *The name of the experiment as displayed. The name doesn't need to be unique. If you don't
- * specify DisplayName, the value in ExperimentName is
- * displayed.
The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify DisplayName, the value in ExperimentName is displayed.
A list of tags to associate with the experiment. You can use Search API - * to search on the tags.
+ *A list of tags to associate with the experiment. You can use Search API to search on the tags.
* @public */ Tags?: Tag[] | undefined; @@ -5327,26 +3797,12 @@ export const FeatureType = { export type FeatureType = (typeof FeatureType)[keyof typeof FeatureType]; /** - *A list of features. You must include FeatureName and
- * FeatureType. Valid feature FeatureTypes are
- * Integral, Fractional and String.
A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.
The name of a feature. The type must be a string. FeatureName cannot be any
- * of the following: is_deleted, write_time,
- * api_invocation_time.
The name:
- *Must start with an alphanumeric character.
- *Can only include alphanumeric characters, underscores, and hyphens. Spaces are not - * allowed.
- *The name of a feature. The type must be a string. FeatureName cannot be any of the following: is_deleted, write_time, api_invocation_time.
The name:
Must start with an alphanumeric character.
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
A grouping of elements where each element within the collection must have the same
- * feature type (String, Integral, or
- * Fractional).
- * List: An ordered collection of elements.
- * Set: An unordered collection of unique elements.
- * Vector: A specialized list that represents a fixed-size array of
- * elements. The vector dimension is determined by you. Must have elements with
- * fractional feature types.
A grouping of elements where each element within the collection must have the same feature type (String, Integral, or Fractional).
List: An ordered collection of elements.
Set: An unordered collection of unique elements.
Vector: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
The meta data of the Glue table which serves as data catalog for the
- * OfflineStore.
The meta data of the Glue table which serves as data catalog for the OfflineStore.
The Amazon Simple Storage (Amazon S3) location and security configuration for
- * OfflineStore.
The Amazon Simple Storage (Amazon S3) location and security configuration for OfflineStore.
The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following:
- * s3://example-bucket/prefix/.
The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/.
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt
- * any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to
- * CreateFeatureGroup must have below permissions to the
- * KmsKeyId:
- * "kms:GenerateDataKey"
- *
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to CreateFeatureGroup must have below permissions to the KmsKeyId:
"kms:GenerateDataKey"
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to
- * CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in
- * S3StorageConfig.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
Set to True to disable the automatic creation of an Amazon Web Services Glue
- * table when configuring an OfflineStore. If set to False, Feature
- * Store will name the OfflineStore Glue table following Athena's
- * naming recommendations.
The default value is False.
Set to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore. If set to False, Feature Store will name the OfflineStore Glue table following Athena's naming recommendations.
The default value is False.
The meta data of the Glue table that is autogenerated when an OfflineStore
- * is created.
The meta data of the Glue table that is autogenerated when an OfflineStore is created.
The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store - * uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side - * encryption.
- *The caller (either user or IAM role) of CreateFeatureGroup must have below
- * permissions to the OnlineStore
- * KmsKeyId:
- * "kms:Encrypt"
- *
- * "kms:Decrypt"
- *
- * "kms:DescribeKey"
- *
- * "kms:CreateGrant"
- *
- * "kms:RetireGrant"
- *
- * "kms:ReEncryptFrom"
- *
- * "kms:ReEncryptTo"
- *
- * "kms:GenerateDataKey"
- *
- * "kms:ListAliases"
- *
- * "kms:ListGrants"
- *
- * "kms:RevokeGrant"
- *
The caller (either user or IAM role) to all DataPlane operations
- * (PutRecord, GetRecord, DeleteRecord) must have the
- * following permissions to the KmsKeyId:
- * "kms:Decrypt"
- *
The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup must have below permissions to the OnlineStore KmsKeyId:
"kms:Encrypt"
"kms:Decrypt"
"kms:DescribeKey"
"kms:CreateGrant"
"kms:RetireGrant"
"kms:ReEncryptFrom"
"kms:ReEncryptTo"
"kms:GenerateDataKey"
"kms:ListAliases"
"kms:ListGrants"
"kms:RevokeGrant"
The caller (either user or IAM role) to all DataPlane operations (PutRecord, GetRecord, DeleteRecord) must have the following permissions to the KmsKeyId:
"kms:Decrypt"
Time to live duration, where the record is hard deleted after the expiration time is
- * reached; ExpiresAt = EventTime + TtlDuration. For
- * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
- * TtlDuration time unit.
TtlDuration time unit.
- * TtlDuration time value.
TtlDuration time value.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or
- * KMSKeyId, for at rest data encryption. You can turn
- * OnlineStore on or off by specifying the EnableOnlineStore flag
- * at General Assembly.
The default value is False.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly.
The default value is False.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your
- * OnlineStore.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your OnlineStore.
Turn OnlineStore off by specifying False for the
- * EnableOnlineStore flag. Turn OnlineStore on by specifying
- * True for the EnableOnlineStore flag.
The default value is False.
Turn OnlineStore off by specifying False for the EnableOnlineStore flag. Turn OnlineStore on by specifying True for the EnableOnlineStore flag.
The default value is False.
Time to live duration, where the record is hard deleted after the expiration time is
- * reached; ExpiresAt = EventTime + TtlDuration. For
- * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Option for different tiers of low latency storage for real-time data retrieval.
- *
- * Standard: A managed low latency data store for feature groups.
- * InMemory: A managed data store for feature groups that supports very
- * low latency retrieval.
Option for different tiers of low latency storage for real-time data retrieval.
Standard: A managed low latency data store for feature groups.
InMemory: A managed data store for feature groups that supports very low latency retrieval.
Used to set feature group throughput configuration. There are two modes:
- * ON_DEMAND and PROVISIONED. With on-demand mode, you are
- * charged for data reads and writes that your application performs on your feature group. You
- * do not need to specify read and write throughput because Feature Store accommodates your
- * workloads as they ramp up and down. You can switch a feature group to on-demand only once
- * in a 24 hour period. With provisioned throughput mode, you specify the read and write
- * capacity per second that you expect your application to require, and you are billed based
- * on those limits. Exceeding provisioned throughput will result in your requests being
- * throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that
- * are offline-only, or use the
- * Standard
- * tier online store.
Used to set feature group throughput configuration. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
The mode used for your feature group throughput: ON_DEMAND or
- * PROVISIONED.
The mode used for your feature group throughput: ON_DEMAND or PROVISIONED.
For provisioned feature groups with online store enabled, this indicates the read - * throughput you are billed for and can consume without throttling.
- *This field is not applicable for on-demand feature groups.
+ *For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
* @public */ ProvisionedReadCapacityUnits?: number | undefined; /** - *For provisioned feature groups, this indicates the write throughput you are billed for - * and can consume without throttling.
- *This field is not applicable for on-demand feature groups.
+ *For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
* @public */ ProvisionedWriteCapacityUnits?: number | undefined; @@ -5753,147 +4053,49 @@ export interface ThroughputConfig { */ export interface CreateFeatureGroupRequest { /** - *The name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
The name:
- *Must start with an alphanumeric character.
- *Can only include alphanumeric characters, underscores, and hyphens. Spaces are not - * allowed.
- *The name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
The name:
Must start with an alphanumeric character.
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
The name of the Feature whose value uniquely identifies a
- * Record defined in the FeatureStore. Only the latest record per
- * identifier value will be stored in the OnlineStore.
- * RecordIdentifierFeatureName must be one of feature definitions'
- * names.
You use the RecordIdentifierFeatureName to access data in a
- * FeatureStore.
This name:
- *Must start with an alphanumeric character.
- *Can only contains alphanumeric characters, hyphens, underscores. Spaces are not - * allowed.
- *The name of the Feature whose value uniquely identifies a Record defined in the FeatureStore. Only the latest record per identifier value will be stored in the OnlineStore. RecordIdentifierFeatureName must be one of feature definitions' names.
You use the RecordIdentifierFeatureName to access data in a FeatureStore.
This name:
Must start with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime of a Record
- * in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to
- * the creation or update of a Record in a FeatureGroup. All
- * Records in the FeatureGroup must have a corresponding
- * EventTime.
An EventTime can be a String or Fractional.
- * Fractional: EventTime feature values must be a Unix
- * timestamp in seconds.
- * String: EventTime feature values must be an ISO-8601
- * string in the format. The following formats are supported
- * yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ
- * where yyyy, MM, and dd represent the year,
- * month, and day respectively and HH, mm, ss,
- * and if applicable, SSS represent the hour, month, second and
- * milliseconds respsectively. 'T' and Z are constants.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
An EventTime can be a String or Fractional.
Fractional: EventTime feature values must be a Unix timestamp in seconds.
String: EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.
A list of Feature names and types. Name and Type
- * is compulsory per Feature.
Valid feature FeatureTypes are Integral,
- * Fractional and String.
- * FeatureNames cannot be any of the following: is_deleted,
- * write_time, api_invocation_time
- *
You can create up to 2,500 FeatureDefinitions per
- * FeatureGroup.
A list of Feature names and types. Name and Type is compulsory per Feature.
Valid feature FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
You can turn the OnlineStore on or off by specifying True for
- * the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for
- * at-rest encryption of the OnlineStore.
The default value is False.
You can turn the OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for at-rest encryption of the OnlineStore.
The default value is False.
Use this to configure an OfflineFeatureStore. This parameter allows you to
- * specify:
The Amazon Simple Storage Service (Amazon S3) location of an
- * OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data - * catalog.
- *An KMS encryption key to encrypt the Amazon S3 location used for
- * OfflineStore. If KMS encryption key is not specified, by default we
- * encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level
- * key for SSE, you can reduce Amazon Web Services KMS requests costs by up to
- * 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and - * Apache Iceberg.
- *To learn more about this parameter, see OfflineStoreConfig.
+ *Use this to configure an OfflineFeatureStore. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
* @public */ OfflineStoreConfig?: OfflineStoreConfig | undefined; /** - *Used to set feature group throughput configuration. There are two modes:
- * ON_DEMAND and PROVISIONED. With on-demand mode, you are
- * charged for data reads and writes that your application performs on your feature group. You
- * do not need to specify read and write throughput because Feature Store accommodates your
- * workloads as they ramp up and down. You can switch a feature group to on-demand only once
- * in a 24 hour period. With provisioned throughput mode, you specify the read and write
- * capacity per second that you expect your application to require, and you are billed based
- * on those limits. Exceeding provisioned throughput will result in your requests being
- * throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that
- * are offline-only, or use the
- * Standard
- * tier online store.
Used to set feature group throughput configuration. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the
- * OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique
- * identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique identifier for the feature group.
Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required - * format of activation conditions.
+ *Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
* @public */ export interface HumanLoopActivationConditionsConfig { /** - *JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. - * The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see - * JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI - * in the Amazon SageMaker Developer Guide.
+ *JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
* @public */ HumanLoopActivationConditions: __AutomaticJsonStringConversion | string | undefined; @@ -5945,8 +4142,7 @@ export interface HumanLoopActivationConditionsConfig { */ export interface HumanLoopActivationConfig { /** - *Container structure for defining under what conditions SageMaker creates a human - * loop.
+ *Container structure for defining under what conditions SageMaker creates a human loop.
* @public */ HumanLoopActivationConditionsConfig: HumanLoopActivationConditionsConfig | undefined; @@ -5977,308 +4173,7 @@ export interface USD { } /** - *Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
- *Use one of the following prices for bounding box tasks. Prices are in US dollars and - * should be based on the complexity of the task; the longer it takes in your initial - * testing, the more you should offer.
- *0.036
- *0.048
- *0.060
- *0.072
- *0.120
- *0.240
- *0.360
- *0.480
- *0.600
- *0.720
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for image classification, text classification, and - * custom tasks. Prices are in US dollars.
- *0.012
- *0.024
- *0.036
- *0.048
- *0.060
- *0.072
- *0.120
- *0.240
- *0.360
- *0.480
- *0.600
- *0.720
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for semantic segmentation tasks. Prices are in US - * dollars.
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon - * Augmented AI review tasks. Prices are in US dollars.
- *2.400
- *2.280
- *2.160
- *2.040
- *1.920
- *1.800
- *1.680
- *1.560
- *1.440
- *1.320
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Use one of the following prices for Rekognition DetectModerationLabels Amazon - * Augmented AI review tasks. Prices are in US dollars.
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Use one of the following prices for Amazon Augmented AI custom human review tasks. - * Prices are in US dollars.
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Amazon Resource Name (ARN) of a team of workers. To learn more about the types of - * workforces and work teams you can create and use with Amazon A2I, see Create - * and Manage Workforces.
+ *Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
* @public */ WorkteamArn: string | undefined; /** - *The Amazon Resource Name (ARN) of the human task user interface.
- *You can use standard HTML and Crowd HTML Elements to create a custom worker task - * template. You use this template to create a human task UI.
- *To learn how to create a custom HTML template, see Create Custom Worker - * Task Template.
- *To learn how to create a human task UI, which is a worker task template that can be used - * in a flow definition, see Create and Delete a Worker Task Templates.
+ *The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
* @public */ HumanTaskUiArn: string | undefined; @@ -6327,10 +4214,7 @@ export interface HumanLoopConfig { TaskDescription: string | undefined; /** - *The number of distinct workers who will perform the same task on each object.
- * For example, if TaskCount is set to 3 for an image classification
- * labeling job, three workers will classify each input image.
- * Increasing TaskCount can improve label accuracy.
The number of distinct workers who will perform the same task on each object. For example, if TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing TaskCount can improve label accuracy.
The amount of time that a worker has to complete a task. The default value is 3,600 - * seconds (1 hour).
+ *The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
* @public */ TaskTimeLimitInSeconds?: number | undefined; @@ -6355,308 +4238,7 @@ export interface HumanLoopConfig { TaskKeywords?: string[] | undefined; /** - *Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
- *Use one of the following prices for bounding box tasks. Prices are in US dollars and - * should be based on the complexity of the task; the longer it takes in your initial - * testing, the more you should offer.
- *0.036
- *0.048
- *0.060
- *0.072
- *0.120
- *0.240
- *0.360
- *0.480
- *0.600
- *0.720
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for image classification, text classification, and - * custom tasks. Prices are in US dollars.
- *0.012
- *0.024
- *0.036
- *0.048
- *0.060
- *0.072
- *0.120
- *0.240
- *0.360
- *0.480
- *0.600
- *0.720
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for semantic segmentation tasks. Prices are in US - * dollars.
- *0.840
- *0.960
- *1.080
- *1.200
- *Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon - * Augmented AI review tasks. Prices are in US dollars.
- *2.400
- *2.280
- *2.160
- *2.040
- *1.920
- *1.800
- *1.680
- *1.560
- *1.440
- *1.320
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Use one of the following prices for Rekognition DetectModerationLabels Amazon - * Augmented AI review tasks. Prices are in US dollars.
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Use one of the following prices for Amazon Augmented AI custom human review tasks. - * Prices are in US dollars.
- *1.200
- *1.080
- *0.960
- *0.840
- *0.720
- *0.600
- *0.480
- *0.360
- *0.240
- *0.120
- *0.072
- *0.060
- *0.048
- *0.036
- *0.024
- *0.012
- *Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. - * The default field settings and JSON parsing rules are different based on the integration source. Valid values:
+ *Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
* @public */ AwsManagedHumanLoopRequestSource: AwsManagedHumanLoopRequestSource | undefined; @@ -6681,9 +4262,7 @@ export interface HumanLoopRequestSource { */ export interface FlowDefinitionOutputConfig { /** - *The Amazon S3 path where the object containing human output will be made available.
- *To learn more about the format of Amazon A2I output data, see Amazon A2I - * Output Data.
+ *The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
* @public */ S3OutputPath: string | undefined; @@ -6706,8 +4285,7 @@ export interface CreateFlowDefinitionRequest { FlowDefinitionName: string | undefined; /** - *Container for configuring the source of human task requests. Use to specify if - * Amazon Rekognition or Amazon Textract is used as an integration source.
+ *Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
* @public */ HumanLoopRequestSource?: HumanLoopRequestSource | undefined; @@ -6917,9 +4495,7 @@ export interface CreateHumanTaskUiResponse { } /** - *For a hyperparameter of the integer type, specifies the range - * that - * a hyperparameter tuning job searches.
+ *For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
* @public */ export interface IntegerParameterRange { @@ -6930,108 +4506,67 @@ export interface IntegerParameterRange { Name: string | undefined; /** - *The minimum - * value - * of the hyperparameter to search.
+ *The minimum value of the hyperparameter to search.
* @public */ MinValue: string | undefined; /** - *The maximum - * value - * of the hyperparameter to search.
+ *The maximum value of the hyperparameter to search.
* @public */ MaxValue: string | undefined; /** - *The scale that hyperparameter tuning uses to search the hyperparameter range. For - * information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
- *SageMaker hyperparameter tuning chooses the best scale for the - * hyperparameter.
- *Hyperparameter tuning searches the values in the hyperparameter range by - * using a linear scale.
- *Hyperparameter tuning searches the values in the hyperparameter range by - * using a logarithmic scale.
- *Logarithmic scaling works only for ranges that have only values greater - * than 0.
- *The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Specifies ranges of integer, continuous, and categorical hyperparameters that a - * hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs - * with hyperparameter values within these ranges to find the combination of values that - * result in the training job with the best performance as measured by the objective metric - * of the hyperparameter tuning job.
- *The maximum number of items specified for Array Members refers to the
- * maximum number of hyperparameters for each range and also the maximum for the
- * hyperparameter tuning job itself. That is, the sum of the number of hyperparameters
- * for all the ranges can't exceed the maximum number specified.
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified.
The array of IntegerParameterRange objects that specify ranges of integer - * hyperparameters that a hyperparameter tuning job searches.
+ *The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
* @public */ IntegerParameterRanges?: IntegerParameterRange[] | undefined; /** - *The array of ContinuousParameterRange objects that specify ranges of continuous - * hyperparameters that a hyperparameter tuning job searches.
+ *The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
* @public */ ContinuousParameterRanges?: ContinuousParameterRange[] | undefined; /** - *The array of CategoricalParameterRange objects that specify ranges of categorical - * hyperparameters that a hyperparameter tuning job searches.
+ *The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
* @public */ CategoricalParameterRanges?: CategoricalParameterRange[] | undefined; /** - *A list containing hyperparameter names and example values to be used by Autotune to - * determine optimal ranges for your tuning job.
+ *A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
* @public */ AutoParameters?: AutoParameter[] | undefined; } /** - *Specifies the maximum number of training jobs and parallel training jobs that a - * hyperparameter tuning job can launch.
+ *Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
* @public */ export interface ResourceLimits { /** - *The maximum number of training jobs that a hyperparameter tuning job can - * launch.
+ *The maximum number of training jobs that a hyperparameter tuning job can launch.
* @public */ MaxNumberOfTrainingJobs?: number | undefined; /** - *The maximum number of concurrent training jobs that a hyperparameter tuning job can - * launch.
+ *The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
* @public */ MaxParallelTrainingJobs: number | undefined; @@ -7061,83 +4596,30 @@ export type HyperParameterTuningJobStrategyType = (typeof HyperParameterTuningJobStrategyType)[keyof typeof HyperParameterTuningJobStrategyType]; /** - *The configuration for Hyperband, a multi-fidelity based hyperparameter
- * tuning strategy. Hyperband uses the final and intermediate results of a
- * training job to dynamically allocate resources to utilized hyperparameter configurations
- * while automatically stopping under-performing configurations. This parameter should be
- * provided only if Hyperband is selected as the StrategyConfig
- * under the HyperParameterTuningJobConfig API.
The configuration for Hyperband, a multi-fidelity based hyperparameter tuning strategy. Hyperband uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband is selected as the StrategyConfig under the HyperParameterTuningJobConfig API.
The minimum number of resources (such as epochs) that can be used by a training job
- * launched by a hyperparameter tuning job. If the value for MinResource has not
- * been reached, the training job is not stopped by Hyperband.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource has not been reached, the training job is not stopped by Hyperband.
The maximum number of resources (such as epochs) that can be used by a training job
- * launched by a hyperparameter tuning job. Once a job reaches the MaxResource
- * value, it is stopped. If a value for MaxResource is not provided, and
- * Hyperband is selected as the hyperparameter tuning strategy,
- * HyperbandTraining attempts to infer MaxResource from the
- * following keys (if present) in StaticsHyperParameters:
- * epochs
- *
- * numepochs
- *
- * n-epochs
- *
- * n_epochs
- *
- * num_epochs
- *
If HyperbandStrategyConfig is unable to infer a value for
- * MaxResource, it generates a validation error. The maximum value is 20,000
- * epochs. All metrics that correspond to an objective metric are used to derive early stopping
- * decisions. For distributed training jobs,
- * ensure that duplicate metrics are not printed in the logs across the individual nodes in a
- * training job. If multiple nodes are publishing duplicate or incorrect metrics, training
- * jobs may make an incorrect stopping decision and stop the job prematurely.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource value, it is stopped. If a value for MaxResource is not provided, and Hyperband is selected as the hyperparameter tuning strategy, HyperbandTraining attempts to infer MaxResource from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig is unable to infer a value for MaxResource, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributed training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The configuration for a training job launched by a hyperparameter tuning job. Choose
- * Bayesian for Bayesian optimization, and Random for random
- * search optimization. For more advanced use cases, use Hyperband, which
- * evaluates objective metrics for training jobs after every epoch. For more information about
- * strategies, see How Hyperparameter
- * Tuning Works.
The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian for Bayesian optimization, and Random for random search optimization. For more advanced use cases, use Hyperband, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The configuration for the object that specifies the Hyperband strategy.
- * This parameter is only supported for the Hyperband selection for
- * Strategy within the HyperParameterTuningJobConfig API.
The configuration for the object that specifies the Hyperband strategy. This parameter is only supported for the Hyperband selection for Strategy within the HyperParameterTuningJobConfig API.
A flag to stop your hyperparameter tuning job if model performance fails to improve as - * evaluated against an objective function.
+ *A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
* @public */ BestObjectiveNotImproving?: BestObjectiveNotImproving | undefined; /** - *A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has - * detected that your model has converged as evaluated against your objective - * function.
+ *A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
* @public */ ConvergenceDetected?: ConvergenceDetected | undefined; @@ -7191,65 +4670,37 @@ export interface TuningJobCompletionCriteria { */ export interface HyperParameterTuningJobConfig { /** - *Specifies how hyperparameter tuning chooses the combinations of hyperparameter values - * to use for the training job it launches. For information about search strategies, see - * How - * Hyperparameter Tuning Works.
+ *Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
* @public */ Strategy: HyperParameterTuningJobStrategyType | undefined; /** - *The configuration for the Hyperband optimization strategy. This parameter
- * should be provided only if Hyperband is selected as the strategy for
- * HyperParameterTuningJobConfig.
The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.
The HyperParameterTuningJobObjective specifies the objective metric used to - * evaluate the performance of training jobs launched by this tuning job.
+ *The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
* @public */ HyperParameterTuningJobObjective?: HyperParameterTuningJobObjective | undefined; /** - *The ResourceLimits - * object that specifies the maximum number of training and parallel training jobs that can - * be used for this hyperparameter tuning job.
+ *The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
* @public */ ResourceLimits: ResourceLimits | undefined; /** - *The ParameterRanges - * object that specifies the ranges of hyperparameters that this tuning job searches over - * to find the optimal configuration for the highest model performance against your chosen - * objective metric.
+ *The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
* @public */ ParameterRanges?: ParameterRanges | undefined; /** - *Specifies whether to use early stopping for training jobs launched by the
- * hyperparameter tuning job. Because the Hyperband strategy has its own
- * advanced internal early stopping mechanism, TrainingJobEarlyStoppingType
- * must be OFF to use Hyperband. This parameter can take on one
- * of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early - * stopping.
- *SageMaker stops training jobs launched by the hyperparameter tuning job when - * they are unlikely to perform better than previously completed training jobs. - * For more information, see Stop Training Jobs Early.
- *Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
A value used to initialize a pseudo-random number generator. Setting a random seed and - * using the same seed later for the same tuning job will allow hyperparameter optimization - * to find more a consistent hyperparameter configuration between the two runs.
+ *A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
* @public */ RandomSeed?: number | undefined; } /** - *Specifies - * which - * training algorithm to use for training jobs that a hyperparameter - * tuning job launches and the metrics to monitor.
+ *Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
* @public */ export interface HyperParameterAlgorithmSpecification { /** - * The registry path of the Docker image that contains the training algorithm. For
- * information about Docker registry paths for built-in algorithms, see Algorithms
- * Provided by Amazon SageMaker: Common Parameters. SageMaker supports both
- * registry/repository[:tag] and registry/repository[@digest]
- * image path formats. For more information, see Using Your Own Algorithms with
- * Amazon SageMaker.
The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The training input mode that the algorithm supports. For more information about input - * modes, see Algorithms.
- *- * Pipe mode - *
- *If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from
- * Amazon S3 to the container.
- * File mode - *
- *If an algorithm supports File mode, SageMaker downloads the training data from
- * S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume
- * for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the - * data downloaded from S3. In addition to the training data, the ML storage volume also - * stores the output model. The algorithm container uses the ML storage volume to also - * store intermediate information, if any.
- *For distributed algorithms, training data is distributed uniformly. Your training - * duration is predictable if the input data objects sizes are approximately the same. SageMaker - * does not split the files any further for model training. If the object sizes are skewed, - * training won't be optimal as the data distribution is also skewed when one host in a - * training cluster is overloaded, thus becoming a bottleneck in training.
- *- * FastFile mode - *
- *If an algorithm supports FastFile mode, SageMaker streams data directly from
- * S3 to the container with no code changes, and provides file system access to the data.
- * Users can author their training script to interact with these files as if they were
- * stored on disk.
- * FastFile mode works best when the data is read sequentially. Augmented
- * manifest files aren't supported. The startup time is lower when there are fewer files in
- * the S3 bucket provided.
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
The name of the resource algorithm to use for the hyperparameter tuning job. If you
- * specify a value for this parameter, do not specify a value for
- * TrainingImage.
The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.
An array of MetricDefinition objects that specify the - * metrics - * that the algorithm emits.
+ *An array of MetricDefinition objects that specify the metrics that the algorithm emits.
* @public */ MetricDefinitions?: MetricDefinition[] | undefined; @@ -7358,61 +4763,36 @@ export type HyperParameterTuningAllocationStrategy = (typeof HyperParameterTuningAllocationStrategy)[keyof typeof HyperParameterTuningAllocationStrategy]; /** - *The configuration for hyperparameter tuning resources for use in training jobs - * launched by the tuning job. These resources include compute instances and storage - * volumes. Specify one or more compute instance configurations and allocation strategies - * to select resources (optional).
+ *The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
* @public */ export interface HyperParameterTuningInstanceConfig { /** - *The instance type used for processing of hyperparameter optimization jobs. Choose from - * general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge - * or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more - * information about instance types, see instance type - * descriptions.
+ *The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
* @public */ InstanceType: TrainingInstanceType | undefined; /** - *The number of instances of the type specified by InstanceType. Choose an
- * instance count larger than 1 for distributed training algorithms. See Step 2:
- * Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more
- * information.
The number of instances of the type specified by InstanceType. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The volume size in GB of the data to be processed for hyperparameter optimization - * (optional).
+ *The volume size in GB of the data to be processed for hyperparameter optimization (optional).
* @public */ VolumeSizeInGB: number | undefined; } /** - *The configuration of resources, including compute instances and storage volumes for
- * use in training jobs launched by hyperparameter tuning jobs.
- * HyperParameterTuningResourceConfig is similar to
- * ResourceConfig, but has the additional InstanceConfigs and
- * AllocationStrategy fields to allow for flexible instance management.
- * Specify one or more instance types, count, and the allocation strategy for instance
- * selection.
- * HyperParameterTuningResourceConfig supports the capabilities of
- * ResourceConfig with the exception of
- * KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools
- * by default, which reuse clusters between training jobs.
The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig is similar to ResourceConfig, but has the additional InstanceConfigs and AllocationStrategy fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig supports the capabilities of ResourceConfig with the exception of KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The instance type used to run hyperparameter optimization tuning jobs. See descriptions of - * instance types for more information.
+ *The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
* @public */ InstanceType?: TrainingInstanceType | undefined; @@ -7424,91 +4804,44 @@ export interface HyperParameterTuningResourceConfig { InstanceCount?: number | undefined; /** - *The volume size in GB for the storage volume to be used in processing hyperparameter
- * optimization jobs (optional). These volumes store model artifacts, incremental states
- * and optionally, scratch space for training algorithms. Do not provide a value for this
- * parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these
- * instances for training, VolumeSizeInGB cannot be greater than this total
- * size. For a list of instance types with local instance storage and their sizes, see
- * instance store volumes.
SageMaker supports only the General Purpose SSD - * (gp2) storage volume type.
- *The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume - * attached to the compute instances used to run the training job. You can use either of - * the following formats to specify a key.
- *KMS Key ID:
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
Amazon Resource Name (ARN) of a KMS key:
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
Some instances use local storage, which use a hardware module to
- * encrypt storage volumes. If you choose one of these instance types, you
- * cannot request a VolumeKmsKeyId. For a list of instance types that use
- * local storage, see instance store
- * volumes. For more information about Amazon Web Services Key Management Service, see KMS
- * encryption for more information.
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The strategy that determines the order of preference for resources specified in
- * InstanceConfigs used in hyperparameter optimization.
The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.
A list containing the configuration(s) for one or more resources for processing
- * hyperparameter jobs. These resources include compute instances and storage volumes to
- * use in model training jobs launched by hyperparameter tuning jobs. The
- * AllocationStrategy controls the order in which multiple configurations
- * provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the
- * HyperParameterTuningResourceConfig API, do not provide a value for
- * InstanceConfigs. Instead, use InstanceType,
- * VolumeSizeInGB and InstanceCount. If you use
- * InstanceConfigs, do not provide values for
- * InstanceType, VolumeSizeInGB or
- * InstanceCount.
A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.
The retry strategy to use when a training job fails due to an
- * InternalServerError. RetryStrategy is specified as part of
- * the CreateTrainingJob and CreateHyperParameterTuningJob
- * requests. You can add the StoppingCondition parameter to the request to
- * limit the training time for the complete job.
The retry strategy to use when a training job fails due to an InternalServerError. RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.
The number of times to retry the job. When the job is retried, it's
- * SecondaryStatus is changed to STARTING.
The number of times to retry the job. When the job is retried, it's SecondaryStatus is changed to STARTING.
Defines - * the training jobs launched by a hyperparameter tuning job.
+ *Defines the training jobs launched by a hyperparameter tuning job.
* @public */ export interface HyperParameterTrainingJobDefinition { @@ -7519,189 +4852,115 @@ export interface HyperParameterTrainingJobDefinition { DefinitionName?: string | undefined; /** - *Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning
- * uses the value of this metric to evaluate the training jobs it launches, and returns the
- * training job that results in either the highest or lowest value for this metric,
- * depending on the value you specify for the Type parameter. If you want to
- * define a custom objective metric, see Define metrics and environment variables.
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
Specifies ranges of integer, continuous, and categorical hyperparameters that a - * hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs - * with hyperparameter values within these ranges to find the combination of values that - * result in the training job with the best performance as measured by the objective metric - * of the hyperparameter tuning job.
- *The maximum number of items specified for Array Members refers to the
- * maximum number of hyperparameters for each range and also the maximum for the
- * hyperparameter tuning job itself. That is, the sum of the number of hyperparameters
- * for all the ranges can't exceed the maximum number specified.
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified.
Specifies the values of hyperparameters - * that - * do not change for the tuning job.
+ *Specifies the values of hyperparameters that do not change for the tuning job.
* @public */ StaticHyperParameters?: RecordThe HyperParameterAlgorithmSpecification object that - * specifies - * the resource algorithm to use for the training jobs that the tuning - * job launches.
+ *The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
* @public */ AlgorithmSpecification: HyperParameterAlgorithmSpecification | undefined; /** - *The Amazon Resource Name (ARN) of the - * IAM - * role associated with the training jobs that the tuning job - * launches.
+ *The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
* @public */ RoleArn: string | undefined; /** - *An array of Channel objects that - * specify - * the - * input for the training jobs that the tuning job launches.
+ *An array of Channel objects that specify the input for the training jobs that the tuning job launches.
* @public */ InputDataConfig?: Channel[] | undefined; /** - *The VpcConfig object that specifies the VPC that you want the training jobs - * that this hyperparameter tuning job launches to connect to. Control access to and from - * your training container by configuring the VPC. For more information, see Protect Training Jobs - * by Using an Amazon Virtual Private Cloud.
+ *The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Specifies the path to the Amazon S3 bucket where you - * store - * model artifacts from the training jobs that the tuning job - * launches.
+ *Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
* @public */ OutputDataConfig: OutputDataConfig | undefined; /** - *The resources, - * including - * the compute instances and storage volumes, to use for the training - * jobs that the tuning job launches.
- *Storage volumes store model artifacts and
- * incremental
- * states. Training algorithms might also use storage volumes for
- * scratch
- * space. If you want SageMaker to use the storage volume to store the
- * training data, choose File as the TrainingInputMode in the
- * algorithm specification. For distributed training algorithms, specify an instance count
- * greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use
- * HyperParameterTuningResourceConfig instead.
The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
The configuration for the hyperparameter tuning resources, including the compute
- * instances and storage volumes, used for training jobs launched by the tuning job. By
- * default, storage volumes hold model artifacts and incremental states. Choose
- * File for TrainingInputMode in the
- * AlgorithmSpecification parameter to additionally store training data in
- * the storage volume (optional).
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
Specifies a limit to how long a model hyperparameter training job can run. It also - * specifies how long a managed spot training job has to complete. When the job reaches the - * time limit, SageMaker ends the training job. Use this API to cap model training costs.
+ *Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
* @public */ StoppingCondition: StoppingCondition | undefined; /** - *Isolates the training container. No inbound or outbound network calls can be made, - * except for calls between peers within a training cluster for distributed training. If - * network isolation is used for training jobs that are configured to use a VPC, SageMaker - * downloads and uploads customer data and model artifacts through the specified VPC, but - * the training container does not have network access.
+ *Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
* @public */ EnableNetworkIsolation?: boolean | undefined; /** - *To encrypt all communications between ML compute instances in distributed training,
- * choose True. Encryption provides greater security for distributed training,
- * but training might take longer. How long it takes depends on the amount of communication
- * between compute instances, especially if you use a deep learning algorithm in
- * distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or
- * not (False).
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Contains information about the output location for managed spot training checkpoint - * data.
+ *Contains information about the output location for managed spot training checkpoint data.
* @public */ CheckpointConfig?: CheckpointConfig | undefined; /** - *The number of times to retry the job when the job fails due to an
- * InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See - * Define metrics and variables for more information.
- *The maximum number of items specified for Map Entries refers to the
- * maximum number of environment variables for each TrainingJobDefinition
- * and also the maximum for the hyperparameter tuning job itself. That is, the sum of
- * the number of environment variables for all the training job definitions can't
- * exceed the maximum number specified.
An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can't exceed the maximum number specified.
A previously completed or stopped hyperparameter tuning job to be used as a starting - * point for a new hyperparameter tuning job.
+ *A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
* @public */ export interface ParentHyperParameterTuningJob { /** - *The name of the hyperparameter tuning job to be used as a starting point for a new - * hyperparameter tuning job.
+ *The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
* @public */ HyperParameterTuningJobName?: string | undefined; @@ -7723,64 +4982,18 @@ export type HyperParameterTuningJobWarmStartType = (typeof HyperParameterTuningJobWarmStartType)[keyof typeof HyperParameterTuningJobWarmStartType]; /** - *Specifies the configuration for a hyperparameter tuning job that uses one or more - * previous hyperparameter tuning jobs as a starting point. The results of previous tuning - * jobs are used to inform which combinations of hyperparameters to search over in the new - * tuning job.
- *All training jobs launched by the new hyperparameter tuning job are evaluated by using - * the objective metric, and the training job that performs the best is compared to the - * best training jobs from the parent tuning jobs. From these, the training job that - * performs the best as measured by the objective metric is returned as the overall best - * training job.
- *All training jobs launched by parent hyperparameter tuning jobs and the new - * hyperparameter tuning jobs count against the limit of training jobs for the tuning - * job.
- *Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
An array of hyperparameter tuning jobs that are used as the starting point for the new - * hyperparameter tuning job. For more information about warm starting a hyperparameter - * tuning job, see Using a Previous - * Hyperparameter Tuning Job as a Starting Point.
- *Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent - * jobs for warm start tuning jobs.
+ *An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
* @public */ ParentHyperParameterTuningJobs: ParentHyperParameterTuningJob[] | undefined; /** - *Specifies one of the following:
- *The new hyperparameter tuning job uses the same input data and training - * image as the parent tuning jobs. You can change the hyperparameter ranges to - * search and the maximum number of training jobs that the hyperparameter - * tuning job launches. You cannot use a new version of the training algorithm, - * unless the changes in the new version do not affect the algorithm itself. - * For example, changes that improve logging or adding support for a different - * data format are allowed. You can also change hyperparameters from tunable to - * static, and from static to tunable, but the total number of static plus - * tunable hyperparameters must remain the same as it is in all parent jobs. - * The objective metric for the new tuning job must be the same as for all - * parent jobs.
- *The new hyperparameter tuning job can include input data, hyperparameter - * ranges, maximum number of concurrent training jobs, and maximum number of - * training jobs that are different than those of its parent hyperparameter - * tuning jobs. The training image can also be a different version from the - * version used in the parent hyperparameter tuning job. You can also change - * hyperparameters from tunable to static, and from static to tunable, but the - * total number of static plus tunable hyperparameters must remain the same as - * it is in all parent jobs. The objective metric for the new tuning job must - * be the same as for all parent jobs.
- *Specifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The name of the tuning job. This name is the prefix for the names of all training jobs - * that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid - * characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case - * sensitive.
+ *The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
* @public */ HyperParameterTuningJobName: string | undefined; /** - *The HyperParameterTuningJobConfig object that describes the tuning job, - * including the search strategy, the objective metric used to evaluate training jobs, - * ranges of parameters to search, and resource limits for the tuning job. For more - * information, see How - * Hyperparameter Tuning Works.
+ *The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
* @public */ HyperParameterTuningJobConfig: HyperParameterTuningJobConfig | undefined; /** - *The HyperParameterTrainingJobDefinition object that describes the training jobs - * that this tuning job launches, including static hyperparameters, input data - * configuration, output data configuration, resource configuration, and stopping - * condition.
+ *The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
* @public */ TrainingJobDefinition?: HyperParameterTrainingJobDefinition | undefined; /** - *A list of the HyperParameterTrainingJobDefinition objects launched for this tuning - * job.
+ *A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
* @public */ TrainingJobDefinitions?: HyperParameterTrainingJobDefinition[] | undefined; /** - *Specifies the configuration for starting the hyperparameter tuning job using one or - * more previous tuning jobs as a starting point. The results of previous tuning jobs are - * used to inform which combinations of hyperparameters to search over in the new tuning - * job.
- *All training jobs launched by the new hyperparameter tuning job are evaluated by using
- * the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the
- * WarmStartType value for the warm start configuration, the training job
- * that performs the best in the new tuning job is compared to the best training jobs from
- * the parent tuning jobs. From these, the training job that performs the best as measured
- * by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new - * hyperparameter tuning jobs count against the limit of training jobs for the tuning - * job.
- *Specifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
- *Tags that you specify for the tuning job are also added to all training jobs that the - * tuning job launches.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
* @public */ Tags?: Tag[] | undefined; /** - *Configures SageMaker Automatic model tuning (AMT) to automatically find optimal - * parameters for the following fields:
- *- * ParameterRanges: The names and ranges of parameters that a - * hyperparameter tuning job can optimize.
- *- * ResourceLimits: The maximum resources that can be used for a - * training job. These resources include the maximum number of training jobs, the - * maximum runtime of a tuning job, and the maximum number of training jobs to run - * at the same time.
- *- * TrainingJobEarlyStoppingType: A flag that specifies whether or not - * to use early stopping for training jobs launched by a hyperparameter tuning - * job.
- *- * RetryStrategy: The number of times to retry a training job.
- *- * Strategy: Specifies how hyperparameter tuning chooses the - * combinations of hyperparameter values to use for the training jobs that it - * launches.
- *- * ConvergenceDetected: A flag to indicate that Automatic model tuning - * (AMT) has detected model convergence.
- *Configures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a - * hyperparameter tuning job when you create it.
+ *The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
* @public */ HyperParameterTuningJobArn: string | undefined; @@ -8006,18 +5153,13 @@ export type VendorGuidance = (typeof VendorGuidance)[keyof typeof VendorGuidance */ export interface CreateImageVersionRequest { /** - *The registry path of the container image to use as the starting point for this - * version. The path is an Amazon ECR URI in the following format:
- *
- *
The registry path of the container image to use as the starting point for this version. The path is an Amazon ECR URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python - * (Boto3), add a unique value to the call.
+ *A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
* @public */ ClientToken?: string | undefined; @@ -8035,45 +5177,13 @@ export interface CreateImageVersionRequest { Aliases?: string[] | undefined; /** - *The stability of the image version, specified by the maintainer.
- *
- * NOT_PROVIDED: The maintainers did not provide a status for image version stability.
- * STABLE: The image version is stable.
- * TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
- * ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
- *
- * TRAINING: The image version is compatible with SageMaker AI training jobs.
- * INFERENCE: The image version is compatible with SageMaker AI inference jobs.
- * NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
- *
- * CPU: The image version is compatible with CPU.
- * GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
The number of runtime copies of the model container to deploy with the inference - * component. Each copy can serve inference requests.
+ *The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
* @public */ CopyCount: number | undefined; } /** - *Defines the compute resources to allocate to run a model, plus any adapter models, that - * you assign to an inference component. These resources include CPU cores, accelerators, and - * memory.
+ *Defines the compute resources to allocate to run a model, plus any adapter models, that you assign to an inference component. These resources include CPU cores, accelerators, and memory.
* @public */ export interface InferenceComponentComputeResourceRequirements { /** - *The number of CPU cores to allocate to run a model that you assign to an inference - * component.
+ *The number of CPU cores to allocate to run a model that you assign to an inference component.
* @public */ NumberOfCpuCoresRequired?: number | undefined; /** - *The number of accelerators to allocate to run a model that you assign to an inference - * component. Accelerators include GPUs and Amazon Web Services Inferentia.
+ *The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
* @public */ NumberOfAcceleratorDevicesRequired?: number | undefined; /** - *The minimum MB of memory to allocate to run a model that you assign to an inference - * component.
+ *The minimum MB of memory to allocate to run a model that you assign to an inference component.
* @public */ MinMemoryRequiredInMb: number | undefined; /** - *The maximum MB of memory to allocate to run a model that you assign to an inference - * component.
+ *The maximum MB of memory to allocate to run a model that you assign to an inference component.
* @public */ MaxMemoryRequiredInMb?: number | undefined; } /** - *Defines a container that provides the runtime environment for a model that you deploy - * with an inference component.
+ *Defines a container that provides the runtime environment for a model that you deploy with an inference component.
* @public */ export interface InferenceComponentContainerSpecification { @@ -8192,17 +5284,13 @@ export interface InferenceComponentContainerSpecification { Image?: string | undefined; /** - *The Amazon S3 path where the model artifacts, which result from model training, - * are stored. This path must point to a single gzip compressed tar archive (.tar.gz - * suffix).
+ *The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
* @public */ ArtifactUrl?: string | undefined; /** - *The environment variables to set in the Docker container. Each key and value in the - * Environment string-to-string map can have length of up to 1024. We support up to 16 entries - * in the map.
+ *The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map.
* @public */ Environment?: RecordThe timeout value, in seconds, to download and extract the model that you want to host - * from Amazon S3 to the individual inference instance associated with this inference - * component.
+ *The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
* @public */ ModelDataDownloadTimeoutInSeconds?: number | undefined; /** - *The timeout value, in seconds, for your inference container to pass health check by - * Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
+ *The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
* @public */ ContainerStartupHealthCheckTimeoutInSeconds?: number | undefined; } /** - *Details about the resources to deploy with this inference component, including the - * model, container, and compute resources.
+ *Details about the resources to deploy with this inference component, including the model, container, and compute resources.
* @public */ export interface InferenceComponentSpecification { /** - *The name of an existing SageMaker AI model object in your account that you want to - * deploy with the inference component.
+ *The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.
* @public */ ModelName?: string | undefined; /** - *Defines a container that provides the runtime environment for a model that you deploy - * with an inference component.
+ *Defines a container that provides the runtime environment for a model that you deploy with an inference component.
* @public */ Container?: InferenceComponentContainerSpecification | undefined; @@ -8256,29 +5338,13 @@ export interface InferenceComponentSpecification { StartupParameters?: InferenceComponentStartupParameters | undefined; /** - *The compute resources allocated to run the model, plus any - * adapter models, that you assign to the inference component.
- *Omit this parameter if your request is meant to create an adapter inference component. - * An adapter inference component is loaded by a base inference component, and it uses the - * compute resources of the base inference component.
+ *The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.
Omit this parameter if your request is meant to create an adapter inference component. An adapter inference component is loaded by a base inference component, and it uses the compute resources of the base inference component.
* @public */ ComputeResourceRequirements?: InferenceComponentComputeResourceRequirements | undefined; /** - *The name of an existing inference component that is to contain the inference component - * that you're creating with your request.
- *Specify this parameter only if your request is meant to create an adapter inference - * component. An adapter inference component contains the path to an adapter model. The - * purpose of the adapter model is to tailor the inference output of a base foundation model, - * which is hosted by the base inference component. The adapter inference component uses the - * compute resources that you assigned to the base inference component.
- *When you create an adapter inference component, use the Container parameter
- * to specify the location of the adapter artifacts. In the parameter value, use the
- * ArtifactUrl parameter of the
- * InferenceComponentContainerSpecification data type.
Before you can create an adapter inference component, you must have an existing - * inference component that contains the foundation model that you want to adapt.
+ *The name of an existing inference component that is to contain the inference component that you're creating with your request.
Specify this parameter only if your request is meant to create an adapter inference component. An adapter inference component contains the path to an adapter model. The purpose of the adapter model is to tailor the inference output of a base foundation model, which is hosted by the base inference component. The adapter inference component uses the compute resources that you assigned to the base inference component.
When you create an adapter inference component, use the Container parameter to specify the location of the adapter artifacts. In the parameter value, use the ArtifactUrl parameter of the InferenceComponentContainerSpecification data type.
Before you can create an adapter inference component, you must have an existing inference component that contains the foundation model that you want to adapt.
* @public */ BaseInferenceComponentName?: string | undefined; @@ -8301,15 +5367,13 @@ export interface CreateInferenceComponentInput { EndpointName: string | undefined; /** - *The name of an existing production variant where you host the inference - * component.
+ *The name of an existing production variant where you host the inference component.
* @public */ VariantName?: string | undefined; /** - *Details about the resources to deploy with this inference component, including the - * model, container, and compute resources.
+ *Details about the resources to deploy with this inference component, including the model, container, and compute resources.
* @public */ Specification: InferenceComponentSpecification | undefined; @@ -8321,9 +5385,7 @@ export interface CreateInferenceComponentInput { RuntimeConfig?: InferenceComponentRuntimeConfig | undefined; /** - *A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services - * resources in the Amazon Web Services General - * Reference.
+ *A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference.
* @public */ Tags?: Tag[] | undefined; @@ -8352,17 +5414,13 @@ export interface InferenceExperimentDataStorageConfig { Destination: string | undefined; /** - *- * The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 - * server-side encryption. - *
+ *The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
* @public */ KmsKey?: string | undefined; /** - *Configuration specifying how to treat different headers. If no headers are specified - * Amazon SageMaker AI will by default base64 encode when capturing the data.
+ *Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker AI will by default base64 encode when capturing the data.
* @public */ ContentType?: CaptureContentTypeHeader | undefined; @@ -8589,13 +5647,7 @@ export interface RealTimeInferenceConfig { */ export interface ModelInfrastructureConfig { /** - *The inference option to which to deploy your model. Possible values are the following:
- *
- * RealTime: Deploy to real-time inference.
The inference option to which to deploy your model. Possible values are the following:
RealTime: Deploy to real-time inference.
The start and end times of an inference experiment.
- *The maximum duration that you can set for an inference experiment is 30 days.
+ *The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
* @public */ export interface InferenceExperimentSchedule { @@ -8662,27 +5713,19 @@ export interface ShadowModelVariantConfig { ShadowModelVariantName: string | undefined; /** - *- * The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant. - *
+ *The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
* @public */ SamplingPercentage: number | undefined; } /** - *
- * The configuration of ShadowMode inference experiment type, which specifies a production variant
- * to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the
- * inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
- *
The configuration of ShadowMode inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
- * The name of the production variant, which takes all the inference requests. - *
+ *The name of the production variant, which takes all the inference requests.
* @public */ SourceModelVariantName: string | undefined; @@ -8718,26 +5761,13 @@ export interface CreateInferenceExperimentRequest { Name: string | undefined; /** - *- * The type of the inference experiment that you want to run. The following types of experiments are possible: - *
- *
- * ShadowMode: You can use this type to validate a shadow variant. For more information,
- * see Shadow tests.
- *
The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
- * The duration for which you want the inference experiment to run. If you don't specify this field, the - * experiment automatically starts immediately upon creation and concludes after 7 days. - *
+ *The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
* @public */ Schedule?: InferenceExperimentSchedule | undefined; @@ -8749,109 +5779,43 @@ export interface CreateInferenceExperimentRequest { Description?: string | undefined; /** - *- * The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage - * Amazon SageMaker Inference endpoints for model deployment. - *
+ *The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
* @public */ RoleArn: string | undefined; /** - *- * The name of the Amazon SageMaker endpoint on which you want to run the inference experiment. - *
+ *The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
* @public */ EndpointName: string | undefined; /** - *
- * An array of ModelVariantConfig objects. There is one for each variant in the inference
- * experiment. Each ModelVariantConfig object in the array describes the infrastructure
- * configuration for the corresponding variant.
- *
An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.
- * The Amazon S3 location and configuration for storing inference request and response data. - *
- *- * This is an optional parameter that you can use for data capture. For more information, see Capture data. - *
+ *The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
* @public */ DataStorageConfig?: InferenceExperimentDataStorageConfig | undefined; /** - *
- * The configuration of ShadowMode inference experiment type. Use this field to specify a
- * production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a
- * percentage of the inference requests. For the shadow variant also specify the percentage of requests that
- * Amazon SageMaker replicates.
- *
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
- * The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on
- * the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can
- * be any of the following formats:
- *
KMS key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
Amazon Resource Name (ARN) of a KMS key
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
KMS key Alias
- *
- * "alias/ExampleAlias"
- *
Amazon Resource Name (ARN) of a KMS key Alias
- *
- * "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
- *
- * If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to
- * call kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for
- * your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for
- * OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that
- * only allows objects with server-side encryption, set the condition key of
- * s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS managed Encryption Keys
- * in the Amazon Simple Storage Service Developer Guide.
- *
- * The KMS key policy must grant permission to the IAM role that you specify in your
- * CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer
- * Guide.
- *
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can be any of the following formats:
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS key Alias
"alias/ExampleAlias"
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
- * Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different - * ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources. - *
+ *Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -8902,36 +5866,24 @@ export type RecommendationJobSupportedEndpointType = (typeof RecommendationJobSupportedEndpointType)[keyof typeof RecommendationJobSupportedEndpointType]; /** - *Specifies mandatory fields for running an Inference Recommender job directly in the
- * CreateInferenceRecommendationsJob
- * API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use
- * ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
The machine learning domain of the model and its components.
- *Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING |
- * MACHINE_LEARNING
- *
The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
- *Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION
- * | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION |
- * REGRESSION | OTHER
- *
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
- *Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
- *
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
- *Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn |
- * densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
- *
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
The endpoint type to receive recommendations for. By default this is null, and the results of - * the inference recommendation job return a combined list of both real-time and serverless benchmarks. - * By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
+ *The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
* @public */ SupportedEndpointType?: RecommendationJobSupportedEndpointType | undefined; /** - *Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. - * This field is used for optimizing your model using SageMaker Neo. For more information, see - * DataInputConfig.
+ *Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
* @public */ DataInputConfig?: string | undefined; @@ -9041,8 +5986,7 @@ export interface EndpointInfo { } /** - *Specifies the maximum number of jobs that can run in parallel - * and the maximum number of jobs that can run.
+ *Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
* @public */ export interface RecommendationJobResourceLimit { @@ -9077,17 +6021,14 @@ export interface Phase { SpawnRate?: number | undefined; /** - *Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600.
- * This value should not exceed JobDurationInSeconds.
Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds.
Defines the stairs traffic pattern for an Inference Recommender load test. This pattern - * type consists of multiple steps where the number of users increases at each step.
- *Specify either the stairs or phases traffic pattern.
+ *Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
* @public */ export interface Stairs { @@ -9154,8 +6095,7 @@ export interface TrafficPattern { */ export interface RecommendationJobVpcConfig { /** - *The VPC security group IDs. IDs have the form of sg-xxxxxxxx.
- * Specify the security groups for the VPC that is specified in the Subnets field.
The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key - * that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. - * This key will be passed to SageMaker Hosting for endpoint creation.
- *The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage
- * volume of the endpoints created for inference recommendation. The inference recommendation job will fail
- * asynchronously during endpoint configuration creation if the role passed does not have
- * kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:
- *
// KMS Key Alias
- *
- * "alias/ExampleAlias"
- *
// Amazon Resource Name (ARN) of a KMS Key Alias
- *
- * "arn:aws:kms:
- *
For more information about key identifiers, see - * Key identifiers (KeyID) in the - * Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
+ *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
* @public */ VolumeKmsKeyId?: string | undefined; /** - *Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig
- * override the corresponding fields in the model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig override the corresponding fields in the model package.
Provides information about the output configuration for the compiled - * model.
+ *Provides information about the output configuration for the compiled model.
* @public */ export interface RecommendationJobCompiledOutputConfig { /** - *Identifies the Amazon S3 bucket where you want SageMaker to store the - * compiled model artifacts.
+ *Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
* @public */ S3OutputUri?: string | undefined; @@ -9304,46 +6205,13 @@ export interface RecommendationJobCompiledOutputConfig { */ export interface RecommendationJobOutputConfig { /** - *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key
- * that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption.
- * The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
// Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:
- *
// KMS Key Alias
- *
- * "alias/ExampleAlias"
- *
// Amazon Resource Name (ARN) of a KMS Key Alias
- *
- * "arn:aws:kms:
- *
For more information about key identifiers, see - * Key identifiers (KeyID) in the - * Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
+ *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
// Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
// KMS Key Alias
"alias/ExampleAlias"
// Amazon Resource Name (ARN) of a KMS Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
* @public */ KmsKeyId?: string | undefined; /** - *Provides information about the output configuration for the compiled - * model.
+ *Provides information about the output configuration for the compiled model.
* @public */ CompiledOutputConfig?: RecommendationJobCompiledOutputConfig | undefined; @@ -9369,8 +6237,7 @@ export type FlatInvocations = (typeof FlatInvocations)[keyof typeof FlatInvocati */ export interface ModelLatencyThreshold { /** - *The model latency percentile threshold. Acceptable values are P95 and P99.
- * For custom load tests, specify the value as P95.
The model latency percentile threshold. Acceptable values are P95 and P99. For custom load tests, specify the value as P95.
Specifies conditions for stopping a job. When a job reaches a - * stopping condition limit, SageMaker ends the job.
+ *Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
* @public */ export interface RecommendationJobStoppingConditions { @@ -9395,18 +6261,13 @@ export interface RecommendationJobStoppingConditions { MaxInvocations?: number | undefined; /** - *The interval of time taken by a model to respond as viewed from SageMaker. - * The interval includes the local communication time taken to send the request - * and to fetch the response from the container of a model and the time taken to - * complete the inference in the container.
+ *The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
* @public */ ModelLatencyThresholds?: ModelLatencyThreshold[] | undefined; /** - *Stops a load test when the number of invocations (TPS) peaks and flattens,
- * which means that the instance has reached capacity. The default value is Stop.
- * If you want the load test to continue after invocations have flattened, set the value to Continue.
Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop. If you want the load test to continue after invocations have flattened, set the value to Continue.
A name for the recommendation job. The name must be unique within - * the Amazon Web Services Region and within your Amazon Web Services account. - * The job name is passed down to the resources created by the recommendation job. - * The names of resources (such as the model, endpoint configuration, endpoint, and compilation) - * that are prefixed with the job name are truncated at 40 characters.
+ *A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
* @public */ JobName: string | undefined; /** - *Defines the type of recommendation job. Specify Default to initiate an instance
- * recommendation and Advanced to initiate a load test. If left unspecified,
- * Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
Defines the type of recommendation job. Specify Default to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker - * to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; /** - *Provides information about the versioned model package Amazon Resource Name (ARN), - * the traffic pattern, and endpoint configurations.
+ *Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
* @public */ InputConfig: RecommendationJobInputConfig | undefined; @@ -9455,25 +6308,19 @@ export interface CreateInferenceRecommendationsJobRequest { JobDescription?: string | undefined; /** - *A set of conditions for stopping a recommendation job. If any of - * the conditions are met, the job is automatically stopped.
+ *A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
* @public */ StoppingConditions?: RecommendationJobStoppingConditions | undefined; /** - *Provides information about the output artifacts and the KMS key - * to use for Amazon S3 server-side encryption.
+ *Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
* @public */ OutputConfig?: RecommendationJobOutputConfig | undefined; /** - *The metadata that you apply to Amazon Web Services resources to help you - * categorize and organize them. Each tag consists of a key and a value, both of - * which you define. For more information, see - * Tagging Amazon Web Services Resources - * in the Amazon Web Services General Reference.
+ *The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
* @public */ Tags?: Tag[] | undefined; @@ -9491,93 +6338,18 @@ export interface CreateInferenceRecommendationsJobResponse { } /** - *Provided configuration information for the worker UI for a labeling job. Provide
- * either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use
- * HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use
- * UiTemplateS3Uri to specify the location of a worker task template in
- * Amazon S3.
Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.
The Amazon S3 bucket location of the UI template, or worker task template. This is the - * template used to render the worker UI and tools for labeling job tasks. For more - * information about the contents of a UI template, see Creating Your Custom - * Labeling Task Template.
+ *The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
* @public */ UiTemplateS3Uri?: string | undefined; /** - *The ARN of the worker task template used to render the worker UI and tools for - * labeling job tasks.
- *Use this parameter when you are creating a labeling job for named entity recognition,
- * 3D point cloud and video frame labeling jobs. Use your labeling job task type to select
- * one of the following ARNs and use it with this parameter when you create a labeling job.
- * Replace aws-region with the Amazon Web Services Region you are creating your labeling job
- * in. For example, replace aws-region with us-west-1 if you
- * create a labeling job in US West (N. California).
- * Named Entity Recognition - *
- *Use the following HumanTaskUiArn for named entity recognition labeling
- * jobs:
- * arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
- *
- * 3D Point Cloud HumanTaskUiArns - *
- *Use this HumanTaskUiArn for 3D point cloud object detection and 3D point
- * cloud object detection adjustment labeling jobs.
- * arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
- *
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point
- * cloud object tracking adjustment labeling jobs.
- * arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
- *
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D
- * point cloud semantic segmentation adjustment labeling jobs.
- * arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
- *
- * Video Frame HumanTaskUiArns - *
- *Use this HumanTaskUiArn for video frame object detection and video frame
- * object detection adjustment labeling jobs.
- * arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
- *
Use this HumanTaskUiArn for video frame object tracking and video frame
- * object tracking adjustment labeling jobs.
- * arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
- *
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region with us-west-1 if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
Information about the user interface that workers use to complete the labeling - * task.
+ *Information about the user interface that workers use to complete the labeling task.
* @public */ UiConfig: UiConfig | undefined; /** - *The Amazon Resource Name (ARN) of a Lambda function that is run before a data object - * is sent to a human worker. Use this function to provide input to a custom labeling - * job.
- *For built-in
- * task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for
- * PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
- * Bounding box - Finds the most similar boxes from - * different workers based on the Jaccard index of the boxes.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
- *
- * Image classification - Uses a variant of the Expectation - * Maximization approach to estimate the true class of an image based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
- *
- * Multi-label image classification - Uses a variant of the Expectation - * Maximization approach to estimate the true classes of an image based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
- *
- * Semantic segmentation - Treats each pixel in an image as - * a multi-class classification and treats pixel annotations from workers as - * "votes" for the correct label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
- *
- * Text classification - Uses a variant of the Expectation - * Maximization approach to estimate the true class of text based on annotations - * from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
- *
- * Multi-label text classification - Uses a variant of the - * Expectation Maximization approach to estimate the true classes of text based on - * annotations from individual workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
- *
- * Named entity recognition - Groups similar selections and - * calculates aggregate boundaries, resolving to most-assigned label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
- *
- * Video Classification - Use this task type when you need workers to classify videos using - * predefined labels that you specify. Workers are shown videos and are asked to choose one - * label for each video.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
- *
- * Video Frame Object Detection - Use this task type to - * have workers identify and locate objects in a sequence of video frames (images extracted - * from a video) using bounding boxes. For example, you can use this task to ask workers to - * identify and localize various objects in a series of video frames, such as cars, bikes, - * and pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
- *
- * Video Frame Object Tracking - Use this task type to - * have workers track the movement of objects in a sequence of video frames (images - * extracted from a video) using bounding boxes. For example, you can use this task to ask - * workers to track the movement of objects, such as cars, bikes, and pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
- *
- * 3D Point Cloud Modalities - *
- *Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. - * See 3D Point Cloud Task types - * to learn more.
- *- * 3D Point Cloud Object Detection - - * Use this task type when you want workers to classify objects in a 3D point cloud by - * drawing 3D cuboids around objects. For example, you can use this task type to ask workers - * to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
- *
- * 3D Point Cloud Object Tracking - - * Use this task type when you want workers to draw 3D cuboids around objects - * that appear in a sequence of 3D point cloud frames. - * For example, you can use this task type to ask workers to track - * the movement of vehicles across multiple point cloud frames. - *
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
- *
- * 3D Point Cloud Semantic Segmentation - - * Use this task type when you want workers to create a point-level semantic segmentation masks by - * painting objects in a 3D point cloud using different colors where each color is assigned to one of - * the classes you specify.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
- *
- * Use the following ARNs for Label Verification and Adjustment Jobs - *
- *Use label verification and adjustment jobs to review and adjust labels. To learn more, - * see Verify and Adjust Labels .
- *- * Bounding box verification - Uses a variant of the - * Expectation Maximization approach to estimate the true class of verification - * judgement for bounding box labels based on annotations from individual - * workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
- *
- * Bounding box adjustment - Finds the most similar boxes - * from different workers based on the Jaccard index of the adjusted - * annotations.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
- *
- * Semantic segmentation verification - Uses a variant of - * the Expectation Maximization approach to estimate the true class of verification - * judgment for semantic segmentation labels based on annotations from individual - * workers.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
- *
- * Semantic segmentation adjustment - Treats each pixel in - * an image as a multi-class classification and treats pixel adjusted annotations - * from workers as "votes" for the correct label.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
- *
- * Video Frame Object Detection Adjustment - - * Use this task type when you want workers to adjust bounding boxes that workers have added - * to video frames to classify and localize objects in a sequence of video frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
- *
- * Video Frame Object Tracking Adjustment - - * Use this task type when you want workers to adjust bounding boxes that workers have added - * to video frames to track object movement across a sequence of video frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
- *
- * 3D point cloud object detection adjustment - Adjust - * 3D cuboids in a point cloud frame.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
- *
- * 3D point cloud object tracking adjustment - Adjust 3D - * cuboids across a sequence of point cloud frames.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
- *
- * 3D point cloud semantic segmentation adjustment - - * Adjust semantic segmentation masks in a 3D point cloud.
- *
- * arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
- * arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
- *
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
Keywords used to describe the task so that workers on Amazon Mechanical Turk can - * discover the task.
+ *Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
* @public */ TaskKeywords?: string[] | undefined; @@ -11106,46 +6403,19 @@ export interface HumanTaskConfig { NumberOfHumanWorkersPerDataObject: number | undefined; /** - *The amount of time that a worker has to complete a task.
- *If you create a custom labeling job, the maximum value for this parameter is 8 hours - * (28,800 seconds).
- *If you create a labeling job using a built-in task type the maximum - * for this parameter depends on the task type you use:
- *For image and - * text labeling jobs, - * the maximum is 8 hours (28,800 seconds).
- *For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
- *The amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The length of time that a task remains available for labeling by human workers. The - * default and maximum values for this parameter depend on the type of workforce you - * use.
- *If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). - * The default is 6 hours (21,600 seconds).
- *If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
- *The length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
Defines the maximum number of data objects that can be labeled by human workers at the - * same time. Also referred to as batch size. Each object may have more than one worker at one time. - * The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
+ *Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
* @public */ MaxConcurrentTaskCount?: number | undefined; @@ -11164,15 +6434,12 @@ export interface HumanTaskConfig { } /** - *Attributes of the data specified by the customer. Use these to describe the data to be - * labeled.
+ *Attributes of the data specified by the customer. Use these to describe the data to be labeled.
* @public */ export interface LabelingJobDataAttributes { /** - *Declares that your content is free of personally identifiable information or adult - * content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task - * based on this information.
+ *Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
* @public */ ContentClassifiers?: ContentClassifier[] | undefined; @@ -11184,25 +6451,7 @@ export interface LabelingJobDataAttributes { */ export interface LabelingJobS3DataSource { /** - *The Amazon S3 location of the manifest file that describes the input data objects.
- *The input manifest file referenced in ManifestS3Uri must contain one of
- * the following keys: source-ref or source. The value of the
- * keys are interpreted as follows:
- * source-ref: The source of the object is the Amazon S3 object
- * specified in the value. Use this value when the object is a binary object, such
- * as an image.
- * source: The source of the object is the value. Use this
- * value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to - * create an input manifest file.
+ *The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri must contain one of the following keys: source-ref or source. The value of the keys are interpreted as follows:
source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
* @public */ ManifestS3Uri: string | undefined; @@ -11214,22 +6463,14 @@ export interface LabelingJobS3DataSource { */ export interface LabelingJobSnsDataSource { /** - *The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic - * you will use to send new data objects to a streaming labeling job.
+ *The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
* @public */ SnsTopicArn: string | undefined; } /** - *Provides information about the location of input data.
- *You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic
- * for a streaming labeling job. If you do not specify
- * and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input
- * manifest file for both streaming and one-time labeling jobs.
- * Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
Provides information about the location of input data.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
Configure encryption on the storage volume attached to the ML compute instance used to - * run automated data labeling model training and inference.
+ *Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
* @public */ export interface LabelingJobResourceConfig { /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume - * attached to the ML compute instance(s) that run the training and inference jobs used for - * automated data labeling.
- *You can only specify a VolumeKmsKeyId when you create a labeling job with
- * automated data labeling enabled using the API operation CreateLabelingJob.
- * You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for
- * automated data labeling model training and inference when you create a labeling job
- * using the console. To learn more, see Output Data and Storage Volume
- * Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
- *
- * "1234abcd-12ab-34cd-56ef-1234567890ab"
- *
Amazon Resource Name (ARN) of a KMS Key
- *
- * "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
- *
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; } /** - *Provides configuration information for auto-labeling of your data objects. A
- * LabelingJobAlgorithmsConfig object must be supplied in order to use
- * auto-labeling.
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You - * must select one of the following ARNs:
- *- * Image classification - *
- *
- * arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
- *
- * Text classification - *
- *
- * arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
- *
- * Object detection - *
- *
- * arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
- *
- * Semantic Segmentation - *
- *
- * arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
- *
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final - * model used for auto-labeling. You can use this model as the starting point for - * subsequent similar jobs by providing the ARN of the model here.
+ *At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
* @public */ InitialActiveLearningModelArn?: string | undefined; @@ -11384,42 +6559,20 @@ export interface LabelingJobOutputConfig { S3OutputPath: string | undefined; /** - *The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
- *If you provide your own KMS key ID, you must add the required permissions to your KMS - * key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
- *If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your - * role's account to encrypt your output data.
- *If you use a bucket policy with an s3:PutObject permission that only
- * allows objects with server-side encryption, set the condition key of
- * s3:x-amz-server-side-encryption to "aws:kms". For more
- * information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer
- * Guide.
- *
The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.
If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to
- * do real time chaining to another streaming job and receive an Amazon SNS notifications each
- * time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers
- * complete labeling tasks, Ground Truth will send labeling task output data to the SNS output
- * topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling - * Job.
+ *An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
* @public */ SnsTopicArn?: string | undefined; } /** - *A set of conditions for stopping a labeling job. If any of the conditions are met, the - * job is automatically stopped. You can use these conditions to control the cost of data - * labeling.
- *Labeling jobs fail after 30 days with an appropriate client error message.
- *A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
The name of the labeling job. This name is used to identify the job in a list of
- * labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region.
- * LabelingJobName is not case sensitive. For example, Example-job and
- * example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The attribute name to use for the label in the output manifest file. This is the key
- * for the key/value pair formed with the label that a worker assigns to the object. The
- * LabelAttributeName must meet the following requirements.
The name can't end with "-metadata".
- *If you are using one of the following built-in task types, - * the attribute name must end with "-ref". If the task type - * you are using is not listed below, the attribute name must - * not end with "-ref".
- *Image semantic segmentation (SemanticSegmentation), and
- * adjustment (AdjustmentSemanticSegmentation) and
- * verification (VerificationSemanticSegmentation) labeling
- * jobs for this task type.
Video frame object detection (VideoObjectDetection), and
- * adjustment and verification
- * (AdjustmentVideoObjectDetection) labeling jobs for this
- * task type.
Video frame object tracking (VideoObjectTracking), and
- * adjustment and verification (AdjustmentVideoObjectTracking)
- * labeling jobs for this task type.
3D point cloud semantic segmentation
- * (3DPointCloudSemanticSegmentation), and adjustment and
- * verification (Adjustment3DPointCloudSemanticSegmentation)
- * labeling jobs for this task type.
3D point cloud object tracking
- * (3DPointCloudObjectTracking), and adjustment and
- * verification (Adjustment3DPointCloudObjectTracking)
- * labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a
- * different
- * LabelAttributeName than the one used in the original labeling job. The
- * original labeling job is the Ground Truth labeling job that produced the labels that you
- * want verified or adjusted. To learn more about adjustment and verification labeling
- * jobs, see Verify and Adjust
- * Labels.
The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
The name can't end with "-metadata".
If you are using one of the following built-in task types, the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
Input data for the labeling job, such as the Amazon S3 location of the data objects and the - * location of the manifest file that describes the data objects.
- *You must specify at least one of the following: S3DataSource or
- * SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming
- * labeling job. If you do not specify and SNS input topic ARN, Ground Truth will
- * create a one-time labeling job that stops after all data objects in the input
- * manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both
- * streaming and one-time labeling jobs. Adding an S3DataSource is
- * optional if you use SnsDataSource to create a streaming labeling
- * job.
If you use the Amazon Mechanical Turk workforce, your input data should not include
- * confidential information, personal information or protected health information. Use
- * ContentClassifiers to specify that your data is free of personally
- * identifiable information and adult content.
Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.
The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt - * the output data, if any.
+ *The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
* @public */ OutputConfig: LabelingJobOutputConfig | undefined; /** - *The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf - * during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker - * can successfully complete data labeling.
+ *The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
* @public */ RoleArn: string | undefined; /** - *The S3 URI of the file, referred to as a label category configuration - * file, that defines the categories used to label the data objects.
- *For 3D point cloud and video frame task types, you can add label category attributes - * and frame attributes to your label category configuration file. To learn how, see Create a - * Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
- *For named entity recognition jobs, in addition to Add Instructions Add additional instructions."labels", you must
- * provide worker instructions in the label category configuration file using the
- * "instructions" parameter: "instructions":
- * \{"shortInstruction":". For details
- * and an example, see Create a
- * Named Entity Recognition Labeling Job (API) .Add header
For all other built-in task types and custom
- * tasks, your label category configuration file must be a JSON file in the
- * following format. Identify the labels you want to use by replacing label_1,
- * label_2,...,label_n with your label
- * categories.
- * \{
- *
- * "document-version": "2018-11-28",
- *
- * "labels": [\{"label": "label_1"\},\{"label": "label_2"\},...\{"label":
- * "label_n"\}]
- *
- * \}
- *
Note the following about the label category configuration file:
- *For image classification and text classification (single and multi-label) you - * must specify at least two label categories. For all other task types, the - * minimum number of label categories required is one.
- *Each label category must be unique, you cannot specify duplicate label - * categories.
- *If you create a 3D point cloud or video frame adjustment or verification
- * labeling job, you must include auditLabelAttributeName in the label
- * category configuration. Use this parameter to enter the
- * LabelAttributeName
- * of the labeling job you want to
- * adjust or verify annotations of.
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to "labels", you must provide worker instructions in the label category configuration file using the "instructions" parameter: "instructions": \{"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>", "fullInstruction":"<p>Add additional instructions.</p>"\}. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.
\{
"document-version": "2018-11-28",
"labels": [\{"label": "label_1"\},\{"label": "label_2"\},...\{"label": "label_n"\}]
\}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
A set of conditions for stopping the labeling job. If any of the conditions are met, - * the job is automatically stopped. You can use these conditions to control the cost of - * data labeling.
+ *A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
* @public */ StoppingConditions?: LabelingJobStoppingConditions | undefined; @@ -11627,8 +6648,7 @@ export interface CreateLabelingJobRequest { HumanTaskConfig: HumanTaskConfig | undefined; /** - *An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management - * User Guide.
+ *An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -11639,8 +6659,7 @@ export interface CreateLabelingJobRequest { */ export interface CreateLabelingJobResponse { /** - *The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the - * labeling job.
+ *The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
* @public */ LabelingJobArn: string | undefined; @@ -11666,50 +6685,37 @@ export type TrackingServerSize = (typeof TrackingServerSize)[keyof typeof Tracki */ export interface CreateMlflowTrackingServerRequest { /** - *A unique string identifying the tracking server name. This string is part of the tracking server - * ARN.
+ *A unique string identifying the tracking server name. This string is part of the tracking server ARN.
* @public */ TrackingServerName: string | undefined; /** - *The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact - * store.
+ *The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
* @public */ ArtifactStoreUri: string | undefined; /** - *The size of the tracking server you want to create. You can choose between
- * "Small", "Medium", and "Large". The default MLflow
- * Tracking Server configuration size is "Small". You can choose a size depending on
- * the projected use of the tracking server such as the volume of data logged, number of users,
- * and frequency of use.
We recommend using a small tracking server for teams of up to 25 users, a medium tracking - * server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
+ *The size of the tracking server you want to create. You can choose between "Small", "Medium", and "Large". The default MLflow Tracking Server configuration size is "Small". You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.
We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
* @public */ TrackingServerSize?: TrackingServerSize | undefined; /** - *The version of MLflow that the tracking server uses. To see which MLflow versions are - * available to use, see How it works.
+ *The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
* @public */ MlflowVersion?: string | undefined; /** - *The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to
- * access the artifact store in Amazon S3. The role should have AmazonS3FullAccess
- * permissions. For more information on IAM permissions for tracking server creation, see
- * Set up IAM permissions for MLflow.
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have AmazonS3FullAccess permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True.
- * To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.
How containers in a multi-container are run. The following values are valid.
- *
- * SERIAL - Containers run as a serial pipeline.
- * DIRECT - Only the individual container that you specify is
- * run.
How containers in a multi-container are run. The following values are valid.
SERIAL - Containers run as a serial pipeline.
DIRECT - Only the individual container that you specify is run.
The location of the primary docker image containing inference code, associated - * artifacts, and custom environment map that the inference code uses when the model is - * deployed for predictions.
+ *The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
* @public */ PrimaryContainer?: ContainerDefinition | undefined; @@ -11806,40 +6799,25 @@ export interface CreateModelInput { InferenceExecutionConfig?: InferenceExecutionConfig | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model - * artifacts and docker image for deployment on ML compute instances or for batch transform - * jobs. Deploying on ML compute instances is part of model hosting. For more information, - * see SageMaker - * Roles.
- *To be able to pass this role to SageMaker, the caller of this API must have the
- * iam:PassRole permission.
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; /** - *A VpcConfig object that specifies the VPC that you want your model to connect
- * to. Control access to and from your model container by configuring the VPC.
- * VpcConfig is used in hosting services and in batch transform. For more
- * information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch
- * Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
Isolates the model container. No inbound or outbound network calls can be made to or - * from the model container.
+ *Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
* @public */ EnableNetworkIsolation?: boolean | undefined; @@ -11868,9 +6846,7 @@ export interface ModelBiasAppSpecification { ImageUri: string | undefined; /** - *JSON formatted S3 file that defines bias parameters. For more information on this JSON - * configuration file, see Configure - * bias parameters.
+ *JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
* @public */ ConfigUri: string | undefined; @@ -11941,8 +6917,7 @@ export interface ModelBiasJobInput { */ export interface CreateModelBiasJobDefinitionRequest { /** - *The name of the bias job definition. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobDefinitionName: string | undefined; @@ -11984,8 +6959,7 @@ export interface CreateModelBiasJobDefinitionRequest { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -11997,9 +6971,7 @@ export interface CreateModelBiasJobDefinitionRequest { StoppingCondition?: MonitoringStoppingCondition | undefined; /** - *(Optional) An array of key-value pairs. For more information, see - * - * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -12038,9 +7010,7 @@ export type ModelCardStatus = (typeof ModelCardStatus)[keyof typeof ModelCardSta */ export interface ModelCardSecurityConfig { /** - *A Key Management Service - * key - * ID to use for encrypting a model card.
+ *A Key Management Service key ID to use for encrypting a model card.
* @public */ KmsKeyId?: string | undefined; @@ -12057,9 +7027,7 @@ export interface CreateModelCardRequest { ModelCardName: string | undefined; /** - *An optional Key Management Service - * key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with - * highly sensitive data.
+ *An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
* @public */ SecurityConfig?: ModelCardSecurityConfig | undefined; @@ -12071,26 +7039,7 @@ export interface CreateModelCardRequest { Content: string | undefined; /** - *The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
JSON formatted Amazon S3 file that defines explainability parameters. For more - * information on this JSON configuration file, see Configure model explainability parameters.
+ *JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
* @public */ ConfigUri: string | undefined; @@ -12231,8 +7179,7 @@ export interface ModelExplainabilityJobInput { */ export interface CreateModelExplainabilityJobDefinitionRequest { /** - *The name of the model explainability job definition. The name must be unique within an - * Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobDefinitionName: string | undefined; @@ -12274,8 +7221,7 @@ export interface CreateModelExplainabilityJobDefinitionRequest { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -12287,9 +7233,7 @@ export interface CreateModelExplainabilityJobDefinitionRequest { StoppingCondition?: MonitoringStoppingCondition | undefined; /** - *(Optional) An array of key-value pairs. For more information, see - * - * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -12331,8 +7275,7 @@ export interface FileSource { } /** - *Represents the drift check bias baselines that can be used when the model monitor is - * set using the model package.
+ *Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
* @public */ export interface DriftCheckBias { @@ -12356,8 +7299,7 @@ export interface DriftCheckBias { } /** - *Represents the drift check explainability baselines that can be used when the model - * monitor is set using the model package.
+ *Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
* @public */ export interface DriftCheckExplainability { @@ -12375,8 +7317,7 @@ export interface DriftCheckExplainability { } /** - *Represents the drift check data quality baselines that can be used when the model - * monitor is set using the model package.
+ *Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
* @public */ export interface DriftCheckModelDataQuality { @@ -12394,8 +7335,7 @@ export interface DriftCheckModelDataQuality { } /** - *Represents the drift check model quality baselines that can be used when the model - * monitor is set using the model package.
+ *Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
* @public */ export interface DriftCheckModelQuality { @@ -12413,84 +7353,48 @@ export interface DriftCheckModelQuality { } /** - *Represents the drift check baselines that can be used when the model monitor is set - * using the model package.
+ *Represents the drift check baselines that can be used when the model monitor is set using the model package.
* @public */ export interface DriftCheckBaselines { /** - *Represents the drift check bias baselines that can be used when the model monitor is - * set using the model package.
+ *Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
* @public */ Bias?: DriftCheckBias | undefined; /** - *Represents the drift check explainability baselines that can be used when the model - * monitor is set using the model package.
+ *Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
* @public */ Explainability?: DriftCheckExplainability | undefined; /** - *Represents the drift check model quality baselines that can be used when the model - * monitor is set using the model package.
+ *Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
* @public */ ModelQuality?: DriftCheckModelQuality | undefined; /** - *Represents the drift check model data quality baselines that can be used when the - * model monitor is set using the model package.
+ *Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
* @public */ ModelDataQuality?: DriftCheckModelDataQuality | undefined; } /** - *The model card associated with the model package. Since
- * ModelPackageModelCard is tied to a model package, it is a specific
- * usage of a model card and its schema is simplified compared to the schema of
- * ModelCard. The ModelPackageModelCard schema does not
- * include model_package_details, and model_overview is composed
- * of the model_creator and model_artifact properties. For more
- * information about the model package model card schema, see Model
- * package model card schema. For more information about the model card
- * associated with the model package, see View the Details of a Model
- * Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
The content of the model card. The content must follow the schema described in Model - * Package Model Card Schema.
+ *The content of the model card. The content must follow the schema described in Model Package Model Card Schema.
* @public */ ModelCardContent?: string | undefined; /** - *The approval status of the model card within your organization. Different - * organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates can be made
- * to the model card content. If you try to update the model card content, you will
- * receive the message Model Card is in Archived state.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates can be made to the model card content. If you try to update the model card content, you will receive the message Model Card is in Archived state.
An optional Key Management Service key to encrypt, decrypt, and re-encrypt model - * package information for regulated workloads with highly sensitive data.
+ *An optional Key Management Service key to encrypt, decrypt, and re-encrypt model package information for regulated workloads with highly sensitive data.
* @public */ export interface ModelPackageSecurityConfig { /** - *The KMS Key ID (KMSKeyId) used for encryption of model
- * package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
Specifies an algorithm that was used to create the model package. The algorithm must - * be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
+ *Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
* @public */ export interface SourceAlgorithm { /** - *The Amazon S3 path where the model artifacts, which result from model training, are stored.
- * This path must point to a single gzip compressed tar archive
- * (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services - * region as the algorithm.
- *The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
The name of an algorithm that was used to create the model package. The algorithm must - * be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
+ *The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
* @public */ AlgorithmName: string | undefined; @@ -12677,10 +7571,7 @@ export interface SourceAlgorithmSpecification { } /** - *Contains data, such as the inputs and targeted instance types that are used in the - * process of validating the model package.
- *The data provided in the validation profile is made available to your buyers on - * Amazon Web Services Marketplace.
+ *Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
* @public */ export interface ModelPackageValidationProfile { @@ -12691,8 +7582,7 @@ export interface ModelPackageValidationProfile { ProfileName: string | undefined; /** - *The TransformJobDefinition object that describes the transform job used
- * for the validation of the model package.
The TransformJobDefinition object that describes the transform job used for the validation of the model package.
An array of ModelPackageValidationProfile objects, each of which
- * specifies a batch transform job that SageMaker runs to validate your model package.
An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
The name of the model package. The name must have 1 to 63 characters. Valid characters - * are a-z, A-Z, 0-9, and - (hyphen).
- *This parameter is required for unversioned models. It is not applicable to versioned - * models.
+ *The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
* @public */ ModelPackageName?: string | undefined; /** - *The name or Amazon Resource Name (ARN) of the model package group that this model version belongs - * to.
- *This parameter is required for versioned models, and does not apply to unversioned - * models.
+ *The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
* @public */ ModelPackageGroupName?: string | undefined; @@ -12746,29 +7629,13 @@ export interface CreateModelPackageInput { ModelPackageDescription?: string | undefined; /** - *Specifies details about inference jobs that you can run with models based on this - * model package, including the following information:
- *The Amazon ECR paths of containers that contain the inference code and model - * artifacts.
- *The instance types that the model package supports for transform jobs and - * real-time endpoints used for inference.
- *The input and output content formats that the model package supports for - * inference.
- *Specifies details about inference jobs that you can run with models based on this model package, including the following information:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Specifies configurations for one or more transform jobs that SageMaker runs to test the - * model package.
+ *Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
* @public */ ValidationSpecification?: ModelPackageValidationSpecification | undefined; @@ -12780,30 +7647,19 @@ export interface CreateModelPackageInput { SourceAlgorithmSpecification?: SourceAlgorithmSpecification | undefined; /** - *Whether to certify the model package for listing on Amazon Web Services - * Marketplace.
- *This parameter is optional for unversioned models, and does not apply to versioned - * models.
+ *Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
* @public */ CertifyForMarketplace?: boolean | undefined; /** - *A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
- *If you supply ModelPackageGroupName, your model package belongs to the
- * model group you specify and uses the tags associated with the model group. In this case,
- * you cannot supply a tag argument.
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag argument.
Whether the model is approved for deployment.
- *This parameter is optional for versioned models, and does not apply to unversioned - * models.
- *For versioned models, the value of this parameter must be set to Approved
- * to deploy the model.
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved to deploy the model.
The machine learning domain of your model package and its components. Common machine - * learning domains include computer vision and natural language processing.
+ *The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
* @public */ Domain?: string | undefined; /** - *The machine learning task your model package accomplishes. Common machine learning
- * tasks include object detection and image classification. The following tasks are
- * supported by Inference Recommender: "IMAGE_CLASSIFICATION" |
- * "OBJECT_DETECTION" | "TEXT_GENERATION"
- * |"IMAGE_SEGMENTATION" | "FILL_MASK" |
- * "CLASSIFICATION" | "REGRESSION" |
- * "OTHER".
Specify "OTHER" if none of the tasks listed fit your use case.
+ *The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION" | "OBJECT_DETECTION" | "TEXT_GENERATION" |"IMAGE_SEGMENTATION" | "FILL_MASK" | "CLASSIFICATION" | "REGRESSION" | "OTHER".
Specify "OTHER" if none of the tasks listed fit your use case.
* @public */ Task?: string | undefined; /** - *The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a - * single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple - * files that are all equally used in the load test. Each file in the archive must satisfy - * the size constraints of the InvokeEndpoint call.
+ *The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
* @public */ SamplePayloadUrl?: string | undefined; @@ -12862,18 +7707,13 @@ export interface CreateModelPackageInput { CustomerMetadataProperties?: RecordRepresents the drift check baselines that can be used when the model monitor is set - * using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker - * Pipelines in the Amazon SageMaker Developer Guide.
+ *Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
* @public */ DriftCheckBaselines?: DriftCheckBaselines | undefined; /** - *An array of additional Inference Specification objects. Each additional Inference - * Specification specifies artifacts based on this model package that can be used on - * inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts. - *
+ *An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
* @public */ AdditionalInferenceSpecifications?: AdditionalInferenceSpecificationDefinition[] | undefined; @@ -12885,31 +7725,19 @@ export interface CreateModelPackageInput { SkipModelValidation?: SkipModelValidation | undefined; /** - *The URI of the source for the model package. If you want to clone a model package, set - * it to the model package Amazon Resource Name (ARN). If you want to register a model, set - * it to the model ARN.
+ *The URI of the source for the model package. If you want to clone a model package, set it to the model package Amazon Resource Name (ARN). If you want to register a model, set it to the model ARN.
* @public */ SourceUri?: string | undefined; /** - *The KMS Key ID (KMSKeyId) used for encryption of model
- * package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
The model card associated with the model package. Since
- * ModelPackageModelCard is tied to a model package, it is a specific
- * usage of a model card and its schema is simplified compared to the schema of
- * ModelCard. The ModelPackageModelCard schema does not
- * include model_package_details, and model_overview is composed
- * of the model_creator and model_artifact properties. For more
- * information about the model package model card schema, see Model
- * package model card schema. For more information about the model card
- * associated with the model package, see View the Details of a Model
- * Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
A list of key value pairs associated with the model group. For more information, see - * Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
+ *A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -13007,16 +7833,13 @@ export interface ModelQualityAppSpecification { ContainerArguments?: string[] | undefined; /** - *An Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use - * the converted data. Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
* @public */ RecordPreprocessorSourceUri?: string | undefined; /** - *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable - * only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
* @public */ PostAnalyticsProcessorSourceUri?: string | undefined; @@ -13035,9 +7858,7 @@ export interface ModelQualityAppSpecification { } /** - *Configuration for monitoring constraints and monitoring statistics. These baseline resources are - * compared against the results of the current job from the series of jobs scheduled to collect data - * periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
* @public */ export interface ModelQualityBaselineConfig { @@ -13055,8 +7876,7 @@ export interface ModelQualityBaselineConfig { } /** - *The input for the model quality monitoring job. Currently endpoints are supported for - * input for model quality monitoring jobs.
+ *The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
* @public */ export interface ModelQualityJobInput { @@ -13126,8 +7946,7 @@ export interface CreateModelQualityJobDefinitionRequest { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -13139,9 +7958,7 @@ export interface CreateModelQualityJobDefinitionRequest { StoppingCondition?: MonitoringStoppingCondition | undefined; /** - *(Optional) An array of key-value pairs. For more information, see - * - * Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -13159,9 +7976,7 @@ export interface CreateModelQualityJobDefinitionResponse { } /** - *Configuration for monitoring constraints and monitoring statistics. These baseline resources are - * compared against the results of the current job from the series of jobs scheduled to collect data - * periodically.
+ *Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
* @public */ export interface MonitoringBaselineConfig { @@ -13172,15 +7987,13 @@ export interface MonitoringBaselineConfig { BaseliningJobName?: string | undefined; /** - *The baseline constraint file in Amazon S3 that the current monitoring job should - * validated against.
+ *The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
* @public */ ConstraintsResource?: MonitoringConstraintsResource | undefined; /** - *The baseline statistics file in Amazon S3 that the current monitoring job should - * be validated against.
+ *The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
* @public */ StatisticsResource?: MonitoringStatisticsResource | undefined; @@ -13210,16 +8023,13 @@ export interface MonitoringAppSpecification { ContainerArguments?: string[] | undefined; /** - *An Amazon S3 URI to a script that is called per row prior to running analysis. It can - * base64 decode the payload and convert it into a flattened JSON so that the built-in container can use - * the converted data. Applicable only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
* @public */ RecordPreprocessorSourceUri?: string | undefined; /** - *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable - * only for the built-in (first party) containers.
+ *An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
* @public */ PostAnalyticsProcessorSourceUri?: string | undefined; diff --git a/clients/client-sagemaker/src/models/models_2.ts b/clients/client-sagemaker/src/models/models_2.ts index 891d7ac9164e..2603b0a52655 100644 --- a/clients/client-sagemaker/src/models/models_2.ts +++ b/clients/client-sagemaker/src/models/models_2.ts @@ -148,32 +148,24 @@ export interface MonitoringInput { } /** - *Networking options for a job, such as network traffic encryption between containers, - * whether to allow inbound and outbound network calls to and from containers, and the VPC - * subnets and security groups to use for VPC-enabled jobs.
+ *Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
* @public */ export interface NetworkConfig { /** - *Whether to encrypt all communications between distributed processing jobs. Choose
- * True to encrypt communications. Encryption provides greater security
- * for distributed processing jobs, but the processing might take longer.
Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for - * the processing job.
+ *Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
* @public */ EnableNetworkIsolation?: boolean | undefined; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; @@ -185,8 +177,7 @@ export interface NetworkConfig { */ export interface MonitoringJobDefinition { /** - *Baseline configuration used to validate that the data conforms to the specified - * constraints and statistics
+ *Baseline configuration used to validate that the data conforms to the specified constraints and statistics
* @public */ BaselineConfig?: MonitoringBaselineConfig | undefined; @@ -204,8 +195,7 @@ export interface MonitoringJobDefinition { MonitoringOutputConfig: MonitoringOutputConfig | undefined; /** - *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a - * monitoring job. In distributed processing, you specify more than one instance.
+ *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
* @public */ MonitoringResources: MonitoringResources | undefined; @@ -235,8 +225,7 @@ export interface MonitoringJobDefinition { NetworkConfig?: NetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -264,100 +253,19 @@ export type MonitoringType = (typeof MonitoringType)[keyof typeof MonitoringType */ export interface ScheduleConfig { /** - *A cron expression that describes details about the monitoring schedule.
- *The supported cron expressions are:
- *If you want to set the job to start every hour, use the following:
- *
- * Hourly: cron(0 * ? * * *)
- *
If you want to start the job daily:
- *
- * cron(0 [00-23] ? * * *)
- *
If you want to run the job one time, immediately, use the following - * keyword:
- *
- * NOW
- *
For example, the following are valid cron expressions:
- *Daily at noon UTC: cron(0 12 ? * * *)
- *
Daily at midnight UTC: cron(0 0 ? * * *)
- *
To support running every 6, 12 hours, the following are also supported:
- *
- * cron(0 [00-23]/[01-24] ? * * *)
- *
For example, the following are valid cron expressions:
- *Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
- *
Every two hours starting at midnight: cron(0 0/2 ? * * *)
- *
Even though the cron expression is set to start at 5PM UTC, note that there - * could be a delay of 0-20 minutes from the actual requested time to run the - * execution.
- *We recommend that if you would like a daily schedule, you do not provide this - * parameter. Amazon SageMaker AI will pick a time for running every day.
- *You can also specify the keyword NOW to run the monitoring job immediately,
- * one time, without recurring.
A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker AI will pick a time for running every day.
You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.
Sets the start time for a monitoring job window. Express this time as an offset to the
- * times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the
- * ScheduleExpression parameter. Specify this offset in ISO 8601 duration
- * format. For example, if you want to monitor the five hours of data in your dataset that
- * precede the start of each monitoring job, you would specify: "-PT5H".
The start time that you specify must not precede the end time that you specify by more
- * than 24 hours. You specify the end time with the DataAnalysisEndTime
- * parameter.
If you set ScheduleExpression to NOW, this parameter is
- * required.
Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: "-PT5H".
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the
- * times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the
- * ScheduleExpression parameter. Specify this offset in ISO 8601 duration
- * format. For example, if you want to end the window one hour before the start of each
- * monitoring job, you would specify: "-PT1H".
The end time that you specify must not follow the start time that you specify by more
- * than 24 hours. You specify the start time with the DataAnalysisStartTime
- * parameter.
If you set ScheduleExpression to NOW, this parameter is
- * required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: "-PT1H".
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
The name of the monitoring schedule. The name must be unique within an Amazon Web Services - * Region within an Amazon Web Services account.
+ *The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
* @public */ MonitoringScheduleName: string | undefined; /** - *The configuration object that specifies the monitoring schedule and defines the monitoring - * job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring job.
* @public */ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; /** - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost - * Management User Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -469,10 +374,7 @@ export type DirectInternetAccess = (typeof DirectInternetAccess)[keyof typeof Di */ export interface InstanceMetadataServiceConfiguration { /** - *Indicates the minimum IMDS version that the notebook instance supports. When passed as
- * part of CreateNotebookInstance, if no value is selected, then it defaults
- * to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of
- * UpdateNotebookInstance, there is no default.
Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
The ID of the subnet in a VPC to which you would like to have a connectivity from - * your ML compute instance.
+ *The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
* @public */ SubnetId?: string | undefined; /** - *The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be - * for the same VPC as specified in the subnet.
+ *The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
* @public */ SecurityGroupIds?: string[] | undefined; /** - *When you send any requests to Amazon Web Services resources from the notebook - * instance, SageMaker AI assumes this role to perform tasks on your behalf. You must - * grant this role necessary permissions so SageMaker AI can perform these tasks. The - * policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com) - * permissions to assume this role. For more information, see SageMaker AI Roles.
- *To be able to pass this role to SageMaker AI, the caller of this API must
- * have the iam:PassRole permission.
When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker AI assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker AI can perform these tasks. The policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker AI Roles.
To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that - * SageMaker AI uses to encrypt data on the storage volume attached to your - * notebook instance. The KMS key you provide must be enabled. For information, see Enabling and - * Disabling Keys in the Amazon Web Services Key Management Service - * Developer Guide.
+ *The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker AI uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
* @public */ KmsKeyId?: string | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; /** - *The name of a lifecycle configuration to associate with the notebook instance. For - * information about lifestyle configurations, see Step 2.1: (Optional) - * Customize a Notebook Instance.
+ *The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @public */ LifecycleConfigName?: string | undefined; /** - *Sets whether SageMaker AI provides internet access to the notebook instance. If
- * you set this to Disabled this notebook instance is able to access resources
- * only in your VPC, and is not be able to connect to SageMaker AI training and
- * endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value
- * of this parameter to Disabled only if you set a value for the
- * SubnetId parameter.
Sets whether SageMaker AI provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker AI training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
The size, in GB, of the ML storage volume to attach to the notebook instance. The - * default value is 5 GB.
+ *The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
* @public */ VolumeSizeInGB?: number | undefined; /** - *This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify a list of EI instance types to associate with this - * notebook instance.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of EI instance types to associate with this notebook instance.
* @public */ AcceleratorTypes?: NotebookInstanceAcceleratorType[] | undefined; /** - *A Git repository to associate with the notebook instance as its default code - * repository. This can be either the name of a Git repository stored as a resource in your - * account, or the URL of a Git repository in Amazon Web Services CodeCommit - * or in any other Git repository. When you open a notebook instance, it opens in the - * directory that contains this repository. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ DefaultCodeRepository?: string | undefined; /** - *An array of up to three Git repositories to associate with the notebook instance. - * These can be either the names of Git repositories stored as resources in your account, - * or the URL of Git repositories in Amazon Web Services CodeCommit - * or in any other Git repository. These repositories are cloned at the same level as the - * default repository of your notebook instance. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ AdditionalCodeRepositories?: string[] | undefined; /** - *Whether root access is enabled or disabled for users of the notebook instance. The
- * default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook - * instance. Because of this, lifecycle configurations associated with a notebook - * instance always run with root access even if you disable root access for - * users.
- *Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Contains the notebook instance lifecycle configuration script.
- *Each lifecycle configuration script has a limit of 16384 characters.
- *The value of the $PATH environment variable that is available to both
- * scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log
- * group /aws/sagemaker/NotebookInstances in log stream
- * [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs - * for longer than 5 minutes, it fails and the notebook instance is not created or - * started.
- *For information about notebook instance lifestyle configurations, see Step - * 2.1: (Optional) Customize a Notebook Instance.
+ *Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @public */ export interface NotebookInstanceLifecycleHook { /** - *A base64-encoded string that contains a shell script for a notebook instance lifecycle - * configuration.
+ *A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
* @public */ Content?: string | undefined; @@ -684,23 +529,19 @@ export interface CreateNotebookInstanceLifecycleConfigInput { NotebookInstanceLifecycleConfigName: string | undefined; /** - *A shell script that runs only once, when you create a notebook instance. The shell - * script must be a base64-encoded string.
+ *A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
* @public */ OnCreate?: NotebookInstanceLifecycleHook[] | undefined; /** - *A shell script that runs every time you start a notebook instance, including when you - * create the notebook instance. The shell script must be a base64-encoded string.
+ *A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
* @public */ OnStart?: NotebookInstanceLifecycleHook[] | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -770,11 +611,7 @@ export type OptimizationJobDeploymentInstanceType = */ export interface OptimizationModelAccessConfig { /** - *Specifies agreement to the model end-user license agreement (EULA). The
- * AcceptEula value must be explicitly defined as True in order
- * to accept the EULA that this model requires. You are responsible for reviewing and
- * complying with any applicable license terms and making sure they are acceptable for your
- * use case before downloading or using a model.
Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
Settings for an optimization technique that you apply with a model optimization - * job.
+ *Settings for an optimization technique that you apply with a model optimization job.
* @public */ export type OptimizationConfig = @@ -944,37 +780,31 @@ export namespace OptimizationConfig { */ export interface OptimizationJobOutputConfig { /** - *The Amazon Resource Name (ARN) of a key in Amazon Web Services KMS. SageMaker uses they key to encrypt the artifacts of the - * optimized model when SageMaker uploads the model to Amazon S3.
+ *The Amazon Resource Name (ARN) of a key in Amazon Web Services KMS. SageMaker uses they key to encrypt the artifacts of the optimized model when SageMaker uploads the model to Amazon S3.
* @public */ KmsKeyId?: string | undefined; /** - *The Amazon S3 URI for where to store the optimized model that you create with an optimization - * job.
+ *The Amazon S3 URI for where to store the optimized model that you create with an optimization job.
* @public */ S3OutputLocation: string | undefined; } /** - *A VPC in Amazon VPC that's accessible to an optimized that you create with an optimization - * job. You can control access to and from your resources by configuring a VPC. For more - * information, see Give SageMaker Access to Resources in your Amazon VPC.
+ *A VPC in Amazon VPC that's accessible to an optimized that you create with an optimization job. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ export interface OptimizationVpcConfig { /** - *The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security
- * groups for the VPC that is specified in the Subnets field.
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your optimized - * model.
+ *The ID of the subnets in the VPC to which you want to connect your optimized model.
* @public */ Subnets: string[] | undefined; @@ -991,26 +821,7 @@ export interface CreateOptimizationJobRequest { OptimizationJobName: string | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
- *During model optimization, Amazon SageMaker AI needs your permission to:
- *Read input data from an S3 bucket
- *Write model artifacts to an S3 bucket
- *Write logs to Amazon CloudWatch Logs
- *Publish metrics to Amazon CloudWatch
- *You grant permissions for all of these tasks to an IAM role. To pass this
- * role to Amazon SageMaker AI, the caller of this API must have the
- * iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
- *
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model optimization, Amazon SageMaker AI needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker - * ends the job. Use this API to cap costs.
- *To stop a training job, SageMaker sends the algorithm the SIGTERM signal,
- * which delays job termination for 120 seconds. Algorithms can use this 120-second window
- * to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results
- * of a model training job when possible. This attempt to save artifacts is only a best
- * effort case as model might not be in a state from which it can be saved. For example, if
- * training has just started, the model might not be ready to save. When saved, this
- * intermediate data is a valid model artifact. You can use it to create a model with
- * CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model - * artifacts. When training NTMs, make sure that the maximum runtime is sufficient for - * the training job to complete.
- *Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
A list of key-value pairs associated with the optimization job. For more information, - * see Tagging Amazon Web Services resources in the Amazon Web Services General Reference - * Guide.
+ *A list of key-value pairs associated with the optimization job. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -1174,8 +968,7 @@ export interface CreatePartnerAppRequest { ExecutionRoleArn: string | undefined; /** - *SageMaker Partner AI Apps uses Amazon Web Services KMS to encrypt data at rest using an Amazon Web Services managed key by default. For more control, specify a - * customer managed key.
+ *SageMaker Partner AI Apps uses Amazon Web Services KMS to encrypt data at rest using an Amazon Web Services managed key by default. For more control, specify a customer managed key.
* @public */ KmsKeyId?: string | undefined; @@ -1217,8 +1010,7 @@ export interface CreatePartnerAppRequest { ClientToken?: string | undefined; /** - *Each tag consists of a key and an optional value. Tag keys must be unique per - * resource.
+ *Each tag consists of a key and an optional value. Tag keys must be unique per resource.
* @public */ Tags?: Tag[] | undefined; @@ -1270,9 +1062,7 @@ export interface CreatePartnerAppPresignedUrlResponse { } /** - *Configuration that controls the parallelism of the pipeline. - * By default, the parallelism configuration specified applies to all - * executions of the pipeline unless overridden.
+ *Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
* @public */ export interface ParallelismConfiguration { @@ -1295,15 +1085,13 @@ export interface PipelineDefinitionS3Location { Bucket: string | undefined; /** - *The object key (or key name) uniquely identifies the - * object in an S3 bucket.
+ *The object key (or key name) uniquely identifies the object in an S3 bucket.
* @public */ ObjectKey: string | undefined; /** - *Version Id of the pipeline definition file. If not specified, Amazon SageMaker - * will retrieve the latest version.
+ *Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
* @public */ VersionId?: string | undefined; @@ -1326,15 +1114,13 @@ export interface CreatePipelineRequest { PipelineDisplayName?: string | undefined; /** - *The JSON - * pipeline definition of the pipeline.
+ *The JSON pipeline definition of the pipeline.
* @public */ PipelineDefinition?: string | undefined; /** - *The location of the pipeline definition stored in Amazon S3. If specified, - * SageMaker will retrieve the pipeline definition from this location.
+ *The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
* @public */ PipelineDefinitionS3Location?: PipelineDefinitionS3Location | undefined; @@ -1346,8 +1132,7 @@ export interface CreatePipelineRequest { PipelineDescription?: string | undefined; /** - *A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than one time.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
* @public */ ClientRequestToken?: string | undefined; @@ -1365,8 +1150,7 @@ export interface CreatePipelineRequest { Tags?: Tag[] | undefined; /** - *This is the configuration that controls the parallelism of the pipeline. - * If specified, it applies to all runs of this pipeline by default.
+ *This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
* @public */ ParallelismConfiguration?: ParallelismConfiguration | undefined; @@ -1418,41 +1202,7 @@ export interface CreatePresignedDomainUrlRequest { SpaceName?: string | undefined; /** - *The landing page that the user is directed to when accessing the presigned URL. Using this - * value, users can access Studio or Studio Classic, even if it is not the default experience for - * the domain. The supported values are:
- *
- * studio::relative/path: Directs users to the relative path in
- * Studio.
- * app:JupyterServer:relative/path: Directs users to the relative path in
- * the Studio Classic application.
- * app:JupyterLab:relative/path: Directs users to the relative path in the
- * JupyterLab application.
- * app:RStudioServerPro:relative/path: Directs users to the relative path in
- * the RStudio application.
- * app:CodeEditor:relative/path: Directs users to the relative path in the
- * Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
- * app:Canvas:relative/path: Directs users to the relative path in the
- * Canvas application.
The landing page that the user is directed to when accessing the presigned URL. Using this value, users can access Studio or Studio Classic, even if it is not the default experience for the domain. The supported values are:
studio::relative/path: Directs users to the relative path in Studio.
app:JupyterServer:relative/path: Directs users to the relative path in the Studio Classic application.
app:JupyterLab:relative/path: Directs users to the relative path in the JupyterLab application.
app:RStudioServerPro:relative/path: Directs users to the relative path in the RStudio application.
app:CodeEditor:relative/path: Directs users to the relative path in the Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
app:Canvas:relative/path: Directs users to the relative path in the Canvas application.
The duration in seconds that your presigned URL is valid. The presigned URL can be used - * only once.
+ *The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.
* @public */ ExpiresInSeconds?: number | undefined; @@ -1533,25 +1282,7 @@ export interface CreatePresignedNotebookInstanceUrlOutput { } /** - *Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ export interface ExperimentConfig { @@ -1562,15 +1293,13 @@ export interface ExperimentConfig { ExperimentName?: string | undefined; /** - *The name of an existing trial to associate the trial component with. If not specified, a - * new trial is created.
+ *The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
* @public */ TrialName?: string | undefined; /** - *The display name for the trial component. If this key isn't specified, the display name is - * the trial component name.
+ *The display name for the trial component. If this key isn't specified, the display name is the trial component name.
* @public */ TrialComponentDisplayName?: string | undefined; @@ -1672,8 +1401,7 @@ export interface RedshiftDatasetDefinition { QueryString: string | undefined; /** - *The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate - * datasets.
+ *The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
* @public */ ClusterRoleArn: string | undefined; @@ -1685,8 +1413,7 @@ export interface RedshiftDatasetDefinition { OutputS3Uri: string | undefined; /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker - * uses to encrypt data from a Redshift execution.
+ *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
* @public */ KmsKeyId?: string | undefined; @@ -1705,9 +1432,7 @@ export interface RedshiftDatasetDefinition { } /** - *Configuration for Dataset Definition inputs. The Dataset Definition input must specify
- * exactly one of either AthenaDatasetDefinition or
- * RedshiftDatasetDefinition types.
Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a
- * processing job. LocalPath is an absolute path to the input data. This is a
- * required parameter when AppManaged is False (default).
The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
Whether the generated dataset is FullyReplicated or
- * ShardedByS3Key (default).
Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
Whether to use File or Pipe input mode. In File
- * (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic
- * Block Store (Amazon EBS) volumes before starting your training algorithm. This is the
- * most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from
- * the source directly to your algorithm without using the EBS volume.
Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
Configuration for downloading input data from Amazon S3 into the processing - * container.
+ *Configuration for downloading input data from Amazon S3 into the processing container.
* @public */ export interface ProcessingS3Input { /** - *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing - * job.
+ *The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
* @public */ S3Uri: string | undefined; /** - *The local path in your container where you want Amazon SageMaker to write input data to.
- * LocalPath is an absolute path to the input data and must begin with
- * /opt/ml/processing/. LocalPath is a required parameter
- * when AppManaged is False (default).
The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
Whether you use an S3Prefix or a ManifestFile for the data
- * type. If you choose S3Prefix, S3Uri identifies a key name
- * prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job.
- * If you choose ManifestFile, S3Uri identifies an object that is
- * a manifest file containing a list of object keys that you want Amazon SageMaker to use for the
- * processing job.
Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker
- * copies the data from the input source onto the local ML storage volume before starting
- * your processing container. This is the most commonly used input mode. In
- * Pipe mode, Amazon SageMaker streams input data from the source directly to your
- * processing container into named pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Whether to distribute the data from Amazon S3 to all processing instances with
- * FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key,
- * downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing
- * container. Gzip can only be used when Pipe mode is specified
- * as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from
- * the source directly to your container without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
The inputs for a processing job. The processing input must specify exactly one of
- * either S3Input or DatasetDefinition types.
The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.
When True, input operations such as data download are managed natively by
- * the processing job application. When False (default), input operations are
- * managed by Amazon SageMaker.
When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
Configuration for downloading input data from Amazon S3 into the processing - * container.
+ *Configuration for downloading input data from Amazon S3 into the processing container.
* @public */ S3Input?: ProcessingS3Input | undefined; @@ -1879,9 +1574,7 @@ export interface ProcessingInput { */ export interface ProcessingFeatureStoreOutput { /** - *The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. - * Note that your processing script is responsible for putting records into your Feature - * Store.
+ *The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
* @public */ FeatureGroupName: string | undefined; @@ -1893,32 +1586,26 @@ export interface ProcessingFeatureStoreOutput { */ export interface ProcessingS3Output { /** - *A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of - * a processing job.
+ *A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
* @public */ S3Uri: string | undefined; /** - *The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.
- * LocalPath is an absolute path to a directory containing output files.
- * This directory will be created by the platform and exist when your container's
- * entrypoint is invoked.
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.
Whether to upload the results of the processing job continuously or after the job - * completes.
+ *Whether to upload the results of the processing job continuously or after the job completes.
* @public */ S3UploadMode: ProcessingS3UploadMode | undefined; } /** - *Describes the results of a processing job. The processing output must specify exactly
- * one of either S3Output or FeatureStoreOutput types.
Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.
Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output
- * type is only supported when AppManaged is specified.
Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged is specified.
When True, output operations such as data upload are managed natively by
- * the processing job application. When False (default), output operations are
- * managed by Amazon SageMaker.
When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
An array of outputs configuring the data to upload from the processing - * container.
+ *An array of outputs configuring the data to upload from the processing container.
* @public */ Outputs: ProcessingOutput[] | undefined; /** - *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker
- * uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS
- * key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to
- * all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.
The number of ML compute instances to use in the processing job. For distributed - * processing jobs, specify a value greater than 1. The default value is 1.
+ *The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
* @public */ InstanceCount: number | undefined; @@ -1991,57 +1670,32 @@ export interface ProcessingClusterConfig { InstanceType: ProcessingInstanceType | undefined; /** - *The size of the ML storage volume in gigabytes that you want to provision. You must - * specify sufficient ML storage for your scenario.
- *Certain Nitro-based instances include local storage with a fixed total size,
- * dependent on the instance type. When using these instances for processing, Amazon SageMaker
- * mounts the local instance storage instead of Amazon EBS gp2 storage. You can't request a
- * VolumeSizeInGB greater than the total size of the local instance
- * storage.
For a list of instance types that support local instance storage, including the - * total size per instance type, see Instance Store Volumes.
- *The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can't request a VolumeSizeInGB greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker - * uses to encrypt data on the storage volume attached to the ML compute instance(s) that - * run the processing job.
- *Certain Nitro-based instances include local storage, dependent on the instance
- * type. Local storage volumes are encrypted using a hardware module on the instance.
- * You can't request a VolumeKmsKeyId when using an instance type with
- * local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
- *For more information about local instance storage encryption, see SSD - * Instance Store Volumes.
- *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
Identifies the resources, ML compute instances, and ML storage volumes to deploy for a - * processing job. In distributed training, you specify more than one instance.
+ *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
* @public */ export interface ProcessingResources { /** - *The configuration for the resources in a cluster used to run the processing - * job.
+ *The configuration for the resources in a cluster used to run the processing job.
* @public */ ClusterConfig: ProcessingClusterConfig | undefined; } /** - *Configures conditions under which the processing job should be stopped, such as how - * long the processing job has been running. After the condition is met, the processing job - * is stopped.
+ *Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
* @public */ export interface ProcessingStoppingCondition { @@ -2057,8 +1711,7 @@ export interface ProcessingStoppingCondition { */ export interface CreateProcessingJobRequest { /** - *An array of inputs configuring the data to download into the processing - * container.
+ *An array of inputs configuring the data to download into the processing container.
* @public */ ProcessingInputs?: ProcessingInput[] | undefined; @@ -2070,15 +1723,13 @@ export interface CreateProcessingJobRequest { ProcessingOutputConfig?: ProcessingOutputConfig | undefined; /** - *The name of the processing job. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ ProcessingJobName: string | undefined; /** - *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a - * processing job. In distributed training, you specify more than one instance.
+ *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
* @public */ ProcessingResources: ProcessingResources | undefined; @@ -2096,68 +1747,31 @@ export interface CreateProcessingJobRequest { AppSpecification: AppSpecification | undefined; /** - *The environment variables to set in the Docker container. Up to 100 key and values - * entries in the map are supported.
- *Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any environment fields. As part of the shared responsibility - * model, you are responsible for any potential exposure, unauthorized access, or compromise of - * your sensitive data if caused by security-sensitive information included in the - * request environment variable or plain text fields.
- *The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
Networking options for a processing job, such as whether to allow inbound and outbound - * network calls to and from processing containers, and the VPC subnets and security groups - * to use for VPC-enabled processing jobs.
+ *Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
* @public */ NetworkConfig?: NetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on - * your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; /** - *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and - * Cost Management User Guide.
- *Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any tags. As part of the shared responsibility - * model, you are responsible for any potential exposure, unauthorized access, or compromise of - * your sensitive data if caused by security-sensitive information included in the - * request tag variable or plain text fields.
- *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any tags. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request tag variable or plain text fields.
Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -2175,9 +1789,7 @@ export interface CreateProcessingJobResponse { } /** - *A key value pair used when you provision a project as a service catalog product. For - * information, see What is Amazon Web Services Service - * Catalog.
+ *A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
* @public */ export interface ProvisioningParameter { @@ -2195,9 +1807,7 @@ export interface ProvisioningParameter { } /** - *Details that you specify to provision a service catalog product. For information about - * service catalog, see What is Amazon Web Services Service - * Catalog.
+ *Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
* @public */ export interface ServiceCatalogProvisioningDetails { @@ -2243,17 +1853,13 @@ export interface CreateProjectInput { ProjectDescription?: string | undefined; /** - *The product ID and provisioning artifact ID to provision a service catalog. The provisioning - * artifact ID will default to the latest provisioning artifact ID of the product, if you don't - * provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service - * Catalog.
+ *The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
* @public */ ServiceCatalogProvisioningDetails?: ServiceCatalogProvisioningDetails | undefined; /** - *An array of key-value pairs that you want to use to organize and track your Amazon Web Services - * resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
+ *An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -2294,16 +1900,14 @@ export interface OwnershipSettings { */ export interface SpaceIdleSettings { /** - *The time that SageMaker waits after the application becomes idle before shutting it - * down.
+ *The time that SageMaker waits after the application becomes idle before shutting it down.
* @public */ IdleTimeoutInMinutes?: number | undefined; } /** - *Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio - * applications in a space.
+ *Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio applications in a space.
* @public */ export interface SpaceAppLifecycleManagement { @@ -2320,27 +1924,20 @@ export interface SpaceAppLifecycleManagement { */ export interface SpaceCodeEditorAppSettings { /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Settings that are used to configure and manage the lifecycle of CodeEditor applications in - * a space.
+ *Settings that are used to configure and manage the lifecycle of CodeEditor applications in a space.
* @public */ AppLifecycleManagement?: SpaceAppLifecycleManagement | undefined; } /** - *A file system, created by you in Amazon EFS, that you assign to a user profile or - * space for an Amazon SageMaker AI Domain. Permitted users can access this file system in - * Amazon SageMaker AI Studio.
+ *A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
* @public */ export interface EFSFileSystem { @@ -2364,8 +1961,7 @@ export interface FSxLustreFileSystem { } /** - *A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI - * Studio.
+ *A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
* @public */ export type CustomFileSystem = @@ -2425,11 +2021,7 @@ export namespace CustomFileSystem { */ export interface SpaceJupyterLabAppSettings { /** - *Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Settings that are used to configure and manage the lifecycle of JupyterLab applications in - * a space.
+ *Settings that are used to configure and manage the lifecycle of JupyterLab applications in a space.
* @public */ AppLifecycleManagement?: SpaceAppLifecycleManagement | undefined; @@ -2502,10 +2093,7 @@ export interface SpaceSettings { JupyterLabAppSettings?: SpaceJupyterLabAppSettings | undefined; /** - *The type of app created within the space.
- *If using the - * UpdateSpace API, you can't change the app type of your - * space by specifying a different value for this field.
+ *The type of app created within the space.
If using the UpdateSpace API, you can't change the app type of your space by specifying a different value for this field.
* @public */ AppType?: AppType | undefined; @@ -2517,23 +2105,13 @@ export interface SpaceSettings { SpaceStorageSettings?: SpaceStorageSettings | undefined; /** - *If you enable this option, SageMaker AI creates the following resources on your - * behalf when you create the space:
- *The user profile that possesses the space.
- *The app that the space contains.
- *If you enable this option, SageMaker AI creates the following resources on your behalf when you create the space:
The user profile that possesses the space.
The app that the space contains.
A file system, created by you, that you assign to a space for an Amazon SageMaker AI - * Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
+ *A file system, created by you, that you assign to a space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
* @public */ CustomFileSystems?: CustomFileSystem[] | undefined; @@ -2582,9 +2160,7 @@ export interface CreateSpaceRequest { SpaceName: string | undefined; /** - *Tags to associated with the space. Each tag consists of a key and an optional value. Tag
- * keys must be unique for each resource. Tags are searchable using the Search
- * API.
Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.
The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This - * content must be base64 encoded.
+ *The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This content must be base64 encoded.
* @public */ StudioLifecycleConfigContent: string | undefined; @@ -2666,9 +2241,7 @@ export interface CreateStudioLifecycleConfigRequest { StudioLifecycleConfigAppType: StudioLifecycleConfigAppType | undefined; /** - *Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an - * optional value. Tag keys must be unique per resource. Tags are searchable using the Search - * API.
+ *Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
* @public */ Tags?: Tag[] | undefined; @@ -2686,16 +2259,12 @@ export interface CreateStudioLifecycleConfigResponse { } /** - *Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and
- * storage paths. To learn more about
- * how to configure the DebugHookConfig parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Path to local storage location for metrics and tensors. Defaults to
- * /opt/ml/output/tensors/.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.
Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about
- * how to configure the CollectionConfiguration parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
- *
Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about
- * how to configure the DebugRuleConfiguration parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the rule configuration. It must be unique relative to other rule - * configuration names.
+ *The name of the rule configuration. It must be unique relative to other rule configuration names.
* @public */ RuleConfigurationName: string | undefined; /** - *Path to local storage location for output of rules. Defaults to
- * /opt/ml/processing/output/rule/.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network - * connectivity.
+ *Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network connectivity.
* @public */ export interface InfraCheckConfig { @@ -2788,8 +2349,7 @@ export interface InfraCheckConfig { } /** - *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and - * storage paths.
+ *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
* @public */ export interface ProfilerConfig { @@ -2800,19 +2360,13 @@ export interface ProfilerConfig { S3OutputPath?: string | undefined; /** - *A time interval for capturing system metrics in milliseconds. Available values are - * 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
+ *A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
* @public */ ProfilingIntervalInMilliseconds?: number | undefined; /** - *Configuration information for capturing framework metrics. Available key strings for different profiling options are
- * DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig.
- * The following codes are configuration structures for the ProfilingParameters parameter. To learn more about
- * how to configure the ProfilingParameters parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
- *
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging - * functionality of SageMaker, see Access a training container - * through Amazon Web Services Systems Manager (SSM) for remote - * debugging.
+ *Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
* @public */ export interface RemoteDebugConfig { @@ -2888,16 +2439,12 @@ export interface RemoteDebugConfig { } /** - *Contains information about attribute-based access control (ABAC) for a training job. - * The session chaining configuration uses Amazon Security Token Service (STS) for your training job to - * request temporary, limited-privilege credentials to tenants. For more information, see - * Attribute-based access control (ABAC) for multi-tenancy training.
+ *Contains information about attribute-based access control (ABAC) for a training job. The session chaining configuration uses Amazon Security Token Service (STS) for your training job to request temporary, limited-privilege credentials to tenants. For more information, see Attribute-based access control (ABAC) for multi-tenancy training.
* @public */ export interface SessionChainingConfig { /** - *Set to True to allow SageMaker to extract session tags from a training job
- * creation role and reuse these tags when assuming the training job execution role.
Set to True to allow SageMaker to extract session tags from a training job creation role and reuse these tags when assuming the training job execution role.
Path to local storage location for tensorBoard output. Defaults to
- * /opt/ml/output/tensorboard.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard.
The name of the training job. The name must be unique within an Amazon Web Services - * Region in an Amazon Web Services account.
+ *The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
* @public */ TrainingJobName: string | undefined; /** - *Algorithm-specific parameters that influence the quality of the model. You set - * hyperparameters before you start the learning process. For a list of hyperparameters for - * each training algorithm provided by SageMaker, see Algorithms.
- *You can specify a maximum of 100 hyperparameters. Each hyperparameter is a
- * key-value pair. Each key and value is limited to 256 characters, as specified by the
- * Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any hyperparameter fields. As part of the shared responsibility - * model, you are responsible for any potential exposure, unauthorized access, or compromise - * of your sensitive data if caused by any security-sensitive information included in the - * request hyperparameter variable or plain text fields.
- *Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request hyperparameter variable or plain text fields.
The registry path of the Docker image that contains the training algorithm and - * algorithm-specific metadata, including the input mode. For more information about - * algorithms provided by SageMaker, see Algorithms. For information about - * providing your own algorithms, see Using Your Own Algorithms with - * Amazon SageMaker.
+ *The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
* @public */ AlgorithmSpecification: AlgorithmSpecification | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform - * tasks on your behalf.
- *During model training, SageMaker needs your permission to read input data from an S3 - * bucket, download a Docker image that contains training code, write model artifacts to an - * S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant - * permissions for all of these tasks to an IAM role. For more information, see SageMaker - * Roles.
- *To be able to pass this role to SageMaker, the caller of this API must have the
- * iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
An array of Channel objects. Each channel is a named input source.
- * InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an
- * algorithm might have two channels of input data, training_data and
- * validation_data. The configuration for each channel provides the S3,
- * EFS, or FSx location where the input data is stored. It also provides information about
- * the stored data: the MIME type, compression method, and whether the data is wrapped in
- * RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input - * data files from an S3 bucket to a local directory in the Docker container, or makes it - * available as input streams. For example, if you specify an EFS location, input data - * files are available as input streams. They do not need to be downloaded.
- *Your input must be in the same Amazon Web Services region as your training - * job.
+ *An array of Channel objects. Each channel is a named input source. InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
* @public */ InputDataConfig?: Channel[] | undefined; /** - *Specifies the path to the S3 location where you want to store model artifacts. SageMaker - * creates subfolders for the artifacts.
+ *Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
* @public */ OutputDataConfig: OutputDataConfig | undefined; /** - *The resources, including the ML compute instances and ML storage volumes, to use - * for model training.
- *ML storage volumes store model artifacts and incremental states. Training
- * algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use
- * the ML storage volume to store the training data, choose File as the
- * TrainingInputMode in the algorithm specification. For distributed
- * training algorithms, specify an instance count greater than 1.
The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
A VpcConfig object that specifies the VPC that you want your training job to - * connect to. Control access to and from your training container by configuring the VPC. - * For more information, see Protect Training Jobs by Using an Amazon - * Virtual Private Cloud.
+ *A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Specifies a limit to how long a model training job can run. It also specifies how long - * a managed Spot training job has to complete. When the job reaches the time limit, SageMaker - * ends the training job. Use this API to cap model training costs.
- *To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays
- * job termination for 120 seconds. Algorithms can use this 120-second window to save the
- * model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
- *Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any tags. As part of the shared responsibility model, you are - * responsible for any potential exposure, unauthorized access, or compromise - * of your sensitive data if caused by any security-sensitive information included in the - * request tag variable or plain text fields.
- *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any tags. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request tag variable or plain text fields.
Isolates the training container. No inbound or outbound network calls can be made, - * except for calls between peers within a training cluster for distributed training. If - * you enable network isolation for training jobs that are configured to use a VPC, SageMaker - * downloads and uploads customer data and model artifacts through the specified VPC, but - * the training container does not have network access.
+ *Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
* @public */ EnableNetworkIsolation?: boolean | undefined; /** - *To encrypt all communications between ML compute instances in distributed training,
- * choose True. Encryption provides greater security for distributed training,
- * but training might take longer. How long it takes depends on the amount of communication
- * between compute instances, especially if you use a deep learning algorithm in
- * distributed training. For more information, see Protect Communications Between ML
- * Compute Instances in a Distributed Training Job.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True. Managed spot
- * training provides a fully managed and scalable infrastructure for training machine
- * learning models. this option is useful when training jobs can be interrupted and when
- * there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be - * used as a starting point to train models incrementally. Amazon SageMaker provides metrics and - * logs in CloudWatch. They can be used to see when managed spot training jobs are running, - * interrupted, resumed, or completed.
+ *To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
* @public */ EnableManagedSpotTraining?: boolean | undefined; /** - *Contains information about the output location for managed spot training checkpoint - * data.
+ *Contains information about the output location for managed spot training checkpoint data.
* @public */ CheckpointConfig?: CheckpointConfig | undefined; /** - *Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and
- * storage paths. To learn more about
- * how to configure the DebugHookConfig parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; /** - *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and - * storage paths.
+ *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
* @public */ ProfilerConfig?: ProfilerConfig | undefined; /** - *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework - * metrics.
+ *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
* @public */ ProfilerRuleConfigurations?: ProfilerRuleConfiguration[] | undefined; /** - *The environment variables to set in the Docker container.
- *Do not include any security-sensitive information including account access IDs, - * secrets, or tokens in any environment fields. As part of the shared responsibility model, - * you are responsible for any potential exposure, unauthorized access, or compromise of your - * sensitive data if caused by security-sensitive information included in the request environment variable - * or plain text fields.
- *The environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
The number of times to retry the job when the job fails due to an
- * InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
Configuration for remote debugging. To learn more about the remote debugging - * functionality of SageMaker, see Access a training container - * through Amazon Web Services Systems Manager (SSM) for remote - * debugging.
+ *Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
* @public */ RemoteDebugConfig?: RemoteDebugConfig | undefined; @@ -3186,8 +2617,7 @@ export interface CreateTrainingJobRequest { InfraCheckConfig?: InfraCheckConfig | undefined; /** - *Contains information about attribute-based access control (ABAC) for the training - * job.
+ *Contains information about attribute-based access control (ABAC) for the training job.
* @public */ SessionChainingConfig?: SessionChainingConfig | undefined; @@ -3215,8 +2645,7 @@ export interface CreateTrainingPlanRequest { TrainingPlanName: string | undefined; /** - *The unique identifier of the training plan offering to use for creating this - * plan.
+ *The unique identifier of the training plan offering to use for creating this plan.
* @public */ TrainingPlanOfferingId: string | undefined; @@ -3254,80 +2683,42 @@ export const JoinSource = { export type JoinSource = (typeof JoinSource)[keyof typeof JoinSource]; /** - *The data structure used to specify the data to be used for inference in a batch - * transform job and to associate the data that is relevant to the prediction results in - * the output. The input filter provided allows you to exclude input data that is not - * needed for inference in a batch transform job. The output filter provided allows you to - * include input data relevant to interpreting the predictions in the output from the job. - * For more information, see Associate Prediction - * Results with their Corresponding Input Records.
+ *The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
* @public */ export interface DataProcessing { /** - *A JSONPath expression used to select a portion of the input data to pass to
- * the algorithm. Use the InputFilter parameter to exclude fields, such as an
- * ID column, from the input. If you want SageMaker to pass the entire input dataset to the
- * algorithm, accept the default value $.
Examples: "$", "$[1:]", "$.features"
- *
A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $.
Examples: "$", "$[1:]", "$.features"
A JSONPath expression used to select a portion of the joined dataset to save
- * in the output file for a batch transform job. If you want SageMaker to store the entire input
- * dataset in the output file, leave the default value, $. If you specify
- * indexes that aren't within the dimension size of the joined dataset, you get an
- * error.
Examples: "$", "$[0,5:]",
- * "$['id','SageMakerOutput']"
- *
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error.
Examples: "$", "$[0,5:]", "$['id','SageMakerOutput']"
Specifies the source of the data to join with the transformed data. The valid values
- * are None and Input. The default value is None,
- * which specifies not to join the input with the transformed data. If you want the batch
- * transform job to join the original input data with the transformed data, set
- * JoinSource to Input. You can specify
- * OutputFilter as an additional filter to select a portion of the joined
- * dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to
- * the input JSON object in an attribute called SageMakerOutput. The joined
- * result for JSON must be a key-value pair object. If the input is not a key-value pair
- * object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored
- * under the SageMakerInput key and the results are stored in
- * SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with - * the input by appending each transformed row to the end of the input. The joined data has - * the original input data followed by the transformed data and the output is a CSV - * file.
- *For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
+ *Specifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource to Input. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput key and the results are stored in SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
* @public */ JoinSource?: JoinSource | undefined; } /** - *Configures the timeout and maximum number of retries for processing a transform job - * invocation.
+ *Configures the timeout and maximum number of retries for processing a transform job invocation.
* @public */ export interface ModelClientConfig { /** - *The timeout value in seconds for an invocation request. The default value is - * 600.
+ *The timeout value in seconds for an invocation request. The default value is 600.
* @public */ InvocationsTimeoutInSeconds?: number | undefined; /** - *The maximum number of retries when invocation requests are failing. The default value - * is 3.
+ *The maximum number of retries when invocation requests are failing. The default value is 3.
* @public */ InvocationsMaxRetries?: number | undefined; @@ -3338,88 +2729,49 @@ export interface ModelClientConfig { */ export interface CreateTransformJobRequest { /** - *The name of the transform job. The name must be unique within an Amazon Web Services Region in an - * Amazon Web Services account.
+ *The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
* @public */ TransformJobName: string | undefined; /** - *The name of the model that you want to use for the transform job.
- * ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services
- * Region in an Amazon Web Services account.
The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The maximum number of parallel requests that can be sent to each instance in a
- * transform job. If MaxConcurrentTransforms is set to 0 or left
- * unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your
- * chosen algorithm. If the execution-parameters endpoint is not enabled, the default value
- * is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to
- * set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.
Configures the timeout and maximum number of retries for processing a transform job - * invocation.
+ *Configures the timeout and maximum number of retries for processing a transform job invocation.
* @public */ ModelClientConfig?: ModelClientConfig | undefined; /** - *The maximum allowed size of the payload, in MB. A payload is the
- * data portion of a record (without metadata). The value in MaxPayloadInMB
- * must be greater than, or equal to, the size of a single record. To estimate the size of
- * a record in MB, divide the size of your dataset by the number of records. To ensure that
- * the records fit within the maximum payload size, we recommend using a slightly larger
- * value. The default value is 6 MB.
- *
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify
- * the MaxConcurrentTransforms parameter, the value of
- * (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100
- * MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP
- * chunked encoding, set the value to 0.
- * This
- * feature works only in supported algorithms. Currently, Amazon SageMaker built-in
- * algorithms do not support HTTP chunked encoding.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
Specifies the number of records to include in a mini-batch for an HTTP inference - * request. A record - * is a single unit of input data that - * inference can be made on. For example, a single line in a CSV file is a record.
- *To enable the batch strategy, you must set the SplitType property to
- * Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set
- * BatchStrategy to SingleRecord and SplitType
- * to Line.
To fit as many records in a mini-batch as can fit within the
- * MaxPayloadInMB limit, set BatchStrategy to
- * MultiRecord and SplitType to Line.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType property to Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.
The environment variables to set in the Docker container. Don't include any - * sensitive data in your environment variables. We support up to 16 key and - * values entries in the map.
+ *The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables. We support up to 16 key and values entries in the map.
* @public */ Environment?: RecordDescribes the input source and - * the - * way the transform job consumes it.
+ *Describes the input source and the way the transform job consumes it.
* @public */ TransformInput: TransformInput | undefined; @@ -3437,56 +2789,25 @@ export interface CreateTransformJobRequest { DataCaptureConfig?: BatchDataCaptureConfig | undefined; /** - *Describes the resources, including - * ML - * instance types and ML instance count, to use for the transform - * job.
+ *Describes the resources, including ML instance types and ML instance count, to use for the transform job.
* @public */ TransformResources: TransformResources | undefined; /** - *The data structure used to specify the data to be used for inference in a batch - * transform job and to associate the data that is relevant to the prediction results in - * the output. The input filter provided allows you to exclude input data that is not - * needed for inference in a batch transform job. The output filter provided allows you to - * include input data relevant to interpreting the predictions in the output from the job. - * For more information, see Associate Prediction - * Results with their Corresponding Input Records.
+ *The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
* @public */ DataProcessing?: DataProcessing | undefined; /** - *(Optional) - * An - * array of key-value pairs. For more information, see Using - * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User - * Guide.
+ *(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; /** - *Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -3508,15 +2829,13 @@ export interface CreateTransformJobResponse { */ export interface CreateTrialRequest { /** - *The name of the trial. The name must be unique in your Amazon Web Services account and is not - * case-sensitive.
+ *The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
* @public */ TrialName: string | undefined; /** - *The name of the trial as displayed. The name doesn't need to be unique. If
- * DisplayName isn't specified, TrialName is displayed.
The name of the trial as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialName is displayed.
A list of tags to associate with the trial. You can use Search API to - * search on the tags.
+ *A list of tags to associate with the trial. You can use Search API to search on the tags.
* @public */ Tags?: Tag[] | undefined; @@ -3553,20 +2871,12 @@ export interface CreateTrialResponse { } /** - *Represents an input or output artifact of a trial component. You specify
- * TrialComponentArtifact as part of the InputArtifacts and
- * OutputArtifacts parameters in the CreateTrialComponent
- * request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and - * instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
+ *Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
* @public */ export interface TrialComponentArtifact { /** - *The media type of the artifact, which indicates the type of data in the artifact file. The - * media type consists of a type and a subtype - * concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The - * type specifies the category of the media. The subtype specifies the kind of data.
+ *The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
* @public */ MediaType?: string | undefined; @@ -3579,9 +2889,7 @@ export interface TrialComponentArtifact { } /** - *The value of a hyperparameter. Only one of NumberValue or
- * StringValue can be specified.
This object is specified in the CreateTrialComponent request.
+ *The value of a hyperparameter. Only one of NumberValue or StringValue can be specified.
This object is specified in the CreateTrialComponent request.
* @public */ export type TrialComponentParameterValue = @@ -3594,8 +2902,7 @@ export type TrialComponentParameterValue = */ export namespace TrialComponentParameterValue { /** - *The string value of a categorical hyperparameter. If you specify a value for this
- * parameter, you can't specify the NumberValue parameter.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the NumberValue parameter.
The numeric value of a numeric hyperparameter. If you specify a value for this parameter,
- * you can't specify the StringValue parameter.
The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the StringValue parameter.
The name of the component. The name must be unique in your Amazon Web Services account and is not - * case-sensitive.
+ *The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
* @public */ TrialComponentName: string | undefined; /** - *The name of the component as displayed. The name doesn't need to be unique. If
- * DisplayName isn't specified, TrialComponentName is
- * displayed.
The name of the component as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
- *InProgress
- *Completed
- *Failed
- *The status of the component. States include:
InProgress
Completed
Failed
The input artifacts for the component. Examples of input artifacts are datasets, - * algorithms, hyperparameters, source code, and instance types.
+ *The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
* @public */ InputArtifacts?: RecordThe output artifacts for the component. Examples of output artifacts are metrics, - * snapshots, logs, and images.
+ *The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
* @public */ OutputArtifacts?: RecordA list of tags to associate with the component. You can use Search API - * to search on the tags.
+ *A list of tags to associate with the component. You can use Search API to search on the tags.
* @public */ Tags?: Tag[] | undefined; @@ -3783,27 +3072,19 @@ export interface CreateUserProfileRequest { UserProfileName: string | undefined; /** - *A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only - * supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is - * required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified. - *
+ *A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is "UserName". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
* @public */ SingleSignOnUserIdentifier?: string | undefined; /** - *The username of the associated Amazon Web Services Single Sign-On User for this - * UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must - * match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
+ *The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
* @public */ SingleSignOnUserValue?: string | undefined; /** - *Each tag consists of a key and an optional value. Tag keys must be unique per - * resource.
- *Tags that you specify for the User Profile are also added to all Apps that the User - * Profile launches.
+ *Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
* @public */ Tags?: Tag[] | undefined; @@ -3893,19 +3174,12 @@ export interface OidcConfig { } /** - *A list of IP address ranges (CIDRs). Used to create an allow - * list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an - * IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
+ *A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
* @public */ export interface SourceIpConfig { /** - *A list of one to ten Classless Inter-Domain Routing (CIDR) values.
- *Maximum: Ten CIDR values
- *The following Length Constraints apply to individual CIDR values in - * the CIDR value list.
- *A list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
Use this parameter to configure an Amazon Cognito private workforce. - * A single Cognito workforce is created using and corresponds to a single - * - * Amazon Cognito user pool.
- *Do not use OidcConfig if you specify values for
- * CognitoConfig.
Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig if you specify values for CognitoConfig.
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
- *Do not use CognitoConfig if you specify values for
- * OidcConfig.
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig if you specify values for OidcConfig.
A list of IP address ranges (CIDRs). Used to create an allow - * list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an - * IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
+ *A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
* @public */ SourceIpConfig?: SourceIpConfig | undefined; @@ -3973,9 +3238,7 @@ export interface CreateWorkforceRequest { WorkforceName: string | undefined; /** - *An array of key-value pairs that contain metadata to help you categorize and - * organize our workforce. Each tag consists of a key and a value, - * both of which you define.
+ *An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
* @public */ Tags?: Tag[] | undefined; @@ -3999,18 +3262,12 @@ export interface CreateWorkforceResponse { } /** - *A list of user groups that exist in your OIDC Identity Provider (IdP).
- * One to ten groups can be used to create a single private work team.
- * When you add a user group to the list of Groups, you can add that user group to one or more
- * private work teams. If you add a user group to a private work team, all workers in that user group
- * are added to the work team.
A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
A list of comma seperated strings that identifies - * user groups in your OIDC IdP. Each user group is - * made up of a group of private workers.
+ *A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
* @public */ Groups?: string[] | undefined; @@ -4028,19 +3285,14 @@ export interface MemberDefinition { CognitoMemberDefinition?: CognitoMemberDefinition | undefined; /** - *A list user groups that exist in your OIDC Identity Provider (IdP).
- * One to ten groups can be used to create a single private work team.
- * When you add a user group to the list of Groups, you can add that user group to one or more
- * private work teams. If you add a user group to a private work team, all workers in that user group
- * are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Configures Amazon SNS notifications of available or expiring work items for work - * teams.
+ *Configures Amazon SNS notifications of available or expiring work items for work teams.
* @public */ export interface NotificationConfiguration { @@ -4084,8 +3336,7 @@ export interface IamPolicyConstraints { } /** - *This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access.
To learn more about how custom templates are created, see Create custom worker task templates.
+ *This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access.
To learn more about how custom templates are created, see Create custom worker task templates.
* @public */ export interface S3Presign { @@ -4125,23 +3376,7 @@ export interface CreateWorkteamRequest { WorkforceName?: string | undefined; /** - *A list of MemberDefinition objects that contains objects that identify
- * the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For
- * private workforces created using Amazon Cognito use CognitoMemberDefinition. For
- * workforces created using your own OIDC identity provider (IdP) use
- * OidcMemberDefinition. Do not provide input for both of these parameters
- * in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito
- * user groups within the user pool used to create a workforce. All of the
- * CognitoMemberDefinition objects that make up the member definition must
- * have the same ClientId and UserPool values. To add a Amazon
- * Cognito user group to an existing worker pool, see Adding groups to a User
- * Pool. For more information about user pools, see Amazon Cognito User
- * Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to
- * include in your private work team in OidcMemberDefinition by listing those groups
- * in Groups.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.
An array of key-value pairs.
- *For more information, see Resource - * Tag and Using - * Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User - * Guide.
+ *An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; @@ -4180,8 +3411,7 @@ export interface CreateWorkteamRequest { */ export interface CreateWorkteamResponse { /** - *The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the - * work team.
+ *The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
* @public */ WorkteamArn?: string | undefined; @@ -4376,15 +3606,13 @@ export interface DeleteAppRequest { DomainId: string | undefined; /** - *The user profile name. If this value is not set, then SpaceName must be
- * set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be
- * set.
The name of the space. If this value is not set, then UserProfileName must be set.
The default is Retain, which specifies to keep the data stored on the
- * Amazon EFS volume.
Specify Delete to delete the data stored on the Amazon EFS
- * volume.
The default is Retain, which specifies to keep the data stored on the Amazon EFS volume.
Specify Delete to delete the data stored on the Amazon EFS volume.
The retention policy for this domain, which specifies whether resources will be retained - * after the Domain is deleted. By default, all resources are retained (not automatically - * deleted).
+ *The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
* @public */ RetentionPolicy?: RetentionPolicy | undefined; @@ -4710,8 +3933,7 @@ export interface DeleteExperimentResponse { */ export interface DeleteFeatureGroupRequest { /** - *The name of the FeatureGroup you want to delete. The name must be unique
- * within an Amazon Web Services Region in an Amazon Web Services account.
The name of the FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
A TrackingServerArn object, the ARN of the tracking server that is deleted if
- * successfully found.
A TrackingServerArn object, the ARN of the tracking server that is deleted if successfully found.
The name or Amazon Resource Name (ARN) of the model package to delete.
- *When you specify a name, the name must have 1 to 63 characters. Valid characters are - * a-z, A-Z, 0-9, and - (hyphen).
+ *The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
* @public */ ModelPackageName: string | undefined; @@ -5111,8 +4330,7 @@ export interface DeletePipelineRequest { PipelineName: string | undefined; /** - *A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than one time.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
* @public */ ClientRequestToken?: string | undefined; @@ -5173,8 +4391,7 @@ export interface DeleteStudioLifecycleConfigRequest { */ export interface DeleteTagsInput { /** - *The Amazon Resource Name (ARN) of the resource whose tags you want to - * delete.
+ *The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
* @public */ ResourceArn: string | undefined; @@ -5284,20 +4501,14 @@ export interface DeleteWorkteamRequest { */ export interface DeleteWorkteamResponse { /** - *Returns true if the work team was successfully deleted; otherwise,
- * returns false.
Returns true if the work team was successfully deleted; otherwise, returns false.
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
- *If you used the registry/repository[:tag] form to specify the image path
- * of the primary container when you created the model hosted in this
- * ProductionVariant, the path resolves to a path of the form
- * registry/repository[@digest]. A digest is a hash value that identifies
- * a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
The specific digest path of the image hosted in this
- * ProductionVariant.
The specific digest path of the image hosted in this ProductionVariant.
The date and time when the image path for the model resolved to the
- * ResolvedImage
- *
The date and time when the image path for the model resolved to the ResolvedImage
A set of recommended deployment configurations for the model. To get more advanced recommendations, see - * CreateInferenceRecommendationsJob - * to create an inference recommendation job.
+ *A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
* @public */ export interface DeploymentRecommendation { /** - *Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker
- * is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS,
- * retry your API call after a few seconds to get a COMPLETED deployment recommendation.
Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS, retry your API call after a few seconds to get a COMPLETED deployment recommendation.
The number of edge devices yet to pick up the deployment in current stage, or in - * progress.
+ *The number of edge devices yet to pick up the deployment in current stage, or in progress.
* @public */ EdgeDeploymentPendingInStage: number | undefined; @@ -5501,9 +4704,7 @@ export interface DeregisterDevicesRequest { */ export interface DerivedInformation { /** - *The data input configuration that SageMaker Neo automatically derived for the model. - * When SageMaker Neo derives this information, you don't need to specify the data input - * configuration when you create a compilation job.
+ *The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don't need to specify the data input configuration when you create a compilation job.
* @public */ DerivedDataInputConfig?: string | undefined; @@ -5573,8 +4774,7 @@ export interface DescribeActionResponse { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -5586,8 +4786,7 @@ export interface DescribeActionResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -5657,8 +4856,7 @@ export interface DescribeAlgorithmOutput { InferenceSpecification?: InferenceSpecification | undefined; /** - *Details about configurations for one or more training jobs that SageMaker runs to test the - * algorithm.
+ *Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
* @public */ ValidationSpecification?: AlgorithmValidationSpecification | undefined; @@ -5682,8 +4880,7 @@ export interface DescribeAlgorithmOutput { ProductId?: string | undefined; /** - *Whether the algorithm is certified to be listed in Amazon Web Services - * Marketplace.
+ *Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
* @public */ CertifyForMarketplace?: boolean | undefined; @@ -5700,8 +4897,7 @@ export interface DescribeAppRequest { DomainId: string | undefined; /** - *The user profile name. If this value is not set, then SpaceName must be
- * set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be
- * set.
The name of the space. If this value is not set, then UserProfileName must be set.
The timestamp of the last user's activity. LastUserActivityTimestamp is also
- * updated when SageMaker AI performs health checks without user activity. As a result, this
- * value is set to the same value as LastHealthCheckTimestamp.
The timestamp of the last user's activity. LastUserActivityTimestamp is also updated when SageMaker AI performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.
The creation time of the application.
- *After an application has been shut down for 24 hours, SageMaker AI deletes all - * metadata for the application. To be considered an update and retain application metadata, - * applications must be restarted within 24 hours after the previous application has been shut - * down. After this time window, creation of an application is considered a new application - * rather than an update of the previous application.
- *The creation time of the application.
After an application has been shut down for 24 hours, SageMaker AI deletes all metadata for the application. To be considered an update and retain application metadata, applications must be restarted within 24 hours after the previous application has been shut down. After this time window, creation of an application is considered a new application rather than an update of the previous application.
The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image - * created on the instance.
+ *The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
* @public */ ResourceSpec?: ResourceSpec | undefined; @@ -5935,8 +5120,7 @@ export interface DescribeArtifactResponse { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -5948,8 +5132,7 @@ export interface DescribeArtifactResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -5984,10 +5167,7 @@ export interface DescribeAutoMLJobRequest { */ export interface ModelDeployResult { /** - *The name of the endpoint to which the model has been deployed.
- *If model deployment fails, this field is omitted from the response.
- *The name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
How long a job is allowed to run, or how many candidates a job is allowed to - * generate.
+ *How long a job is allowed to run, or how many candidates a job is allowed to generate.
* @public */ CompletionCriteria?: AutoMLJobCompletionCriteria | undefined; @@ -6047,8 +5226,7 @@ export interface DescribeAutoMLJobResponse { OutputDataConfig: AutoMLOutputDataConfig | undefined; /** - *The ARN of the IAM role that has read permission to the input data - * location and write permission to the output data location in Amazon S3.
+ *The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
* @public */ RoleArn: string | undefined; @@ -6102,9 +5280,7 @@ export interface DescribeAutoMLJobResponse { PartialFailureReasons?: AutoMLPartialFailureReason[] | undefined; /** - *The best model candidate selected by SageMaker AI Autopilot using both the best - * objective metric and lowest InferenceLatency for - * an experiment.
+ *The best model candidate selected by SageMaker AI Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
* @public */ BestCandidate?: AutoMLCandidate | undefined; @@ -6122,30 +5298,25 @@ export interface DescribeAutoMLJobResponse { AutoMLJobSecondaryStatus: AutoMLJobSecondaryStatus | undefined; /** - *Indicates whether the output for an AutoML job generates candidate definitions - * only.
+ *Indicates whether the output for an AutoML job generates candidate definitions only.
* @public */ GenerateCandidateDefinitionsOnly?: boolean | undefined; /** - *Returns information on the job's artifacts found in
- * AutoMLJobArtifacts.
Returns information on the job's artifacts found in AutoMLJobArtifacts.
Contains ProblemType, AutoMLJobObjective, and
- * CompletionCriteria. If you do not provide these values, they are
- * inferred.
Contains ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are inferred.
Indicates whether the model was deployed automatically to an endpoint and the name of - * that endpoint if deployed automatically.
+ *Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
* @public */ ModelDeployConfig?: ModelDeployConfig | undefined; @@ -6197,8 +5368,7 @@ export interface DescribeAutoMLJobV2Response { OutputDataConfig: AutoMLOutputDataConfig | undefined; /** - *The ARN of the IAM role that has read permission to the input data - * location and write permission to the output data location in Amazon S3.
+ *The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
* @public */ RoleArn: string | undefined; @@ -6252,8 +5422,7 @@ export interface DescribeAutoMLJobV2Response { PartialFailureReasons?: AutoMLPartialFailureReason[] | undefined; /** - *Information about the candidate produced by an AutoML training job V2, including its - * status, steps, and other properties.
+ *Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
* @public */ BestCandidate?: AutoMLCandidate | undefined; @@ -6283,8 +5452,7 @@ export interface DescribeAutoMLJobV2Response { ResolvedAttributes?: AutoMLResolvedAttributes | undefined; /** - *Indicates whether the model was deployed automatically to an endpoint and the name of - * that endpoint if deployed automatically.
+ *Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
* @public */ ModelDeployConfig?: ModelDeployConfig | undefined; @@ -6296,15 +5464,13 @@ export interface DescribeAutoMLJobV2Response { ModelDeployResult?: ModelDeployResult | undefined; /** - *Returns the configuration settings of how the data are split into train and validation - * datasets.
+ *Returns the configuration settings of how the data are split into train and validation datasets.
* @public */ DataSplitConfig?: AutoMLDataSplitConfig | undefined; /** - *Returns the security configuration for traffic encryption or Amazon VPC - * settings.
+ *Returns the security configuration for traffic encryption or Amazon VPC settings.
* @public */ SecurityConfig?: AutoMLSecurityConfig | undefined; @@ -6368,10 +5534,7 @@ export interface DescribeClusterResponse { InstanceGroups: ClusterInstanceGroupDetails[] | undefined; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; @@ -6481,9 +5644,7 @@ export interface DescribeClusterSchedulerConfigResponse { ClusterArn?: string | undefined; /** - *Cluster policy configuration. This policy is used for task prioritization and fair-share - * allocation. This helps prioritize critical workloads and distributes idle compute - * across entities.
+ *Cluster policy configuration. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
* @public */ SchedulerConfig?: SchedulerConfig | undefined; @@ -6501,8 +5662,7 @@ export interface DescribeClusterSchedulerConfigResponse { CreationTime: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -6514,8 +5674,7 @@ export interface DescribeClusterSchedulerConfigResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -6561,9 +5720,7 @@ export interface DescribeCodeRepositoryOutput { LastModifiedTime: Date | undefined; /** - *Configuration details about the repository, including the URL where the repository is - * located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the - * repository.
+ *Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
* @public */ GitConfig?: GitConfig | undefined; @@ -6581,19 +5738,12 @@ export interface DescribeCompilationJobRequest { } /** - *Provides information about the location that is configured for storing model - * artifacts.
- *Model artifacts are outputs that result from training a model. They typically consist
- * of trained parameters, a model definition that describes how to compute inferences, and
- * other metadata. A SageMaker container stores your trained model artifacts in the
- * /opt/ml/model directory. After training has completed, by default,
- * these artifacts are uploaded to your Amazon S3 bucket as compressed files.
Provides information about the location that is configured for storing model artifacts.
Model artifacts are outputs that result from training a model. They typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata. A SageMaker container stores your trained model artifacts in the /opt/ml/model directory. After training has completed, by default, these artifacts are uploaded to your Amazon S3 bucket as compressed files.
The path of the S3 object that contains the model artifacts. For example,
- * s3://bucket-name/keynameprefix/model.tar.gz.
The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
Provides a hash value that uniquely identifies the stored model - * artifacts.
+ *Provides a hash value that uniquely identifies the stored model artifacts.
* @public */ ArtifactDigest?: string | undefined; @@ -6635,42 +5784,31 @@ export interface DescribeCompilationJobResponse { CompilationJobStatus: CompilationJobStatus | undefined; /** - *The time when the model compilation job started the CompilationJob
- * instances.
You are billed for the time between this timestamp and the timestamp in the
- * CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later
- * than this time. That's because it takes time to download the compilation job, which
- * depends on the size of the compilation job container.
The time when the model compilation job started the CompilationJob instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later than this time. That's because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a - * successful or stopped job, this is when the job's model artifacts have finished - * uploading. For a failed job, this is when Amazon SageMaker AI detected that the job failed.
+ *The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker AI detected that the job failed.
* @public */ CompilationEndTime?: Date | undefined; /** - *Specifies a limit to how long a model compilation job can run. When the job reaches - * the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training - * costs.
+ *Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
* @public */ StoppingCondition: StoppingCondition | undefined; /** - *The inference image to use when compiling a model. Specify an image only if the target - * device is a cloud instance.
+ *The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
* @public */ InferenceImage?: string | undefined; /** - *The Amazon Resource Name (ARN) of the versioned model package that was - * provided to SageMaker Neo when you initiated a compilation job.
+ *The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
* @public */ ModelPackageVersionArn?: string | undefined; @@ -6682,9 +5820,7 @@ export interface DescribeCompilationJobResponse { CreationTime: Date | undefined; /** - *The time that the status - * of - * the model compilation job was last modified.
+ *The time that the status of the model compilation job was last modified.
* @public */ LastModifiedTime: Date | undefined; @@ -6696,45 +5832,37 @@ export interface DescribeCompilationJobResponse { FailureReason: string | undefined; /** - *Information about the location in Amazon S3 that has been configured for storing the model - * artifacts used in the compilation job.
+ *Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
* @public */ ModelArtifacts: ModelArtifacts | undefined; /** - *Provides a BLAKE2 hash value that identifies the compiled model artifacts in - * Amazon S3.
+ *Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
* @public */ ModelDigests?: ModelDigests | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model - * compilation job.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model compilation job.
* @public */ RoleArn: string | undefined; /** - *Information about the location in Amazon S3 of the input model artifacts, the name and - * shape of the expected data inputs, and the framework in which the model was - * trained.
+ *Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
* @public */ InputConfig: InputConfig | undefined; /** - *Information about the output location for the compiled model and the target device - * that the model runs on.
+ *Information about the output location for the compiled model and the target device that the model runs on.
* @public */ OutputConfig: OutputConfig | undefined; /** - *A VpcConfig object that specifies the VPC that you want your compilation job - * to connect to. Control access to your models by configuring the VPC. For more - * information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
+ *A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: NeoVpcConfig | undefined; @@ -6816,8 +5944,7 @@ export interface DescribeComputeQuotaResponse { ClusterArn?: string | undefined; /** - *Configuration of the compute allocation definition. This includes the resource sharing - * option, and the setting to preempt low priority tasks.
+ *Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
* @public */ ComputeQuotaConfig?: ComputeQuotaConfig | undefined; @@ -6829,9 +5956,7 @@ export interface DescribeComputeQuotaResponse { ComputeQuotaTarget: ComputeQuotaTarget | undefined; /** - *The state of the compute allocation being described. Use to enable or disable compute - * allocation.
- *Default is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -6856,8 +5980,7 @@ export interface DescribeComputeQuotaResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -6921,8 +6044,7 @@ export interface DescribeContextResponse { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -6934,8 +6056,7 @@ export interface DescribeContextResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -6993,8 +6114,7 @@ export interface DescribeDataQualityJobDefinitionResponse { DataQualityAppSpecification: DataQualityAppSpecification | undefined; /** - *The list of inputs for the data quality monitoring job. Currently endpoints are - * supported.
+ *The list of inputs for the data quality monitoring job. Currently endpoints are supported.
* @public */ DataQualityJobInput: DataQualityJobInput | undefined; @@ -7018,8 +6138,7 @@ export interface DescribeDataQualityJobDefinitionResponse { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -7284,8 +6403,7 @@ export interface DescribeDomainResponse { SingleSignOnManagedApplicationInstanceId?: string | undefined; /** - *The ARN of the application managed by SageMaker AI in IAM Identity Center. This value - * is only returned for domains created after October 1, 2023.
+ *The ARN of the application managed by SageMaker AI in IAM Identity Center. This value is only returned for domains created after October 1, 2023.
* @public */ SingleSignOnApplicationArn?: string | undefined; @@ -7315,8 +6433,7 @@ export interface DescribeDomainResponse { FailureReason?: string | undefined; /** - *The ID of the security group that authorizes traffic between the
- * RSessionGateway apps and the RStudioServerPro app.
The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.
Settings which are applied to UserProfiles in this domain if settings are not explicitly - * specified in a given UserProfile.
+ *Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
* @public */ DefaultUserSettings?: UserSettings | undefined; @@ -7341,18 +6457,7 @@ export interface DescribeDomainResponse { DomainSettings?: DomainSettings | undefined; /** - *Specifies the VPC used for non-EFS traffic. The default value is
- * PublicInternetOnly.
- * PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
- * VpcOnly - All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
VpcOnly - All traffic is through the specified VPC and subnets
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to - * the domain.
+ *The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
* @public */ KmsKeyId?: string | undefined; /** - *The entity that creates and manages the required security groups for inter-app
- * communication in VPCOnly mode. Required when
- * CreateDomain.AppNetworkAccessType is VPCOnly and
- * DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is
- * provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
If the edge deployment plan has enough stages to require tokening, then this is the - * response from the last list of stages returned.
+ *If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
* @public */ NextToken?: string | undefined; @@ -7557,8 +6656,7 @@ export type EdgePresetDeploymentStatus = (typeof EdgePresetDeploymentStatus)[key */ export interface EdgePresetDeploymentOutput { /** - *The deployment type created by SageMaker Edge Manager. Currently only - * supports Amazon Web Services IoT Greengrass Version 2 components.
+ *The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
* @public */ Type: EdgePresetDeploymentType | undefined; @@ -7617,7 +6715,7 @@ export interface DescribeEdgePackagingJobResponse { ModelVersion?: string | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
+ *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
* @public */ RoleArn?: string | undefined; @@ -7732,34 +6830,7 @@ export type VariantStatus = (typeof VariantStatus)[keyof typeof VariantStatus]; */ export interface ProductionVariantStatus { /** - *The endpoint variant status which describes the current deployment stage status or - * operational status.
- *
- * Creating: Creating inference resources for the production
- * variant.
- * Deleting: Terminating inference resources for the production
- * variant.
- * Updating: Updating capacity for the production variant.
- * ActivatingTraffic: Turning on traffic for the production
- * variant.
- * Baking: Waiting period to monitor the CloudWatch alarms in the
- * automatic rollback configuration.
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
The production variant summary for a deployment when an endpoint is creating or
- * updating with the CreateEndpoint
- * or UpdateEndpoint
- * operations. Describes the VariantStatus , weight and capacity for a
- * production variant associated with an endpoint.
The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.
An array of DeployedImage objects that specify the Amazon EC2 Container
- * Registry paths of the inference images deployed on instances of this
- * ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The requested weight for the variant in this deployment, as specified in the endpoint - * configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
+ *The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
* @public */ DesiredWeight?: number | undefined; @@ -7820,8 +6884,7 @@ export interface PendingProductionVariantSummary { CurrentInstanceCount?: number | undefined; /** - *The number of instances requested in this deployment, as specified in the endpoint - * configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
+ *The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
* @public */ DesiredInstanceCount?: number | undefined; @@ -7833,17 +6896,13 @@ export interface PendingProductionVariantSummary { InstanceType?: ProductionVariantInstanceType | undefined; /** - *This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify the size of the EI instance to use for the - * production variant.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify the size of the EI instance to use for the production variant.
* @public */ AcceleratorType?: ProductionVariantAcceleratorType | undefined; /** - *The endpoint variant status which describes the current deployment stage status or - * operational status.
+ *The endpoint variant status which describes the current deployment stage status or operational status.
* @public */ VariantStatus?: ProductionVariantStatus[] | undefined; @@ -7861,23 +6920,20 @@ export interface PendingProductionVariantSummary { DesiredServerlessConfig?: ProductionVariantServerlessConfig | undefined; /** - *Settings that control the range in the number of instances that the endpoint provisions - * as it scales up or down to accommodate traffic.
+ *Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
* @public */ ManagedInstanceScaling?: ProductionVariantManagedInstanceScaling | undefined; /** - *Settings that control how the endpoint routes incoming traffic to the instances that the - * endpoint hosts.
+ *Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
* @public */ RoutingConfig?: ProductionVariantRoutingConfig | undefined; } /** - *The summary of an in-progress deployment when an endpoint is creating or updating with - * a new endpoint configuration.
+ *The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
* @public */ export interface PendingDeploymentSummary { @@ -7888,8 +6944,7 @@ export interface PendingDeploymentSummary { EndpointConfigName: string | undefined; /** - *An array of PendingProductionVariantSummary objects, one for each model hosted behind - * this endpoint for the in-progress deployment.
+ *An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
* @public */ ProductionVariants?: PendingProductionVariantSummary[] | undefined; @@ -7901,19 +6956,14 @@ export interface PendingDeploymentSummary { StartTime?: Date | undefined; /** - *An array of PendingProductionVariantSummary objects, one for each model hosted behind
- * this endpoint in shadow mode with production traffic replicated from the model specified
- * on ProductionVariants for the in-progress deployment.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants for the in-progress deployment.
Describes weight and capacities for a production variant associated with an
- * endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities
- * API and the endpoint status is Updating, you get different desired and
- * current values.
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the
- * inference images deployed on instances of this ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The requested weight, as specified in the
- * UpdateEndpointWeightsAndCapacities request.
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
The number of instances requested in the
- * UpdateEndpointWeightsAndCapacities request.
The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
The endpoint variant status which describes the current deployment stage status or - * operational status.
+ *The endpoint variant status which describes the current deployment stage status or operational status.
* @public */ VariantStatus?: ProductionVariantStatus[] | undefined; @@ -7976,15 +7022,13 @@ export interface ProductionVariantSummary { DesiredServerlessConfig?: ProductionVariantServerlessConfig | undefined; /** - *Settings that control the range in the number of instances that the endpoint provisions - * as it scales up or down to accommodate traffic.
+ *Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
* @public */ ManagedInstanceScaling?: ProductionVariantManagedInstanceScaling | undefined; /** - *Settings that control how the endpoint routes incoming traffic to the instances that the - * endpoint hosts.
+ *Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
* @public */ RoutingConfig?: ProductionVariantRoutingConfig | undefined; @@ -8013,8 +7057,7 @@ export interface DescribeEndpointOutput { EndpointConfigName?: string | undefined; /** - *An array of ProductionVariantSummary objects, one for each model hosted behind this - * endpoint.
+ *An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
* @public */ ProductionVariants?: ProductionVariantSummary[] | undefined; @@ -8026,69 +7069,13 @@ export interface DescribeEndpointOutput { DataCaptureConfig?: DataCaptureConfigSummary | undefined; /** - *The status of the endpoint.
- *
- * OutOfService: Endpoint is not available to take incoming
- * requests.
- * Creating: CreateEndpoint is executing.
- * Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
- * SystemUpdating: Endpoint is undergoing maintenance and cannot be
- * updated or deleted or re-scaled until it has completed. This maintenance
- * operation does not change any customer-specified values such as VPC config, KMS
- * encryption, model, instance type, or instance count.
- * RollingBack: Endpoint fails to scale up or down or change its
- * variant weight and is in the process of rolling back to its previous
- * configuration. Once the rollback completes, endpoint returns to an
- * InService status. This transitional status only applies to an
- * endpoint that has autoscaling enabled and is undergoing variant weight or
- * capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called
- * explicitly.
- * InService: Endpoint is available to process incoming
- * requests.
- * Deleting: DeleteEndpoint is executing.
- * Failed: Endpoint could not be created, updated, or re-scaled. Use
- * the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a
- * failed endpoint.
- * UpdateRollbackFailed: Both the rolling deployment and
- * auto-rollback failed. Your endpoint is in service with a mix of the old and new
- * endpoint configurations. For information about how to remedy this issue and
- * restore the endpoint's status to InService, see Rolling
- * Deployments.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint's status to InService, see Rolling Deployments.
If the status of the endpoint is Failed, the reason why it failed.
- *
If the status of the endpoint is Failed, the reason why it failed.
Returns the description of an endpoint configuration created using the
- * CreateEndpointConfig
- * API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Returns the summary of an in-progress deployment. This field is only returned when the - * endpoint is creating or updating with a new endpoint configuration.
+ *Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
* @public */ PendingDeploymentSummary?: PendingDeploymentSummary | undefined; @@ -8133,9 +7117,7 @@ export interface DescribeEndpointOutput { ExplainerConfig?: ExplainerConfig | undefined; /** - *An array of ProductionVariantSummary objects, one for each model that you want to host
- * at this endpoint in shadow mode with production traffic replicated from the model
- * specified on ProductionVariants.
An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
An array of ProductionVariant objects, one for each model that you
- * want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML - * storage volume attached to the instance.
+ *Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
* @public */ KmsKeyId?: string | undefined; @@ -8195,9 +7175,7 @@ export interface DescribeEndpointConfigOutput { CreationTime: Date | undefined; /** - *Returns the description of an endpoint configuration created using the
- * CreateEndpointConfig
- * API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
An array of ProductionVariant objects, one for each model that you want
- * to host at this endpoint in shadow mode with production traffic replicated from the
- * model specified on ProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
The Amazon Resource Name (ARN) of the IAM role that you assigned to the - * endpoint configuration.
+ *The Amazon Resource Name (ARN) of the IAM role that you assigned to the endpoint configuration.
* @public */ ExecutionRoleArn?: string | undefined; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Indicates whether all model containers deployed to the endpoint are isolated. If they - * are, no inbound or outbound network calls can be made to or from the model - * containers.
+ *Indicates whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
* @public */ EnableNetworkIsolation?: boolean | undefined; @@ -8287,8 +7257,7 @@ export interface DescribeExperimentResponse { ExperimentArn?: string | undefined; /** - *The name of the experiment as displayed. If DisplayName isn't specified,
- * ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want
- * described.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want described.
A token to resume pagination of the list of Features
- * (FeatureDefinitions). 2,500 Features are returned by
- * default.
A token to resume pagination of the list of Features (FeatureDefinitions). 2,500 Features are returned by default.
Active throughput configuration of the feature group. There are two modes:
- * ON_DEMAND and PROVISIONED. With on-demand mode, you are
- * charged for data reads and writes that your application performs on your feature group. You
- * do not need to specify read and write throughput because Feature Store accommodates your
- * workloads as they ramp up and down. You can switch a feature group to on-demand only once
- * in a 24 hour period. With provisioned throughput mode, you specify the read and write
- * capacity per second that you expect your application to require, and you are billed based
- * on those limits. Exceeding provisioned throughput will result in your requests being
- * throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that
- * are offline-only, or use the
- * Standard
- * tier online store.
Active throughput configuration of the feature group. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
The mode used for your feature group throughput: ON_DEMAND or
- * PROVISIONED.
The mode used for your feature group throughput: ON_DEMAND or PROVISIONED.
For provisioned feature groups with online store enabled, this indicates the read - * throughput you are billed for and can consume without throttling.
- *This field is not applicable for on-demand feature groups.
+ *For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
* @public */ ProvisionedReadCapacityUnits?: number | undefined; /** - *For provisioned feature groups, this indicates the write throughput you are billed for - * and can consume without throttling.
- *This field is not applicable for on-demand feature groups.
+ *For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
* @public */ ProvisionedWriteCapacityUnits?: number | undefined; @@ -8491,26 +7440,19 @@ export interface DescribeFeatureGroupResponse { FeatureGroupName: string | undefined; /** - *The name of the Feature used for RecordIdentifier, whose value
- * uniquely identifies a record stored in the feature store.
The name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime of a Record in a
- * FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds
- * to the creation or update of a Record in a FeatureGroup. All
- * Records in the FeatureGroup have a corresponding
- * EventTime.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup have a corresponding EventTime.
A list of the Features in the FeatureGroup. Each feature is
- * defined by a FeatureName and FeatureType.
A list of the Features in the FeatureGroup. Each feature is defined by a FeatureName and FeatureType.
The configuration of the offline store. It includes the following configurations:
- *Amazon S3 location of the offline store.
- *Configuration of the Glue data catalog.
- *Table format of the offline store.
- *Option to disable the automatic creation of a Glue table for the offline - * store.
- *Encryption configuration.
- *The configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
Active throughput configuration of the feature group. There are two modes:
- * ON_DEMAND and PROVISIONED. With on-demand mode, you are
- * charged for data reads and writes that your application performs on your feature group. You
- * do not need to specify read and write throughput because Feature Store accommodates your
- * workloads as they ramp up and down. You can switch a feature group to on-demand only once
- * in a 24 hour period. With provisioned throughput mode, you specify the read and write
- * capacity per second that you expect your application to require, and you are billed based
- * on those limits. Exceeding provisioned throughput will result in your requests being
- * throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that
- * are offline-only, or use the
- * Standard
- * tier online store.
Active throughput configuration of the feature group. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the - * OfflineStore if an OfflineStoreConfig is provided.
+ *The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
* @public */ RoleArn?: string | undefined; @@ -8589,10 +7500,7 @@ export interface DescribeFeatureGroupResponse { FeatureGroupStatus?: FeatureGroupStatus | undefined; /** - *The status of the OfflineStore. Notifies you if replicating data into the
- * OfflineStore has failed. Returns either: Active or
- * Blocked
- *
The status of the OfflineStore. Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked
The reason that the FeatureGroup failed to be replicated in the
- * OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the
- * OfflineStore.
The FeatureGroup could not be deleted from the
- * OfflineStore.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the OfflineStore.
The FeatureGroup could not be deleted from the OfflineStore.
A token to resume pagination of the list of Features
- * (FeatureDefinitions).
A token to resume pagination of the list of Features (FeatureDefinitions).
The name or Amazon Resource Name (ARN) of the feature group containing the - * feature.
+ *The name or Amazon Resource Name (ARN) of the feature group containing the feature.
* @public */ FeatureGroupName: string | undefined; @@ -8711,9 +7606,7 @@ export interface DescribeFeatureMetadataResponse { CreationTime: Date | undefined; /** - *A timestamp indicating when the metadata for the feature group was modified. For - * example, if you add a parameter describing the feature, the timestamp changes to reflect - * the last time you
+ *A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
* @public */ LastModifiedTime: Date | undefined; @@ -8787,8 +7680,7 @@ export interface DescribeFlowDefinitionResponse { CreationTime: Date | undefined; /** - *Container for configuring the source of human task requests. Used to specify if - * Amazon Rekognition or Amazon Textract is used as an integration source.
+ *Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
* @public */ HumanLoopRequestSource?: HumanLoopRequestSource | undefined; diff --git a/clients/client-sagemaker/src/models/models_3.ts b/clients/client-sagemaker/src/models/models_3.ts index 1042902829d9..5e8284c3a34c 100644 --- a/clients/client-sagemaker/src/models/models_3.ts +++ b/clients/client-sagemaker/src/models/models_3.ts @@ -469,8 +469,7 @@ export interface DescribeHubContentResponse { */ export interface DescribeHumanTaskUiRequest { /** - *The name of the human task user interface - * (worker task template) you want information about.
+ *The name of the human task user interface (worker task template) you want information about.
* @public */ HumanTaskUiName: string | undefined; @@ -555,24 +554,18 @@ export interface DescribeHyperParameterTuningJobRequest { } /** - *Shows the latest objective metric emitted by a training job that was launched by a
- * hyperparameter tuning job. You define the objective metric in the
- * HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
Select if you want to minimize or maximize the objective metric during hyperparameter - * tuning.
+ *Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
* @public */ Type?: HyperParameterTuningJobObjectiveType | undefined; /** - *The name of the objective metric. For SageMaker built-in algorithms, metrics are defined - * per algorithm. See the metrics for XGBoost as an - * example. You can also use a custom algorithm for training and define your own metrics. - * For more information, see Define metrics and environment variables.
+ *The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
* @public */ MetricName: string | undefined; @@ -643,75 +636,37 @@ export interface HyperParameterTrainingJobSummary { TrainingStartTime?: Date | undefined; /** - *Specifies the time when the training job ends on training instances. You are billed
- * for the time interval between the value of TrainingStartTime and this time.
- * For successful jobs and stopped jobs, this is the time after model artifacts are
- * uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The - * status - * of the training job.
+ *The status of the training job.
* @public */ TrainingJobStatus: TrainingJobStatus | undefined; /** - *A - * list of the hyperparameters for which you specified ranges to - * search.
+ *A list of the hyperparameters for which you specified ranges to search.
* @public */ TunedHyperParameters: RecordThe - * reason that the training job failed. - *
+ *The reason that the training job failed.
* @public */ FailureReason?: string | undefined; /** - *The FinalHyperParameterTuningJobObjectiveMetric object that specifies the - * value - * of the - * objective - * metric of the tuning job that launched this training job.
+ *The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
* @public */ FinalHyperParameterTuningJobObjectiveMetric?: FinalHyperParameterTuningJobObjectiveMetric | undefined; /** - *The status of the objective metric for the training job:
- *Succeeded: The - * final - * objective metric for the training job was evaluated by the - * hyperparameter tuning job and - * used - * in the hyperparameter tuning process.
- *Pending: The training job is in progress and evaluation of its final objective - * metric is pending.
- *Failed: - * The final objective metric for the training job was not evaluated, and was not - * used in the hyperparameter tuning process. This typically occurs when the - * training job failed or did not emit an objective - * metric.
- *The status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
Specifies the number of training jobs that this hyperparameter tuning job launched, - * categorized by the status of their objective metric. The objective metric status shows - * whether the - * final - * objective metric for the training job has been evaluated by the - * tuning job and used in the hyperparameter tuning process.
+ *Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
* @public */ export interface ObjectiveStatusCounters { /** - *The number of training jobs whose final objective metric was evaluated by the - * hyperparameter tuning job and used in the hyperparameter tuning process.
+ *The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
* @public */ Succeeded?: number | undefined; /** - *The number of training jobs that are in progress and pending evaluation of their final - * objective metric.
+ *The number of training jobs that are in progress and pending evaluation of their final objective metric.
* @public */ Pending?: number | undefined; /** - *The number of training jobs whose final objective metric was not evaluated and used in - * the hyperparameter tuning process. This typically occurs when the training job failed or - * did not emit an objective metric.
+ *The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
* @public */ Failed?: number | undefined; } /** - *The numbers of training jobs launched by a hyperparameter tuning job, categorized by - * status.
+ *The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
* @public */ export interface TrainingJobStatusCounters { /** - *The number of completed training jobs launched by the hyperparameter tuning - * job.
+ *The number of completed training jobs launched by the hyperparameter tuning job.
* @public */ Completed?: number | undefined; /** - *The number of in-progress training jobs launched by a hyperparameter tuning - * job.
+ *The number of in-progress training jobs launched by a hyperparameter tuning job.
* @public */ InProgress?: number | undefined; /** - *The number of training jobs that failed, but can be retried. A failed training job can - * be retried only if it failed because an internal service error occurred.
+ *The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
* @public */ RetryableError?: number | undefined; /** - *The number of training jobs that failed and can't be retried. A failed training job - * can't be retried if it failed because a client error occurred.
+ *The number of training jobs that failed and can't be retried. A failed training job can't be retried if it failed because a client error occurred.
* @public */ NonRetryableError?: number | undefined; /** - *The number of training jobs launched by a hyperparameter tuning job that were - * manually - * stopped.
+ *The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
* @public */ Stopped?: number | undefined; } /** - *A structure that contains runtime information about both current and completed - * hyperparameter tuning jobs.
+ *A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
* @public */ export interface HyperParameterTuningJobCompletionDetails { /** - *The number of training jobs launched by a tuning job that are not improving (1% or - * less) as measured by model performance evaluated against an objective function.
+ *The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
* @public */ NumberOfTrainingJobsObjectiveNotImproving?: number | undefined; /** - *The time in timestamp format that AMT detected model convergence, as defined by a lack - * of significant improvement over time based on criteria developed over a wide range of - * diverse benchmarking tests.
+ *The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
* @public */ ConvergenceDetectedTime?: Date | undefined; @@ -864,22 +799,19 @@ export interface DescribeHyperParameterTuningJobResponse { HyperParameterTuningJobArn: string | undefined; /** - *The HyperParameterTuningJobConfig object that specifies the configuration of - * the tuning job.
+ *The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
* @public */ HyperParameterTuningJobConfig: HyperParameterTuningJobConfig | undefined; /** - *The HyperParameterTrainingJobDefinition object that specifies the definition of - * the training jobs that this tuning job launches.
+ *The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
* @public */ TrainingJobDefinition?: HyperParameterTrainingJobDefinition | undefined; /** - *A list of the HyperParameterTrainingJobDefinition objects launched for this tuning - * job.
+ *A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
* @public */ TrainingJobDefinitions?: HyperParameterTrainingJobDefinition[] | undefined; @@ -909,42 +841,31 @@ export interface DescribeHyperParameterTuningJobResponse { LastModifiedTime?: Date | undefined; /** - *The TrainingJobStatusCounters object that specifies the number of training - * jobs, categorized by status, that this tuning job launched.
+ *The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
* @public */ TrainingJobStatusCounters: TrainingJobStatusCounters | undefined; /** - *The ObjectiveStatusCounters object that specifies the number of training jobs, - * categorized by the status of their final objective metric, that this tuning job - * launched.
+ *The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
* @public */ ObjectiveStatusCounters: ObjectiveStatusCounters | undefined; /** - *A TrainingJobSummary object that describes the training job that completed - * with the best current HyperParameterTuningJobObjective.
+ *A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
* @public */ BestTrainingJob?: HyperParameterTrainingJobSummary | undefined; /** - *If the hyperparameter tuning job is an warm start tuning job with a
- * WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the
- * TrainingJobSummary for the training job with the best objective metric
- * value of all training jobs launched by this tuning job and all parent jobs specified for
- * the warm start tuning job.
If the hyperparameter tuning job is an warm start tuning job with a WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or - * more previous tuning jobs as a starting point. The results of previous tuning jobs are - * used to inform which combinations of hyperparameters to search over in the new tuning - * job.
+ *The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
* @public */ WarmStartConfig?: HyperParameterTuningJobWarmStartConfig | undefined; @@ -962,10 +883,7 @@ export interface DescribeHyperParameterTuningJobResponse { FailureReason?: string | undefined; /** - *Tuning job completion information returned as the response from a hyperparameter - * tuning job. This information tells if your tuning job has or has not converged. It also - * includes the number of training jobs that have not improved model performance as - * evaluated against the objective function.
+ *Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
* @public */ TuningJobCompletionDetails?: HyperParameterTuningJobCompletionDetails | undefined; @@ -1165,45 +1083,13 @@ export interface DescribeImageVersionResponse { Version?: number | undefined; /** - *The stability of the image version specified by the maintainer.
- *
- * NOT_PROVIDED: The maintainers did not provide a status for image version stability.
- * STABLE: The image version is stable.
- * TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
- * ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
- *
- * TRAINING: The image version is compatible with SageMaker AI training jobs.
- * INFERENCE: The image version is compatible with SageMaker AI inference jobs.
- * NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
- *
- * CPU: The image version is compatible with CPU.
- * GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Specifies the type and size of the endpoint capacity to activate for a rolling - * deployment or a rollback strategy. You can specify your batches as either of the - * following:
- *A count of inference component copies
- *The overall percentage or your fleet
- *For a rollback strategy, if you don't specify the fields in this object, or if you set
- * the Value parameter to 100%, then SageMaker AI uses a blue/green rollback
- * strategy and rolls all traffic back to the blue fleet.
Specifies the type and size of the endpoint capacity to activate for a rolling deployment or a rollback strategy. You can specify your batches as either of the following:
A count of inference component copies
The overall percentage or your fleet
For a rollback strategy, if you don't specify the fields in this object, or if you set the Value parameter to 100%, then SageMaker AI uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
Specifies the endpoint capacity type.
- *The endpoint activates based on the number of inference component - * copies.
- *The endpoint activates based on the specified percentage of capacity.
- *Specifies the endpoint capacity type.
The endpoint activates based on the number of inference component copies.
The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of inference component copies or a - * capacity percentage.
+ *Defines the capacity size, either as a number of inference component copies or a capacity percentage.
* @public */ Value: number | undefined; } /** - *Specifies a rolling deployment strategy for updating a SageMaker AI inference - * component.
+ *Specifies a rolling deployment strategy for updating a SageMaker AI inference component.
* @public */ export interface InferenceComponentRollingUpdatePolicy { /** - *The batch size for each rolling step in the deployment process. For each step, SageMaker AI provisions capacity on the new endpoint fleet, routes traffic to that fleet, - * and terminates capacity on the old endpoint fleet. The value must be between 5% to 50% of - * the copy count of the inference component.
+ *The batch size for each rolling step in the deployment process. For each step, SageMaker AI provisions capacity on the new endpoint fleet, routes traffic to that fleet, and terminates capacity on the old endpoint fleet. The value must be between 5% to 50% of the copy count of the inference component.
* @public */ MaximumBatchSize: InferenceComponentCapacitySize | undefined; /** - *The length of the baking period, during which SageMaker AI monitors alarms for each - * batch on the new fleet.
+ *The length of the baking period, during which SageMaker AI monitors alarms for each batch on the new fleet.
* @public */ WaitIntervalInSeconds: number | undefined; @@ -1363,45 +1210,37 @@ export interface InferenceComponentRollingUpdatePolicy { MaximumExecutionTimeoutInSeconds?: number | undefined; /** - *The batch size for a rollback to the old endpoint fleet. If this field is absent, the - * value is set to the default, which is 100% of the total capacity. When the default is used, - * SageMaker AI provisions the entire capacity of the old fleet at once during - * rollback.
+ *The batch size for a rollback to the old endpoint fleet. If this field is absent, the value is set to the default, which is 100% of the total capacity. When the default is used, SageMaker AI provisions the entire capacity of the old fleet at once during rollback.
* @public */ RollbackMaximumBatchSize?: InferenceComponentCapacitySize | undefined; } /** - *The deployment configuration for an endpoint that hosts inference components. The - * configuration includes the desired deployment strategy and rollback settings.
+ *The deployment configuration for an endpoint that hosts inference components. The configuration includes the desired deployment strategy and rollback settings.
* @public */ export interface InferenceComponentDeploymentConfig { /** - *Specifies a rolling deployment strategy for updating a SageMaker AI - * endpoint.
+ *Specifies a rolling deployment strategy for updating a SageMaker AI endpoint.
* @public */ RollingUpdatePolicy: InferenceComponentRollingUpdatePolicy | undefined; /** - *Automatic rollback configuration for handling endpoint deployment failures and - * recovery.
+ *Automatic rollback configuration for handling endpoint deployment failures and recovery.
* @public */ AutoRollbackConfiguration?: AutoRollbackConfig | undefined; } /** - *Details about the runtime settings for the model that is deployed with the inference - * component.
+ *Details about the runtime settings for the model that is deployed with the inference component.
* @public */ export interface InferenceComponentRuntimeConfigSummary { /** - *The number of runtime copies of the model container that you requested to deploy with - * the inference component.
+ *The number of runtime copies of the model container that you requested to deploy with the inference component.
* @public */ DesiredCopyCount?: number | undefined; @@ -1419,12 +1258,7 @@ export interface InferenceComponentRuntimeConfigSummary { */ export interface InferenceComponentContainerSpecificationSummary { /** - *Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
- *If you used the registry/repository[:tag] form to specify the image path
- * of the primary container when you created the model hosted in this
- * ProductionVariant, the path resolves to a path of the form
- * registry/repository[@digest]. A digest is a hash value that identifies
- * a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
The name of the SageMaker AI model object that is deployed with the inference - * component.
+ *The name of the SageMaker AI model object that is deployed with the inference component.
* @public */ ModelName?: string | undefined; /** - *Details about the container that provides the runtime environment for the model that is - * deployed with the inference component.
+ *Details about the container that provides the runtime environment for the model that is deployed with the inference component.
* @public */ Container?: InferenceComponentContainerSpecificationSummary | undefined; @@ -1468,8 +1300,7 @@ export interface InferenceComponentSpecificationSummary { StartupParameters?: InferenceComponentStartupParameters | undefined; /** - *The compute resources allocated to run the model, plus any - * adapter models, that you assign to the inference component.
+ *The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.
* @public */ ComputeResourceRequirements?: InferenceComponentComputeResourceRequirements | undefined; @@ -1516,8 +1347,7 @@ export interface DescribeInferenceComponentOutput { VariantName?: string | undefined; /** - *If the inference component status is Failed, the reason for the
- * failure.
If the inference component status is Failed, the reason for the failure.
Details about the runtime settings for the model that is deployed with the inference - * component.
+ *Details about the runtime settings for the model that is deployed with the inference component.
* @public */ RuntimeConfig?: InferenceComponentRuntimeConfigSummary | undefined; @@ -1554,8 +1383,7 @@ export interface DescribeInferenceComponentOutput { InferenceComponentStatus?: InferenceComponentStatus | undefined; /** - *The deployment and rollback settings that you assigned to the inference - * component.
+ *The deployment and rollback settings that you assigned to the inference component.
* @public */ LastDeploymentConfig?: InferenceComponentDeploymentConfig | undefined; @@ -1590,18 +1418,13 @@ export interface EndpointMetadata { EndpointConfigName?: string | undefined; /** - *- * The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary. - *
+ *The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
* @public */ EndpointStatus?: EndpointStatus | undefined; /** - *
- * If the status of the endpoint is Failed, or the status is InService but update
- * operation fails, this provides the reason why it failed.
- *
If the status of the endpoint is Failed, or the status is InService but update operation fails, this provides the reason why it failed.
The status of deployment for the model variant on the hosted inference endpoint.
- *
- * Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
- *
- * InService - The model variant is running on the hosted inference endpoint.
- *
- * Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.
- *
- * Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
- *
- * Deleted - The model variant has been deleted on the hosted inference endpoint. This
- * can only happen after stopping the experiment.
- *
The status of deployment for the model variant on the hosted inference endpoint.
Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService - The model variant is running on the hosted inference endpoint.
Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
- * The status of the inference experiment. The following are the possible statuses for an inference - * experiment: - *
- *
- * Creating - Amazon SageMaker is creating your experiment.
- *
- * Created - Amazon SageMaker has finished the creation of your experiment and will begin the
- * experiment at the scheduled time.
- *
- * Updating - When you make changes to your experiment, your experiment shows as updating.
- *
- * Starting - Amazon SageMaker is beginning your experiment.
- *
- * Running - Your experiment is in progress.
- *
- * Stopping - Amazon SageMaker is stopping your experiment.
- *
- * Completed - Your experiment has completed.
- *
- * Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows
- * as cancelled.
- *
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating - Amazon SageMaker is creating your experiment.
Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating - When you make changes to your experiment, your experiment shows as updating.
Starting - Amazon SageMaker is beginning your experiment.
Running - Your experiment is in progress.
Stopping - Amazon SageMaker is stopping your experiment.
Completed - Your experiment has completed.
Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
- * The error message or client-specified Reason from the StopInferenceExperiment
- * API, that explains the status of the inference experiment.
- *
The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.
- * The timestamp at which the inference experiment was completed. - *
+ *The timestamp at which the inference experiment was completed.
* @public */ CompletionTime?: Date | undefined; @@ -1819,10 +1562,7 @@ export interface DescribeInferenceExperimentResponse { LastModifiedTime?: Date | undefined; /** - *- * The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage - * Amazon SageMaker Inference endpoints for model deployment. - *
+ *The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
* @public */ RoleArn?: string | undefined; @@ -1834,11 +1574,7 @@ export interface DescribeInferenceExperimentResponse { EndpointMetadata: EndpointMetadata | undefined; /** - *
- * An array of ModelVariantConfigSummary objects. There is one for each variant in the inference
- * experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure
- * configuration for deploying the corresponding variant.
- *
An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.
- * The configuration of ShadowMode inference experiment type, which shows the production variant
- * that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the
- * inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
- *
The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
- * The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on - * the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see - * CreateInferenceExperiment. - *
+ *The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
* @public */ KmsKey?: string | undefined; @@ -1875,8 +1603,7 @@ export interface DescribeInferenceExperimentResponse { */ export interface DescribeInferenceRecommendationsJobRequest { /** - *The name of the job. The name must be unique within an - * Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobName: string | undefined; @@ -1984,27 +1711,19 @@ export interface RecommendationMetrics { ModelLatency?: number | undefined; /** - *The expected CPU utilization at maximum invocations per minute for the instance.
- *
- * NaN indicates that the value is not available.
The expected CPU utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
- *
- * NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The time it takes to launch new compute resources for a serverless endpoint. - * The time can vary depending on the model size, how long it takes to download the - * model, and the start-up time of the container.
- *
- * NaN indicates that the value is not available.
The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN indicates that the value is not available.
The name of the job. The name must be unique within an - * Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobName: string | undefined; @@ -2150,8 +1868,7 @@ export interface DescribeInferenceRecommendationsJobResponse { JobArn: string | undefined; /** - *The Amazon Resource Name (ARN) of the Amazon Web Services - * Identity and Access Management (IAM) role you provided when you initiated the job.
+ *The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
* @public */ RoleArn: string | undefined; @@ -2187,8 +1904,7 @@ export interface DescribeInferenceRecommendationsJobResponse { FailureReason?: string | undefined; /** - *Returns information about the versioned model package Amazon Resource Name (ARN), - * the traffic pattern, and endpoint configurations you provided when you initiated the job.
+ *Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
* @public */ InputConfig: RecommendationJobInputConfig | undefined; @@ -2271,8 +1987,7 @@ export interface LabelingJobOutput { OutputDatasetS3Uri: string | undefined; /** - *The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of - * automated data labeling.
+ *The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
* @public */ FinalActiveLearningModelArn?: string | undefined; @@ -2307,9 +2022,7 @@ export interface DescribeLabelingJobResponse { LabelingJobStatus: LabelingJobStatus | undefined; /** - *Provides a breakdown of the number of data objects labeled by humans, the number of - * objects labeled by machine, the number of objects than couldn't be labeled, and the - * total number of objects labeled.
+ *Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.
* @public */ LabelCounters: LabelCounters | undefined; @@ -2357,91 +2070,31 @@ export interface DescribeLabelingJobResponse { LabelAttributeName?: string | undefined; /** - *Input configuration information for the labeling job, such as the Amazon S3 location of the - * data objects and the location of the manifest file that describes the data - * objects.
+ *Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
* @public */ InputConfig: LabelingJobInputConfig | undefined; /** - *The location of the job's output data and the Amazon Web Services Key Management - * Service key ID for the key used to encrypt the output data, if any.
+ *The location of the job's output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
* @public */ OutputConfig: LabelingJobOutputConfig | undefined; /** - *The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf - * during data labeling.
+ *The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
* @public */ RoleArn: string | undefined; /** - *The S3 location of the JSON file that defines the categories used to label data - * objects. Please note the following label-category limits:
- *Semantic segmentation labeling jobs using automated labeling: 20 labels
- *Box bounding labeling jobs (all): 10 labels
- *The file is a JSON structure in the following format:
- *
- * \{
- *
- * "document-version": "2018-11-28"
- *
- * "labels": [
- *
- * \{
- *
- * "label": "label 1"
- *
- * \},
- *
- * \{
- *
- * "label": "label 2"
- *
- * \},
- *
- * ...
- *
- * \{
- *
- * "label": "label n"
- *
- * \}
- *
- * ]
- *
- * \}
- *
The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
\{
"document-version": "2018-11-28"
"labels": [
\{
"label": "label 1"
\},
\{
"label": "label 2"
\},
...
\{
"label": "label n"
\}
]
\}
A set of conditions for stopping a labeling job. If any of the conditions are met, the - * job is automatically stopped.
+ *A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
* @public */ StoppingConditions?: LabelingJobStoppingConditions | undefined; @@ -2453,16 +2106,13 @@ export interface DescribeLabelingJobResponse { LabelingJobAlgorithmsConfig?: LabelingJobAlgorithmsConfig | undefined; /** - *Configuration information required for human workers to complete a labeling - * task.
+ *Configuration information required for human workers to complete a labeling task.
* @public */ HumanTaskConfig: HumanTaskConfig | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -2520,8 +2170,7 @@ export interface DescribeLineageGroupResponse { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -2533,8 +2182,7 @@ export interface DescribeLineageGroupResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -2611,8 +2259,7 @@ export interface DescribeMlflowTrackingServerResponse { TrackingServerName?: string | undefined; /** - *The S3 URI of the general purpose bucket used as the MLflow Tracking Server - * artifact store.
+ *The S3 URI of the general purpose bucket used as the MLflow Tracking Server artifact store.
* @public */ ArtifactStoreUri?: string | undefined; @@ -2630,8 +2277,7 @@ export interface DescribeMlflowTrackingServerResponse { MlflowVersion?: string | undefined; /** - *The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server - * uses to access the artifact store in Amazon S3.
+ *The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server uses to access the artifact store in Amazon S3.
* @public */ RoleArn?: string | undefined; @@ -2673,8 +2319,7 @@ export interface DescribeMlflowTrackingServerResponse { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -2686,8 +2331,7 @@ export interface DescribeMlflowTrackingServerResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -2715,9 +2359,7 @@ export interface DescribeModelOutput { ModelName: string | undefined; /** - *The location of the primary inference code, associated artifacts, and custom - * environment map that the inference code uses when it is deployed in production. - *
+ *The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
* @public */ PrimaryContainer?: ContainerDefinition | undefined; @@ -2735,17 +2377,13 @@ export interface DescribeModelOutput { InferenceExecutionConfig?: InferenceExecutionConfig | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that you specified for the - * model.
+ *The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
* @public */ ExecutionRoleArn?: string | undefined; /** - *A VpcConfig object that specifies the VPC that this model has access to. For - * more information, see Protect Endpoints by Using an Amazon Virtual - * Private Cloud - *
+ *A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
* @public */ VpcConfig?: VpcConfig | undefined; @@ -2763,8 +2401,7 @@ export interface DescribeModelOutput { ModelArn: string | undefined; /** - *If True, no inbound or outbound network calls can be made to or from the
- * model container.
If True, no inbound or outbound network calls can be made to or from the model container.
The name of the bias job definition. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobDefinitionName: string | undefined; @@ -2847,8 +2483,7 @@ export interface DescribeModelBiasJobDefinitionResponse { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that has read permission to the - * input data location and write permission to the output data location in Amazon S3.
+ *The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
* @public */ RoleArn: string | undefined; @@ -2924,26 +2559,7 @@ export interface DescribeModelCardResponse { Content: string | undefined; /** - *The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy: UserContext | undefined; @@ -2974,40 +2589,13 @@ export interface DescribeModelCardResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; /** - *The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
- * DeletePending: Model card deletion request received.
- * DeleteInProgress: Model card deletion is in progress.
- * ContentDeleted: Deleted model card content.
- * ExportJobsDeleted: Deleted all export jobs associated with the model card.
- * DeleteCompleted: Successfully deleted the model card.
- * DeleteFailed: The model card failed to delete.
The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
DeletePending: Model card deletion request received.
DeleteInProgress: Model card deletion is in progress.
ContentDeleted: Deleted model card content.
ExportJobsDeleted: Deleted all export jobs associated with the model card.
DeleteCompleted: Successfully deleted the model card.
DeleteFailed: The model card failed to delete.
The completion status of the model card export job.
- *
- * InProgress: The model card export job is in progress.
- * Completed: The model card export job is complete.
- * Failed: The model card export job failed. To see the reason for the failure, see
- * the FailureReason field in the response to a
- * DescribeModelCardExportJob call.
The completion status of the model card export job.
InProgress: The model card export job is in progress.
Completed: The model card export job is complete.
Failed: The model card export job failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeModelCardExportJob call.
The name of the model explainability job definition. The name must be unique within an - * Amazon Web Services Region in the Amazon Web Services account.
+ *The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobDefinitionName: string | undefined; @@ -3203,8 +2774,7 @@ export interface DescribeModelExplainabilityJobDefinitionResponse { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that has read permission to the - * input data location and write permission to the output data location in Amazon S3.
+ *The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
* @public */ RoleArn: string | undefined; @@ -3221,9 +2791,7 @@ export interface DescribeModelExplainabilityJobDefinitionResponse { */ export interface DescribeModelPackageInput { /** - *The name or Amazon Resource Name (ARN) of the model package to describe.
- *When you specify a name, the name must have 1 to 63 characters. Valid characters are - * a-z, A-Z, 0-9, and - (hyphen).
+ *The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
* @public */ ModelPackageName: string | undefined; @@ -3298,8 +2866,7 @@ export interface DescribeModelPackageOutput { ModelPackageName: string | undefined; /** - *If the model is a versioned model, the name of the model group that the versioned - * model belongs to.
+ *If the model is a versioned model, the name of the model group that the versioned model belongs to.
* @public */ ModelPackageGroupName?: string | undefined; @@ -3329,8 +2896,7 @@ export interface DescribeModelPackageOutput { CreationTime: Date | undefined; /** - *Details about inference jobs that you can run with models based on this model - * package.
+ *Details about inference jobs that you can run with models based on this model package.
* @public */ InferenceSpecification?: InferenceSpecification | undefined; @@ -3342,8 +2908,7 @@ export interface DescribeModelPackageOutput { SourceAlgorithmSpecification?: SourceAlgorithmSpecification | undefined; /** - *Configurations for one or more transform jobs that SageMaker runs to test the model - * package.
+ *Configurations for one or more transform jobs that SageMaker runs to test the model package.
* @public */ ValidationSpecification?: ModelPackageValidationSpecification | undefined; @@ -3361,8 +2926,7 @@ export interface DescribeModelPackageOutput { ModelPackageStatusDetails: ModelPackageStatusDetails | undefined; /** - *Whether the model package is certified for listing on Amazon Web Services - * Marketplace.
+ *Whether the model package is certified for listing on Amazon Web Services Marketplace.
* @public */ CertifyForMarketplace?: boolean | undefined; @@ -3374,8 +2938,7 @@ export interface DescribeModelPackageOutput { ModelApprovalStatus?: ModelApprovalStatus | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -3399,8 +2962,7 @@ export interface DescribeModelPackageOutput { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -3412,22 +2974,19 @@ export interface DescribeModelPackageOutput { ApprovalDescription?: string | undefined; /** - *The machine learning domain of the model package you specified. Common machine - * learning domains include computer vision and natural language processing.
+ *The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
* @public */ Domain?: string | undefined; /** - *The machine learning task you specified that your model package accomplishes. Common - * machine learning tasks include object detection and image classification.
+ *The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
* @public */ Task?: string | undefined; /** - *The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a - * single gzip compressed tar archive (.tar.gz suffix).
+ *The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
* @public */ SamplePayloadUrl?: string | undefined; @@ -3439,18 +2998,13 @@ export interface DescribeModelPackageOutput { CustomerMetadataProperties?: RecordRepresents the drift check baselines that can be used when the model monitor is set - * using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker - * Pipelines in the Amazon SageMaker Developer Guide.
+ *Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
* @public */ DriftCheckBaselines?: DriftCheckBaselines | undefined; /** - *An array of additional Inference Specification objects. Each additional Inference - * Specification specifies artifacts based on this model package that can be used on - * inference endpoints. Generally used with SageMaker Neo to store the compiled - * artifacts.
+ *An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
* @public */ AdditionalInferenceSpecifications?: AdditionalInferenceSpecificationDefinition[] | undefined; @@ -3468,23 +3022,13 @@ export interface DescribeModelPackageOutput { SourceUri?: string | undefined; /** - *The KMS Key ID (KMSKeyId) used for encryption of model
- * package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
The model card associated with the model package. Since
- * ModelPackageModelCard is tied to a model package, it is a specific
- * usage of a model card and its schema is simplified compared to the schema of
- * ModelCard. The ModelPackageModelCard schema does not
- * include model_package_details, and model_overview is composed
- * of the model_creator and model_artifact properties. For more
- * information about the model package model card schema, see Model
- * package model card schema. For more information about the model card
- * associated with the model package, see View the Details of a Model
- * Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy: UserContext | undefined; @@ -3572,8 +3115,7 @@ export interface DescribeModelPackageGroupOutput { */ export interface DescribeModelQualityJobDefinitionRequest { /** - *The name of the model quality job. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ JobDefinitionName: string | undefined; @@ -3638,8 +3180,7 @@ export interface DescribeModelQualityJobDefinitionResponse { NetworkConfig?: MonitoringNetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can - * assume to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -3786,36 +3327,13 @@ export interface DescribeMonitoringScheduleResponse { MonitoringScheduleStatus: ScheduleStatus | undefined; /** - *The type of the monitoring job that this schedule runs. This is one of the following - * values.
- *
- * DATA_QUALITY - The schedule is for a data quality monitoring
- * job.
- * MODEL_QUALITY - The schedule is for a model quality monitoring
- * job.
- * MODEL_BIAS - The schedule is for a bias monitoring job.
- * MODEL_EXPLAINABILITY - The schedule is for an explainability
- * monitoring job.
The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY - The schedule is for a data quality monitoring job.
MODEL_QUALITY - The schedule is for a model quality monitoring job.
MODEL_BIAS - The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job.
A string, up to one KB in size, that contains the reason a monitoring job failed, if it - * failed.
+ *A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
* @public */ FailureReason?: string | undefined; @@ -3833,8 +3351,7 @@ export interface DescribeMonitoringScheduleResponse { LastModifiedTime: Date | undefined; /** - *The configuration object that specifies the monitoring schedule and defines the monitoring - * job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring job.
* @public */ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; @@ -3911,8 +3428,7 @@ export interface DescribeNotebookInstanceOutput { FailureReason?: string | undefined; /** - *The URL that you use to connect to the Jupyter notebook that is running in your - * notebook instance.
+ *The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
* @public */ Url?: string | undefined; @@ -3936,55 +3452,43 @@ export interface DescribeNotebookInstanceOutput { SecurityGroups?: string[] | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role associated with the instance. - *
+ *The Amazon Resource Name (ARN) of the IAM role associated with the instance.
* @public */ RoleArn?: string | undefined; /** - *The Amazon Web Services KMS key ID SageMaker AI uses to encrypt data when - * storing it on the ML storage volume attached to the instance.
+ *The Amazon Web Services KMS key ID SageMaker AI uses to encrypt data when storing it on the ML storage volume attached to the instance.
* @public */ KmsKeyId?: string | undefined; /** - *The network interface IDs that SageMaker AI created at the time of creating - * the instance.
+ *The network interface IDs that SageMaker AI created at the time of creating the instance.
* @public */ NetworkInterfaceId?: string | undefined; /** - *A timestamp. Use this parameter to retrieve the time when the notebook instance was - * last modified.
+ *A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
* @public */ LastModifiedTime?: Date | undefined; /** - *A timestamp. Use this parameter to return the time when the notebook instance was - * created
+ *A timestamp. Use this parameter to return the time when the notebook instance was created
* @public */ CreationTime?: Date | undefined; /** - *Returns the name of a notebook instance lifecycle configuration.
- *For information about notebook instance lifestyle configurations, see Step - * 2.1: (Optional) Customize a Notebook Instance - *
+ *Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
* @public */ NotebookInstanceLifecycleConfigName?: string | undefined; /** - *Describes whether SageMaker AI provides internet access to the notebook instance. - * If this value is set to Disabled, the notebook instance does not - * have internet access, and cannot connect to SageMaker AI training and endpoint - * services.
- *For more information, see Notebook Instances Are Internet-Enabled by Default.
+ *Describes whether SageMaker AI provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker AI training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
* @public */ DirectInternetAccess?: DirectInternetAccess | undefined; @@ -3996,44 +3500,25 @@ export interface DescribeNotebookInstanceOutput { VolumeSizeInGB?: number | undefined; /** - *This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify a list of the EI instance types associated with - * this notebook instance.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types associated with this notebook instance.
* @public */ AcceleratorTypes?: NotebookInstanceAcceleratorType[] | undefined; /** - *The Git repository associated with the notebook instance as its default code - * repository. This can be either the name of a Git repository stored as a resource in your - * account, or the URL of a Git repository in Amazon Web Services CodeCommit - * or in any other Git repository. When you open a notebook instance, it opens in the - * directory that contains this repository. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ DefaultCodeRepository?: string | undefined; /** - *An array of up to three Git repositories associated with the notebook instance. These - * can be either the names of Git repositories stored as resources in your account, or the - * URL of Git repositories in Amazon Web Services CodeCommit - * or in any other Git repository. These repositories are cloned at the same level as the - * default repository of your notebook instance. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ AdditionalCodeRepositories?: string[] | undefined; /** - *Whether root access is enabled or disabled for users of the notebook instance.
- *Lifecycle configurations need root access to be able to set up a notebook - * instance. Because of this, lifecycle configurations associated with a notebook - * instance always run with root access even if you disable root access for - * users.
- *Whether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
The shell script that runs every time you start a notebook instance, including when - * you create the notebook instance.
+ *The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
* @public */ OnStart?: NotebookInstanceLifecycleHook[] | undefined; @@ -4139,8 +3623,7 @@ export type OptimizationJobStatus = (typeof OptimizationJobStatus)[keyof typeof */ export interface OptimizationOutput { /** - *The image that SageMaker recommends that you use to host the optimized model that you created - * with an optimization job.
+ *The image that SageMaker recommends that you use to host the optimized model that you created with an optimization job.
* @public */ RecommendedInferenceImage?: string | undefined; @@ -4187,8 +3670,7 @@ export interface DescribeOptimizationJobResponse { LastModifiedTime: Date | undefined; /** - *If the optimization job status is FAILED, the reason for the
- * failure.
If the optimization job status is FAILED, the reason for the failure.
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker - * ends the job. Use this API to cap costs.
- *To stop a training job, SageMaker sends the algorithm the SIGTERM signal,
- * which delays job termination for 120 seconds. Algorithms can use this 120-second window
- * to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results
- * of a model training job when possible. This attempt to save artifacts is only a best
- * effort case as model might not be in a state from which it can be saved. For example, if
- * training has just started, the model might not be ready to save. When saved, this
- * intermediate data is a valid model artifact. You can use it to create a model with
- * CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model - * artifacts. When training NTMs, make sure that the maximum runtime is sufficient for - * the training job to complete.
- *Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -4620,21 +4085,13 @@ export interface SelectedStep { */ export interface SelectiveExecutionConfig { /** - *The ARN from a reference execution of the current pipeline.
- * Used to copy input collaterals needed for the selected steps to run.
- * The execution status of the pipeline can be either Failed
- * or Success.
This field is required if the steps you specify for
- * SelectedSteps depend on output collaterals from any non-specified pipeline
- * steps. For more information, see Selective
- * Execution for Pipeline Steps.
The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed or Success.
This field is required if the steps you specify for SelectedSteps depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
A list of pipeline steps to run. All step(s) in all path(s) between - * two selected steps should be included.
+ *A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
* @public */ SelectedSteps: SelectedStep[] | undefined; @@ -4699,15 +4156,13 @@ export interface DescribePipelineExecutionResponse { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -4730,8 +4185,7 @@ export interface DescribePipelineExecutionResponse { */ export interface DescribeProcessingJobRequest { /** - *The name of the processing job. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ ProcessingJobName: string | undefined; @@ -4771,15 +4225,13 @@ export interface DescribeProcessingJobResponse { ProcessingOutputConfig?: ProcessingOutputConfig | undefined; /** - *The name of the processing job. The name must be unique within an Amazon Web Services - * Region in the Amazon Web Services account.
+ *The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
* @public */ ProcessingJobName: string | undefined; /** - *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a - * processing job. In distributed training, you specify more than one instance.
+ *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
* @public */ ProcessingResources: ProcessingResources | undefined; @@ -4809,8 +4261,7 @@ export interface DescribeProcessingJobResponse { NetworkConfig?: NetworkConfig | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on - * your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
* @public */ RoleArn?: string | undefined; @@ -4834,15 +4285,13 @@ export interface DescribeProcessingJobResponse { ProcessingJobStatus: ProcessingJobStatus | undefined; /** - *An optional string, up to one KB in size, that contains metadata from the processing - * container when the processing job exits.
+ *An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
* @public */ ExitMessage?: string | undefined; /** - *A string, up to one KB in size, that contains the reason a processing job failed, if - * it failed.
+ *A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
* @public */ FailureReason?: string | undefined; @@ -4872,8 +4321,7 @@ export interface DescribeProcessingJobResponse { CreationTime: Date | undefined; /** - *The ARN of a monitoring schedule for an endpoint associated with this processing - * job.
+ *The ARN of a monitoring schedule for an endpoint associated with this processing job.
* @public */ MonitoringScheduleArn?: string | undefined; @@ -4925,9 +4373,7 @@ export const ProjectStatus = { export type ProjectStatus = (typeof ProjectStatus)[keyof typeof ProjectStatus]; /** - *Details of a provisioned service catalog product. For information about service catalog, - * see What is Amazon Web Services Service - * Catalog.
+ *Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
* @public */ export interface ServiceCatalogProvisionedProductDetails { @@ -4938,29 +4384,7 @@ export interface ServiceCatalogProvisionedProductDetails { ProvisionedProductId?: string | undefined; /** - *The current status of the product.
- *
- * AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
- * UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
- * TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
- * ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
- * PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
The current status of the product.
AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
Information used to provision a service catalog product. For information, see What is Amazon Web Services Service - * Catalog.
+ *Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
* @public */ ServiceCatalogProvisioningDetails?: ServiceCatalogProvisioningDetails | undefined; @@ -5014,8 +4437,7 @@ export interface DescribeProjectOutput { ProjectStatus: ProjectStatus | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -5033,8 +4455,7 @@ export interface DescribeProjectOutput { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -5153,26 +4574,7 @@ export interface DescribeSpaceResponse { SpaceDisplayName?: string | undefined; /** - *Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity - * Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to - * the URL after appending the respective redirect parameter for the application type to be - * federated through Amazon Web Services IAM Identity Center.
- *The following application types are supported:
- *Studio Classic: &redirect=JupyterServer
- *
JupyterLab: &redirect=JupyterLab
- *
Code Editor, based on Code-OSS, Visual Studio Code - Open Source:
- * &redirect=CodeEditor
- *
Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to the URL after appending the respective redirect parameter for the application type to be federated through Amazon Web Services IAM Identity Center.
The following application types are supported:
Studio Classic: &redirect=JupyterServer
JupyterLab: &redirect=JupyterLab
Code Editor, based on Code-OSS, Visual Studio Code - Open Source: &redirect=CodeEditor
The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is - * described.
+ *The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is described.
* @public */ StudioLifecycleConfigName?: string | undefined; @@ -5213,8 +4614,7 @@ export interface DescribeStudioLifecycleConfigResponse { CreationTime?: Date | undefined; /** - *This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle - * Configurations are immutable.
+ *This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.
* @public */ LastModifiedTime?: Date | undefined; @@ -5405,191 +4805,30 @@ export const SecondaryStatus = { export type SecondaryStatus = (typeof SecondaryStatus)[keyof typeof SecondaryStatus]; /** - *An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the
- * training job has transitioned through. A training job can be in one of several states,
- * for example, starting, downloading, training, or uploading. Within each state, there are
- * a number of intermediate states. For example, within the starting state, SageMaker could be
- * starting the training job or launching the ML instances. These transitional states are
- * referred to as the job's secondary
- * status.
- *
An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job's secondary status.
Contains a secondary status information from a training - * job.
- *Status might be one of the following secondary statuses:
- *
- * Starting
- * - Starting the training job.
- * Downloading - An optional stage for algorithms that
- * support File training input mode. It indicates that
- * data is being downloaded to the ML storage volumes.
- * Training - Training is in progress.
- * Uploading - Training is complete and the model
- * artifacts are being uploaded to the S3 location.
- * Completed - The training job has completed.
- * Failed - The training job has failed. The reason for
- * the failure is returned in the FailureReason field of
- * DescribeTrainingJobResponse.
- * MaxRuntimeExceeded - The job stopped because it
- * exceeded the maximum allowed runtime.
- * Stopped - The training job has stopped.
- * Stopping - Stopping the training job.
We no longer support the following secondary statuses:
- *
- * LaunchingMLInstances
- *
- * PreparingTrainingStack
- *
- * DownloadingTrainingImage
- *
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
A timestamp that shows when the training job transitioned to the current secondary - * status state.
+ *A timestamp that shows when the training job transitioned to the current secondary status state.
* @public */ StartTime: Date | undefined; /** - *A timestamp that shows when the training job transitioned out of this secondary status - * state into another secondary status state or when the training job has ended.
+ *A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
* @public */ EndTime?: Date | undefined; /** - *A detailed description of the progress within a secondary status. - *
- *SageMaker provides secondary statuses and status messages that apply to each of - * them:
- *Starting the training job.
- *Launching requested ML - * instances.
- *Insufficient - * capacity error from EC2 while launching instances, - * retrying!
- *Launched - * instance was unhealthy, replacing it!
- *Preparing the instances for training.
- *Training - * image download completed. Training in - * progress.
- *Status messages are subject to change. Therefore, we recommend not including them - * in code that programmatically initiates actions. For examples, don't use status - * messages in if statements.
- *To have an overview of your training job's progress, view
- * TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example,
- * at the start of a training job, you might see the following:
- * TrainingJobStatus - InProgress
- * SecondaryStatus - Training
- * StatusMessage - Downloading the training image
A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don't use status messages in if statements.
To have an overview of your training job's progress, view TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example, at the start of a training job, you might see the following:
TrainingJobStatus - InProgress
SecondaryStatus - Training
StatusMessage - Downloading the training image
The status of the warm pool.
- *
- * InUse: The warm pool is in use for the training job.
- * Available: The warm pool is available to reuse for a matching
- * training job.
- * Reused: The warm pool moved to a matching training job for
- * reuse.
- * Terminated: The warm pool is no longer available. Warm pools are
- * unavailable if they are terminated by a user, terminated for a patch update, or
- * terminated for exceeding the specified
- * KeepAlivePeriodInSeconds.
The status of the warm pool.
InUse: The warm pool is in use for the training job.
Available: The warm pool is available to reuse for a matching training job.
Reused: The warm pool moved to a matching training job for reuse.
Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.
The billable time in seconds used by the warm pool. Billable time refers to the - * absolute wall-clock time.
- *Multiply ResourceRetainedBillableTimeInSeconds by the number of instances
- * (InstanceCount) in your training cluster to get the total compute time
- * SageMaker bills you if you run warm pool training. The formula is as follows:
- * ResourceRetainedBillableTimeInSeconds * InstanceCount.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount.
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the - * training job was launched by a hyperparameter tuning job.
+ *The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
* @public */ TuningJobArn?: string | undefined; /** - *The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the - * transform or training job.
+ *The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
* @public */ LabelingJobArn?: string | undefined; @@ -5700,151 +4909,19 @@ export interface DescribeTrainingJobResponse { AutoMLJobArn?: string | undefined; /** - *Information about the Amazon S3 location that is configured for storing model artifacts. - *
+ *Information about the Amazon S3 location that is configured for storing model artifacts.
* @public */ ModelArtifacts: ModelArtifacts | undefined; /** - *The status of the training job.
- *SageMaker provides the following training job statuses:
- *
- * InProgress - The training is in progress.
- * Completed - The training job has completed.
- * Failed - The training job has failed. To see the reason for the
- * failure, see the FailureReason field in the response to a
- * DescribeTrainingJobResponse call.
- * Stopping - The training job is stopping.
- * Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
Provides detailed information about the state of the training job. For detailed
- * information on the secondary status of the training job, see StatusMessage
- * under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of - * them:
- *
- * Starting
- * - Starting the training job.
- * Downloading - An optional stage for algorithms that
- * support File training input mode. It indicates that
- * data is being downloaded to the ML storage volumes.
- * Training - Training is in progress.
- * Interrupted - The job stopped because the managed
- * spot training instances were interrupted.
- * Uploading - Training is complete and the model
- * artifacts are being uploaded to the S3 location.
- * Completed - The training job has completed.
- * Failed - The training job has failed. The reason for
- * the failure is returned in the FailureReason field of
- * DescribeTrainingJobResponse.
- * MaxRuntimeExceeded - The job stopped because it
- * exceeded the maximum allowed runtime.
- * MaxWaitTimeExceeded - The job stopped because it
- * exceeded the maximum allowed wait time.
- * Stopped - The training job has stopped.
- * Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
- *
- * LaunchingMLInstances
- *
- * PreparingTraining
- *
- * DownloadingTrainingImage
- *
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Interrupted - The job stopped because the managed spot training instances were interrupted.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Information about the algorithm used for training, and algorithm metadata. - *
+ *Information about the algorithm used for training, and algorithm metadata.
* @public */ AlgorithmSpecification: AlgorithmSpecification | undefined; /** - *The Amazon Web Services Identity and Access Management (IAM) role configured for - * the training job.
+ *The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
* @public */ RoleArn?: string | undefined; /** - *An array of Channel objects that describes each data input channel.
- *
An array of Channel objects that describes each data input channel.
The S3 path where model artifacts that you configured when creating the job are - * stored. SageMaker creates subfolders for model artifacts.
+ *The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
* @public */ OutputDataConfig?: OutputDataConfig | undefined; /** - *Resources, including ML compute instances and ML storage volumes, that are - * configured for model training.
+ *Resources, including ML compute instances and ML storage volumes, that are configured for model training.
* @public */ ResourceConfig: ResourceConfig | undefined; @@ -5903,20 +4975,13 @@ export interface DescribeTrainingJobResponse { WarmPoolStatus?: WarmPoolStatus | undefined; /** - *A VpcConfig object that specifies the VPC that this training job has access - * to. For more information, see Protect Training Jobs by Using an Amazon - * Virtual Private Cloud.
+ *A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Specifies a limit to how long a model training job can run. It also specifies how long - * a managed Spot training job has to complete. When the job reaches the time limit, SageMaker - * ends the training job. Use this API to cap model training costs.
- *To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays
- * job termination for 120 seconds. Algorithms can use this 120-second window to save the
- * model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Indicates the time when the training job starts on training instances. You are
- * billed for the time interval between this time and the value of
- * TrainingEndTime. The start time in CloudWatch Logs might be later than this time.
- * The difference is due to the time it takes to download the training data and to the size
- * of the training container.
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed
- * for the time interval between the value of TrainingStartTime and this time.
- * For successful jobs and stopped jobs, this is the time after model artifacts are
- * uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last - * modified.
+ *A timestamp that indicates when the status of the training job was last modified.
* @public */ LastModifiedTime?: Date | undefined; /** - *A history of all of the secondary statuses that the training job has transitioned - * through.
+ *A history of all of the secondary statuses that the training job has transitioned through.
* @public */ SecondaryStatusTransitions?: SecondaryStatusTransition[] | undefined; /** - *A collection of MetricData objects that specify the names, values, and
- * dates and times that the training algorithm emitted to Amazon CloudWatch.
A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
If you want to allow inbound or outbound network calls, except for calls between peers
- * within a training cluster for distributed training, choose True. If you
- * enable network isolation for training jobs that are configured to use a VPC, SageMaker
- * downloads and uploads customer data and model artifacts through the specified VPC, but
- * the training container does not have network access.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training,
- * choose True. Encryption provides greater security for distributed training,
- * but training might take longer. How long it takes depends on the amount of communication
- * between compute instances, especially if you use a deep learning algorithms in
- * distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or
- * not (False).
A Boolean indicating whether managed spot training is enabled (True) or not (False).
Contains information about the output location for managed spot training checkpoint - * data.
+ *Contains information about the output location for managed spot training checkpoint data.
* @public */ CheckpointConfig?: CheckpointConfig | undefined; @@ -6008,49 +5053,19 @@ export interface DescribeTrainingJobResponse { TrainingTimeInSeconds?: number | undefined; /** - *The billable time in seconds. Billable time refers to the absolute wall-clock - * time.
- *Multiply BillableTimeInSeconds by the number of instances
- * (InstanceCount) in your training cluster to get the total compute time
- * SageMaker bills you if you run distributed training. The formula is as follows:
- * BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula
- * (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example,
- * if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is
- * 500, the savings is 80%.
The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and
- * storage paths. To learn more about
- * how to configure the DebugHookConfig parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -6074,15 +5089,13 @@ export interface DescribeTrainingJobResponse { DebugRuleEvaluationStatuses?: DebugRuleEvaluationStatus[] | undefined; /** - *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and - * storage paths.
+ *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
* @public */ ProfilerConfig?: ProfilerConfig | undefined; /** - *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework - * metrics.
+ *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
* @public */ ProfilerRuleConfigurations?: ProfilerRuleConfiguration[] | undefined; @@ -6100,30 +5113,19 @@ export interface DescribeTrainingJobResponse { ProfilingStatus?: ProfilingStatus | undefined; /** - *The environment variables to set in the Docker container.
- *Do not include any security-sensitive information including account access IDs, secrets, - * or tokens in any environment fields. As part of the shared responsibility - * model, you are responsible for any potential exposure, unauthorized access, or compromise of - * your sensitive data if caused by security-sensitive information included in the - * request environment variable or plain text fields.
- *The environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
The number of times to retry the job when the job fails due to an
- * InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
Configuration for remote debugging. To learn more about the remote debugging - * functionality of SageMaker, see Access a training container - * through Amazon Web Services Systems Manager (SSM) for remote - * debugging.
+ *Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
* @public */ RemoteDebugConfig?: RemoteDebugConfig | undefined; @@ -6183,11 +5185,7 @@ export const ReservedCapacityStatus = { export type ReservedCapacityStatus = (typeof ReservedCapacityStatus)[keyof typeof ReservedCapacityStatus]; /** - *Details of a reserved capacity for the training plan.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
Details of a reserved capacity for the training plan.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The additional minutes beyond whole hours in the total duration for this reserved - * capacity.
+ *The additional minutes beyond whole hours in the total duration for this reserved capacity.
* @public */ DurationMinutes?: number | undefined; @@ -6295,18 +5292,13 @@ export interface DescribeTrainingPlanResponse { TrainingPlanName: string | undefined; /** - *The current status of the training plan (e.g., Pending, Active, Expired). To see the
- * complete list of status values available for a training plan, refer to the
- * Status attribute within the
- * TrainingPlanSummary
- * object.
The current status of the training plan (e.g., Pending, Active, Expired). To see the complete list of status values available for a training plan, refer to the Status attribute within the TrainingPlanSummary object.
A message providing additional information about the current status of the training - * plan.
+ *A message providing additional information about the current status of the training plan.
* @public */ StatusMessage?: string | undefined; @@ -6318,8 +5310,7 @@ export interface DescribeTrainingPlanResponse { DurationHours?: number | undefined; /** - *The additional minutes beyond whole hours in the total duration for this training - * plan.
+ *The additional minutes beyond whole hours in the total duration for this training plan.
* @public */ DurationMinutes?: number | undefined; @@ -6367,26 +5358,13 @@ export interface DescribeTrainingPlanResponse { InUseInstanceCount?: number | undefined; /** - *The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) that can use this training - * plan.
- *Training plans are specific to their target resource.
- *A training plan designed for SageMaker training jobs can only be used to schedule and - * run training jobs.
- *A training plan for HyperPod clusters can be used exclusively to provide - * compute resources to a cluster's instance group.
- *The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) that can use this training plan.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
The list of Reserved Capacity providing the underlying compute resources of the plan. - *
+ *The list of Reserved Capacity providing the underlying compute resources of the plan.
* @public */ ReservedCapacitySummaries?: ReservedCapacitySummary[] | undefined; @@ -6437,21 +5415,13 @@ export interface DescribeTransformJobResponse { TransformJobArn: string | undefined; /** - *The
- * status of the transform job. If the transform job failed, the reason
- * is returned in the FailureReason field.
The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.
If the transform job failed, FailureReason describes
- * why
- * it failed. A transform job creates a log file, which includes error
- * messages, and stores it
- * as
- * an Amazon S3 object. For more information, see Log Amazon SageMaker Events with
- * Amazon CloudWatch.
If the transform job failed, FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The - * maximum number - * of - * parallel requests on each instance node - * that can be launched in a transform job. The default value is 1.
+ *The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
* @public */ MaxConcurrentTransforms?: number | undefined; /** - *The timeout and maximum number of retries for processing a transform job - * invocation.
+ *The timeout and maximum number of retries for processing a transform job invocation.
* @public */ ModelClientConfig?: ModelClientConfig | undefined; /** - *The - * maximum - * payload size, in MB, used in the - * transform job.
+ *The maximum payload size, in MB, used in the transform job.
* @public */ MaxPayloadInMB?: number | undefined; /** - *Specifies the number of records to include in a mini-batch for an HTTP inference - * request. - * A record - * is a single unit of input data that inference - * can be made on. For example, a single line in a CSV file is a record.
- *To enable the batch strategy, you must set SplitType
- * to
- * Line, RecordIO, or
- * TFRecord.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType to Line, RecordIO, or TFRecord.
The - * environment variables to set in the Docker container. We support up to 16 key and values - * entries in the map.
+ *The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
* @public */ Environment?: RecordDescribes the dataset to be transformed and the Amazon S3 location where it is - * stored.
+ *Describes the dataset to be transformed and the Amazon S3 location where it is stored.
* @public */ TransformInput: TransformInput | undefined; /** - *Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the - * transform job.
+ *Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
* @public */ TransformOutput?: TransformOutput | undefined; @@ -6531,9 +5481,7 @@ export interface DescribeTransformJobResponse { DataCaptureConfig?: BatchDataCaptureConfig | undefined; /** - *Describes - * the resources, including ML instance types and ML instance count, to - * use for the transform job.
+ *Describes the resources, including ML instance types and ML instance count, to use for the transform job.
* @public */ TransformResources: TransformResources | undefined; @@ -6545,26 +5493,19 @@ export interface DescribeTransformJobResponse { CreationTime: Date | undefined; /** - *Indicates when the transform job starts
- * on
- * ML instances. You are billed for the time interval between this time
- * and the value of TransformEndTime.
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been
- *
- * completed, or has stopped or failed. You are billed for the time
- * interval between this time and the value of TransformStartTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the - * transform or training job.
+ *The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
* @public */ LabelingJobArn?: string | undefined; @@ -6576,37 +5517,13 @@ export interface DescribeTransformJobResponse { AutoMLJobArn?: string | undefined; /** - *The data structure used to specify the data to be used for inference in a batch - * transform job and to associate the data that is relevant to the prediction results in - * the output. The input filter provided allows you to exclude input data that is not - * needed for inference in a batch transform job. The output filter provided allows you to - * include input data relevant to interpreting the predictions in the output from the job. - * For more information, see Associate Prediction - * Results with their Corresponding Input Records.
+ *The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
* @public */ DataProcessing?: DataProcessing | undefined; /** - *Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -6658,8 +5575,7 @@ export interface DescribeTrialResponse { TrialArn?: string | undefined; /** - *The name of the trial as displayed. If DisplayName isn't specified,
- * TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
The name of the component as displayed. If DisplayName isn't specified,
- * TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
- *InProgress
- *Completed
- *Failed
- *The status of the component. States include:
InProgress
Completed
Failed
A list of ARNs and, if applicable, job types for multiple sources of an experiment - * run.
+ *A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
* @public */ Sources?: TrialComponentSource[] | undefined; @@ -7034,9 +5937,7 @@ export interface DescribeUserProfileResponse { */ export interface DescribeWorkforceRequest { /** - *The name of the private workforce whose access you want to restrict.
- * WorkforceName is automatically set to default when a
- * workforce is created and cannot be modified.
The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.
A single private workforce, which is automatically created when you create your first - * private work team. You can create one private work force in each Amazon Web Services Region. By default, - * any workforce-related API operation used in a specific region will apply to the - * workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
+ *A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
* @public */ export interface Workforce { @@ -7170,16 +6068,13 @@ export interface Workforce { WorkforceArn: string | undefined; /** - *The most recent date that UpdateWorkforce was used to - * successfully add one or more IP address ranges (CIDRs) to a private workforce's - * allow list.
+ *The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce's allow list.
* @public */ LastUpdatedDate?: Date | undefined; /** - *A list of one to ten IP address ranges (CIDRs) to be added to the - * workforce allow list. By default, a workforce isn't restricted to specific IP addresses.
+ *A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn't restricted to specific IP addresses.
* @public */ SourceIpConfig?: SourceIpConfig | undefined; @@ -7191,10 +6086,7 @@ export interface Workforce { SubDomain?: string | undefined; /** - *The configuration of an Amazon Cognito workforce. - * A single Cognito workforce is created using and corresponds to a single - * - * Amazon Cognito user pool.
+ *The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
* @public */ CognitoConfig?: CognitoConfig | undefined; @@ -7235,10 +6127,7 @@ export interface Workforce { */ export interface DescribeWorkforceResponse { /** - *A single private workforce, which is automatically created when you create your first - * private work team. You can create one private work force in each Amazon Web Services Region. By default, - * any workforce-related API operation used in a specific region will apply to the - * workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
+ *A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
* @public */ Workforce: Workforce | undefined; @@ -7267,12 +6156,7 @@ export interface Workteam { WorkteamName: string | undefined; /** - *A list of MemberDefinition objects that contains objects that identify
- * the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP).
- * For private workforces created using Amazon Cognito use
- * CognitoMemberDefinition. For workforces created using your own OIDC identity
- * provider (IdP) use OidcMemberDefinition.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.
The URI of the labeling job's user interface. Workers open this URI to start labeling - * your data objects.
+ *The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.
* @public */ SubDomain?: string | undefined; @@ -7321,8 +6204,7 @@ export interface Workteam { LastUpdatedDate?: Date | undefined; /** - *Configures SNS notifications of available or expiring work items for work - * teams.
+ *Configures SNS notifications of available or expiring work items for work teams.
* @public */ NotificationConfiguration?: NotificationConfiguration | undefined; @@ -7339,8 +6221,7 @@ export interface Workteam { */ export interface DescribeWorkteamResponse { /** - *A Workteam instance that contains information about the work team.
- *
A Workteam instance that contains information about the work team.
The updated amount of provisioned concurrency to allocate for the serverless endpoint.
- * Should be less than or equal to MaxConcurrency.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
A collection of settings that update the current configuration for the
- * RStudioServerPro Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro Domain-level app.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that - * the version runs on.
- *When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
A collection of RStudioServerPro Domain-level app settings to update. A
- * single RStudioServerPro application is created for a domain.
A collection of RStudioServerPro Domain-level app settings to update. A single RStudioServerPro application is created for a domain.
The configuration for attaching a SageMaker AI user profile name to the execution
- * role as a sts:SourceIdentity key. This configuration can only be modified if there are no
- * apps in the InService or Pending state.
The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for
- * communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker - * Unified Studio.
+ *The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
* @public */ UnifiedStudioSettings?: UnifiedStudioSettings | undefined; @@ -7892,9 +6762,7 @@ export namespace MetricSpecification { } /** - *A target tracking scaling policy. Includes support for predefined or customized metrics.
- *When using the PutScalingPolicy API,
- * this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
The type of the Association(Edge) between the source and destination. For example ContributedTo,
- * Produced, or DerivedFrom.
The type of the Association(Edge) between the source and destination. For example ContributedTo, Produced, or DerivedFrom.
The path to the log file where the cluster step's failure root cause - * is recorded.
+ *The path to the log file where the cluster step's failure root cause is recorded.
* @public */ LogFilePath?: string | undefined; @@ -8202,8 +7068,7 @@ export interface EnableSagemakerServicecatalogPortfolioInput {} export interface EnableSagemakerServicecatalogPortfolioOutput {} /** - *A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model - * Monitor.
+ *A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
* @public */ export interface MonitoringSchedule { @@ -8220,25 +7085,7 @@ export interface MonitoringSchedule { MonitoringScheduleName?: string | undefined; /** - *The status of the monitoring schedule. This can be one of the following values.
- *
- * PENDING - The schedule is pending being created.
- * FAILED - The schedule failed.
- * SCHEDULED - The schedule was successfully created.
- * STOPPED - The schedule was stopped.
The status of the monitoring schedule. This can be one of the following values.
PENDING - The schedule is pending being created.
FAILED - The schedule failed.
SCHEDULED - The schedule was successfully created.
STOPPED - The schedule was stopped.
A list of the tags associated with the monitoring schedlue. For more information, see - * Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
+ *A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -8318,8 +7163,7 @@ export interface Endpoint { EndpointConfigName: string | undefined; /** - *A list of the production variants hosted on the endpoint. Each production variant is a - * model.
+ *A list of the production variants hosted on the endpoint. Each production variant is a model.
* @public */ ProductionVariants?: ProductionVariantSummary[] | undefined; @@ -8355,22 +7199,19 @@ export interface Endpoint { LastModifiedTime: Date | undefined; /** - *A list of monitoring schedules for the endpoint. For information about model - * monitoring, see Amazon SageMaker Model Monitor.
+ *A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
* @public */ MonitoringSchedules?: MonitoringSchedule[] | undefined; /** - *A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
+ *A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; /** - *A list of the shadow variants hosted on the endpoint. Each shadow variant is a model - * in shadow mode with production traffic replicated from the production variant.
+ *A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
* @public */ ShadowProductionVariants?: ProductionVariantSummary[] | undefined; @@ -8483,66 +7324,14 @@ export interface EndpointSummary { LastModifiedTime: Date | undefined; /** - *The status of the endpoint.
- *
- * OutOfService: Endpoint is not available to take incoming
- * requests.
- * Creating: CreateEndpoint is executing.
- * Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
- * SystemUpdating: Endpoint is undergoing maintenance and cannot be
- * updated or deleted or re-scaled until it has completed. This maintenance
- * operation does not change any customer-specified values such as VPC config, KMS
- * encryption, model, instance type, or instance count.
- * RollingBack: Endpoint fails to scale up or down or change its
- * variant weight and is in the process of rolling back to its previous
- * configuration. Once the rollback completes, endpoint returns to an
- * InService status. This transitional status only applies to an
- * endpoint that has autoscaling enabled and is undergoing variant weight or
- * capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called
- * explicitly.
- * InService: Endpoint is available to process incoming
- * requests.
- * Deleting: DeleteEndpoint is executing.
- * Failed: Endpoint could not be created, updated, or re-scaled. Use
- * DescribeEndpointOutput$FailureReason for information about the
- * failure. DeleteEndpoint is the only operation that can be performed on a
- * failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals
- * filter with a call to ListEndpoints.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals filter with a call to ListEndpoints.
The properties of an experiment as returned by the Search API. - * For information about experiments, see the - * CreateExperiment API.
+ *The properties of an experiment as returned by the Search API. For information about experiments, see the CreateExperiment API.
* @public */ export interface Experiment { @@ -8559,8 +7348,7 @@ export interface Experiment { ExperimentArn?: string | undefined; /** - *The name of the experiment as displayed. If DisplayName isn't specified,
- * ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -8610,9 +7397,7 @@ export interface Experiment { } /** - *A summary of the properties of an experiment. To get the complete set of properties, call
- * the DescribeExperiment API and provide the
- * ExperimentName.
A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.
The name of the experiment as displayed. If DisplayName isn't specified,
- * ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
A message that you define and then is processed and rendered by - * the Fail step when the error occurs.
+ *A message that you define and then is processed and rendered by the Fail step when the error occurs.
* @public */ ErrorMessage?: string | undefined; } /** - *Amazon SageMaker Feature Store stores features in a collection called Feature Group. A - * Feature Group can be visualized as a table which has rows, with a unique identifier for - * each row where each column in the table is a feature. In principle, a Feature Group is - * composed of features and values per features.
+ *Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
* @public */ export interface FeatureGroup { @@ -8688,34 +7468,19 @@ export interface FeatureGroup { FeatureGroupName?: string | undefined; /** - *The name of the Feature whose value uniquely identifies a
- * Record defined in the FeatureGroup
- * FeatureDefinitions.
The name of the Feature whose value uniquely identifies a Record defined in the FeatureGroup FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a
- * FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to
- * the creation or update of a Record in FeatureGroup. All
- * Records in the FeatureGroup must have a corresponding
- * EventTime.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
A list of Features. Each Feature must include a
- * FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and
- * String.
- * FeatureNames cannot be any of the following: is_deleted,
- * write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per
- * FeatureGroup.
A list of Features. Each Feature must include a FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or
- * KMSKeyId, for at rest data encryption. You can turn
- * OnlineStore on or off by specifying the EnableOnlineStore flag
- * at General Assembly.
The default value is False.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly.
The default value is False.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to
- * CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in
- * S3StorageConfig.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
The Amazon Resource Name (ARN) of the IAM execution role used to create the feature - * group.
+ *The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
* @public */ RoleArn?: string | undefined; @@ -8778,10 +7534,7 @@ export interface FeatureGroup { LastUpdateStatus?: LastUpdateStatus | undefined; /** - *The reason that the FeatureGroup failed to be replicated in the
- * OfflineStore. This is failure may be due to a failure to create a
- * FeatureGroup in or delete a FeatureGroup from the
- * OfflineStore.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure may be due to a failure to create a FeatureGroup in or delete a FeatureGroup from the OfflineStore.
The name, ARN, CreationTime, FeatureGroup values,
- * LastUpdatedTime and EnableOnlineStorage status of a
- * FeatureGroup.
The name, ARN, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.
A timestamp indicating the time of creation time of the
- * FeatureGroup.
A timestamp indicating the time of creation time of the FeatureGroup.
The status of a FeatureGroup. The status can be any of the following:
- * Creating, Created, CreateFail,
- * Deleting or DetailFail.
The status of a FeatureGroup. The status can be any of the following: Creating, Created, CreateFail, Deleting or DetailFail.
Notifies you if replicating data into the OfflineStore has failed. Returns
- * either: Active or Blocked.
Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked.
The metadata for a feature. It can either be metadata that you specify, or metadata that - * is updated automatically.
+ *The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
* @public */ export interface FeatureMetadata { @@ -8949,201 +7695,24 @@ export const Operator = { export type Operator = (typeof Operator)[keyof typeof Operator]; /** - *A conditional statement for a search expression that includes a resource property, a - * Boolean operator, and a value. Resources that match the statement are returned in the results - * from the Search API.
- *If you specify a Value, but not an Operator, SageMaker uses the
- * equals operator.
In search, there are several property types:
- *To define a metric filter, enter a value using the form
- * "Metrics., where "accuracy" metric greater than "0.9":
- * \{
- *
- * "Name": "Metrics.accuracy",
- *
- * "Operator": "GreaterThan",
- *
- * "Value": "0.9"
- *
- * \}
- *
To define a hyperparameter filter, enter a value with the form
- * "HyperParameters.. Decimal hyperparameter values are treated
- * as a decimal in a comparison if the specified Value is also a decimal
- * value. If the specified Value is an integer, the decimal hyperparameter
- * values are treated as integers. For example, the following filter is satisfied by
- * training jobs with a "learning_rate" hyperparameter that is less than
- * "0.5":
- * \{
- *
- * "Name": "HyperParameters.learning_rate",
- *
- * "Operator": "LessThan",
- *
- * "Value": "0.5"
- *
- * \}
- *
To define a tag filter, enter a value with the form
- * Tags..
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form "Metrics.<name>", where <name> is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9":
\{
"Name": "Metrics.accuracy",
"Operator": "GreaterThan",
"Value": "0.9"
\}
To define a hyperparameter filter, enter a value with the form "HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a "learning_rate" hyperparameter that is less than "0.5":
\{
"Name": "HyperParameters.learning_rate",
"Operator": "LessThan",
"Value": "0.5"
\}
To define a tag filter, enter a value with the form Tags.<key>.
A resource property name. For example, TrainingJobName. For valid property
- * names, see SearchRecord. You must
- * specify a valid property for the resource.
A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
A Boolean binary operator that is used to evaluate the filter. The operator field contains - * one of the following values:
- *The value of Name equals Value.
The value of Name doesn't equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for
- * text properties.
The value of Name is greater than or equal to Value. Not
- * supported for text properties.
The value of Name is less than Value. Not supported for
- * text properties.
The value of Name is less than or equal to Value. Not
- * supported for text properties.
The value of Name is one of the comma delimited strings in
- * Value. Only supported for text properties.
The value of Name contains the string Value. Only
- * supported for text properties.
A SearchExpression can include the Contains operator
- * multiple times when the value of Name is one of the following:
- * Experiment.DisplayName
- *
- * Experiment.ExperimentName
- *
- * Experiment.Tags
- *
- * Trial.DisplayName
- *
- * Trial.TrialName
- *
- * Trial.Tags
- *
- * TrialComponent.DisplayName
- *
- * TrialComponent.TrialComponentName
- *
- * TrialComponent.Tags
- *
- * TrialComponent.InputArtifacts
- *
- * TrialComponent.OutputArtifacts
- *
A SearchExpression can include only one Contains operator
- * for all other values of Name. In these cases, if you include multiple
- * Contains operators in the SearchExpression, the result is
- * the following error message: "'CONTAINS' operator usage limit of 1
- * exceeded."
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name equals Value.
The value of Name doesn't equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for text properties.
The value of Name is greater than or equal to Value. Not supported for text properties.
The value of Name is less than Value. Not supported for text properties.
The value of Name is less than or equal to Value. Not supported for text properties.
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: "'CONTAINS' operator usage limit of 1 exceeded."
A value used with Name and Operator to determine which resources
- * satisfy the filter's condition. For numerical properties, Value must be an
- * integer or floating-point decimal. For timestamp properties, Value must be an ISO
- * 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
A value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
The recommendation ID of a previously completed inference recommendation. This ID should come from one of the
- * recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the
- * recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
The number of invocations sent to a model, normalized by InstanceCount
- * in each ProductionVariant. 1/numberOfInstances is sent as the value on each
- * request, where numberOfInstances is the number of active instances for the
- * ProductionVariant behind the endpoint at the time of the request.
The number of invocations sent to a model, normalized by InstanceCount in each ProductionVariant. 1/numberOfInstances is sent as the value on each request, where numberOfInstances is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker. - * This interval includes the local communication times taken to send the request - * and to fetch the response from the container of a model and the time taken to - * complete the inference in the container.
+ *The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
* @public */ ModelLatency?: number | undefined; @@ -9488,8 +8047,7 @@ export const ResourceType = { export type ResourceType = (typeof ResourceType)[keyof typeof ResourceType]; /** - *Part of the SuggestionQuery type. Specifies a hint for retrieving property
- * names that begin with the specified text.
Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.
Specified in the GetSearchSuggestions request. Limits the property names that are included in the - * response.
+ *Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
* @public */ export interface SuggestionQuery { /** - *Defines a property name hint. Only property names that begin with the specified hint are - * included in the response.
+ *Defines a property name hint. Only property names that begin with the specified hint are included in the response.
* @public */ PropertyNameQuery?: PropertyNameQuery | undefined; @@ -9532,14 +8088,12 @@ export interface GetSearchSuggestionsRequest { } /** - *A property name returned from a GetSearchSuggestions call that specifies a
- * value in the PropertyNameQuery field.
A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.
A suggested property name based on what you entered in the search textbox in the SageMaker - * console.
+ *A suggested property name based on what you entered in the search textbox in the SageMaker console.
* @public */ PropertyName?: string | undefined; @@ -9550,27 +8104,19 @@ export interface PropertyNameSuggestion { */ export interface GetSearchSuggestionsResponse { /** - *A list of property names for a Resource that match a
- * SuggestionQuery.
A list of property names for a Resource that match a SuggestionQuery.
Specifies configuration details for a Git repository when the repository is - * updated.
+ *Specifies configuration details for a Git repository when the repository is updated.
* @public */ export interface GitConfigForUpdate { /** - *The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that
- * contains the credentials used to access the git repository. The secret must have a
- * staging label of AWSCURRENT and must be in the following format:
- * \{"username": UserName, "password":
- * Password\}
- *
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
\{"username": UserName, "password": Password\}
An entity returned by the SearchRecord API - * containing the properties of a hyperparameter tuning job.
+ *An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
* @public */ export interface HyperParameterTuningJobSearchEntity { @@ -9794,8 +8339,7 @@ export interface HyperParameterTuningJobSearchEntity { HyperParameterTuningJobConfig?: HyperParameterTuningJobConfig | undefined; /** - *Defines - * the training jobs launched by a hyperparameter tuning job.
+ *Defines the training jobs launched by a hyperparameter tuning job.
* @public */ TrainingJobDefinition?: HyperParameterTrainingJobDefinition | undefined; @@ -9831,19 +8375,13 @@ export interface HyperParameterTuningJobSearchEntity { LastModifiedTime?: Date | undefined; /** - *The numbers of training jobs launched by a hyperparameter tuning job, categorized by - * status.
+ *The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
* @public */ TrainingJobStatusCounters?: TrainingJobStatusCounters | undefined; /** - *Specifies the number of training jobs that this hyperparameter tuning job launched, - * categorized by the status of their objective metric. The objective metric status shows - * whether the - * final - * objective metric for the training job has been evaluated by the - * tuning job and used in the hyperparameter tuning process.
+ *Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
* @public */ ObjectiveStatusCounters?: ObjectiveStatusCounters | undefined; @@ -9861,20 +8399,7 @@ export interface HyperParameterTuningJobSearchEntity { OverallBestTrainingJob?: HyperParameterTrainingJobSummary | undefined; /** - *Specifies the configuration for a hyperparameter tuning job that uses one or more - * previous hyperparameter tuning jobs as a starting point. The results of previous tuning - * jobs are used to inform which combinations of hyperparameters to search over in the new - * tuning job.
- *All training jobs launched by the new hyperparameter tuning job are evaluated by using - * the objective metric, and the training job that performs the best is compared to the - * best training jobs from the parent tuning jobs. From these, the training job that - * performs the best as measured by the objective metric is returned as the overall best - * training job.
- *All training jobs launched by parent hyperparameter tuning jobs and the new - * hyperparameter tuning jobs count against the limit of training jobs for the tuning - * job.
- *Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The - * Amazon - * Resource Name (ARN) of the tuning job.
+ *The Amazon Resource Name (ARN) of the tuning job.
* @public */ HyperParameterTuningJobArn: string | undefined; /** - *The status of the - * tuning - * job.
+ *The status of the tuning job.
* @public */ HyperParameterTuningJobStatus: HyperParameterTuningJobStatus | undefined; /** - *Specifies the search strategy hyperparameter tuning uses to choose which - * hyperparameters to - * evaluate - * at each iteration.
+ *Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
* @public */ Strategy: HyperParameterTuningJobStrategyType | undefined; @@ -9969,39 +8487,32 @@ export interface HyperParameterTuningJobSummary { HyperParameterTuningEndTime?: Date | undefined; /** - *The date and time that the tuning job was - * modified.
+ *The date and time that the tuning job was modified.
* @public */ LastModifiedTime?: Date | undefined; /** - *The TrainingJobStatusCounters object that specifies the numbers of training - * jobs, categorized by status, that this tuning job launched.
+ *The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
* @public */ TrainingJobStatusCounters: TrainingJobStatusCounters | undefined; /** - *The ObjectiveStatusCounters object that specifies the numbers of training jobs, - * categorized by objective metric status, that this tuning job launched.
+ *The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
* @public */ ObjectiveStatusCounters: ObjectiveStatusCounters | undefined; /** - *The ResourceLimits - * object that specifies the maximum number of training jobs and parallel training jobs - * allowed for this tuning job.
+ *The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
* @public */ ResourceLimits?: ResourceLimits | undefined; } /** - *A SageMaker AI image. A SageMaker AI image represents a set of container images that are derived from
- * a common base container image. Each of these container images is represented by a SageMaker AI
- * ImageVersion.
A SageMaker AI image. A SageMaker AI image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker AI ImageVersion.
A version of a SageMaker AI Image. A version represents an existing container
- * image.
A version of a SageMaker AI Image. A version represents an existing container image.
The duration for which the inference experiment ran or will run.
- *The maximum duration that you can set for an inference experiment is 30 days.
+ *The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
* @public */ Schedule?: InferenceExperimentSchedule | undefined; @@ -10385,10 +8894,7 @@ export interface InferenceExperimentSummary { LastModifiedTime: Date | undefined; /** - *- * The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage - * Amazon SageMaker Inference endpoints for model deployment. - *
+ *The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
* @public */ RoleArn?: string | undefined; @@ -10457,8 +8963,7 @@ export interface InferenceRecommendationsJob { CompletionTime?: Date | undefined; /** - *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker - * to perform tasks on your behalf.
+ *The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
* @public */ RoleArn: string | undefined; @@ -10482,8 +8987,7 @@ export interface InferenceRecommendationsJob { ModelName?: string | undefined; /** - *The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. - * This path must point to a single gzip compressed tar archive (.tar.gz suffix).
+ *The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
* @public */ SamplePayloadUrl?: string | undefined; @@ -10557,15 +9061,12 @@ export const RecommendationStepType = { export type RecommendationStepType = (typeof RecommendationStepType)[keyof typeof RecommendationStepType]; /** - *A returned array object for the Steps response field in the
- * ListInferenceRecommendationsJobSteps API command.
A returned array object for the Steps response field in the ListInferenceRecommendationsJobSteps API command.
The type of the subtask.
- *
- * BENCHMARK: Evaluate the performance of your model on different instance types.
The type of the subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
A unique identifier for a labeling job. You can use this to refer to a specific - * labeling job.
+ *A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
* @public */ JobReferenceCode: string | undefined; /** - *The Amazon Web Services account ID of the account used to start the labeling - * job.
+ *The Amazon Web Services account ID of the account used to start the labeling job.
* @public */ WorkRequesterAccountId: string | undefined; @@ -10669,8 +9168,7 @@ export interface LabelingJobSummary { LabelingJobName: string | undefined; /** - *The Amazon Resource Name (ARN) assigned to the labeling job when it was - * created.
+ *The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
* @public */ LabelingJobArn: string | undefined; @@ -10706,24 +9204,19 @@ export interface LabelingJobSummary { WorkteamArn: string | undefined; /** - *The Amazon Resource Name (ARN) of a Lambda function. The function is run before each - * data object is sent to a worker.
+ *The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
* @public */ PreHumanTaskLambdaArn?: string | undefined; /** - *The Amazon Resource Name (ARN) of the Lambda function used to consolidate the - * annotations from individual workers into a label for a data object. For more - * information, see Annotation - * Consolidation.
+ *The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
* @public */ AnnotationConsolidationLambdaArn?: string | undefined; /** - *If the LabelingJobStatus field is Failed, this field
- * contains a description of the error.
If the LabelingJobStatus field is Failed, this field contains a description of the error.
Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity - * resources.
+ *Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
* @public */ export interface LineageGroupSummary { @@ -10881,8 +9373,7 @@ export interface ListActionsRequest { SortOrder?: SortOrder | undefined; /** - *If the previous call to ListActions didn't return the full set of actions,
- * the call returns a token for getting the next set of actions.
If the previous call to ListActions didn't return the full set of actions, the call returns a token for getting the next set of actions.
A filter that returns only algorithms created after the specified time - * (timestamp).
+ *A filter that returns only algorithms created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only algorithms created before the specified time - * (timestamp).
+ *A filter that returns only algorithms created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; @@ -10936,23 +9425,19 @@ export interface ListAlgorithmsInput { MaxResults?: number | undefined; /** - *A string in the algorithm name. This filter returns only algorithms whose name - * contains the specified string.
+ *A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *If the response to a previous ListAlgorithms request was truncated, the
- * response includes a NextToken. To retrieve the next set of algorithms, use
- * the token in the next request.
If the response to a previous ListAlgorithms request was truncated, the response includes a NextToken. To retrieve the next set of algorithms, use the token in the next request.
The parameter by which to sort the results. The default is
- * CreationTime.
The parameter by which to sort the results. The default is CreationTime.
>An array of AlgorithmSummary objects, each of which lists an
- * algorithm.
>An array of AlgorithmSummary objects, each of which lists an algorithm.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * algorithms, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -11012,8 +9495,7 @@ export interface ListAliasesRequest { MaxResults?: number | undefined; /** - *If the previous call to ListAliases didn't return the full set of
- * aliases, the call returns a token for retrieving the next set of aliases.
If the previous call to ListAliases didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases.
The total number of items to return in the response. If the total
- * number of items available is more than the value specified, a NextToken
- * is provided in the response. To resume pagination, provide the NextToken
- * value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
If the previous call to ListImages didn't return the full set of
- * AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
If the previous call to ListImages didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; /** - *This parameter defines the maximum number of results that can be return in a single
- * response. The MaxResults parameter is an upper bound, not a target. If there are
- * more results available than the value specified, a NextToken is provided in the
- * response. The NextToken indicates that the user should get the next set of
- * results by providing this token as a part of a subsequent call. The default value for
- * MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
A parameter to search by user profile name. If SpaceNameEquals is set, then
- * this value cannot be set.
A parameter to search by user profile name. If SpaceNameEquals is set, then this value cannot be set.
A parameter to search by space name. If UserProfileNameEquals is set, then
- * this value cannot be set.
A parameter to search by space name. If UserProfileNameEquals is set, then this value cannot be set.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11243,8 +9712,7 @@ export interface ListArtifactsRequest { SortOrder?: SortOrder | undefined; /** - *If the previous call to ListArtifacts didn't return the full set of artifacts,
- * the call returns a token for getting the next set of artifacts.
If the previous call to ListArtifacts didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts.
If the previous call to ListAssociations didn't return the full set of associations,
- * the call returns a token for getting the next set of associations.
If the previous call to ListAssociations didn't return the full set of associations, the call returns a token for getting the next set of associations.
If the previous response was truncated, you receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11456,8 +9922,7 @@ export interface ListAutoMLJobsResponse { AutoMLJobSummaries: AutoMLJobSummary[] | undefined; /** - *If the previous response was truncated, you receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11492,8 +9957,7 @@ export interface ListCandidatesForAutoMLJobRequest { SortOrder?: AutoMLSortOrder | undefined; /** - *The parameter by which to sort the results. The default is
- * Descending.
The parameter by which to sort the results. The default is Descending.
If the previous response was truncated, you receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11523,8 +9986,7 @@ export interface ListCandidatesForAutoMLJobResponse { Candidates: AutoMLCandidate[] | undefined; /** - *If the previous response was truncated, you receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11535,51 +9997,19 @@ export interface ListCandidatesForAutoMLJobResponse { */ export interface ListClusterNodesRequest { /** - *The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the - * list of nodes.
+ *The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the list of nodes.
* @public */ ClusterName: string | undefined; /** - *A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. - * Timestamps are formatted according to the ISO 8601 standard.
- *Acceptable formats include:
- *
- * YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example,
- * 2014-10-01T20:30:00.000Z
- *
- * YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example,
- * 2014-10-01T12:30:00.000-08:00
- *
- * YYYY-MM-DD, for example, 2014-10-01
- *
Unix time in seconds, for example, 1412195400. This is also referred
- * to as Unix Epoch time and represents the number of seconds since midnight, January 1,
- * 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User - * Guide.
+ *A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD, for example, 2014-10-01
Unix time in seconds, for example, 1412195400. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The
- * acceptable formats are the same as the timestamp formats for
- * CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User
- * Guide.
A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
If the result of the previous ListClusterNodes request was truncated, the
- * response includes a NextToken. To retrieve the next set of cluster nodes, use
- * the token in the next request.
If the result of the previous ListClusterNodes request was truncated, the response includes a NextToken. To retrieve the next set of cluster nodes, use the token in the next request.
The field by which to sort results. The default value is
- * CREATION_TIME.
The field by which to sort results. The default value is CREATION_TIME.
Set a start time for the time range during which you want to list SageMaker HyperPod clusters. - * Timestamps are formatted according to the ISO 8601 standard.
- *Acceptable formats include:
- *
- * YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example,
- * 2014-10-01T20:30:00.000Z
- *
- * YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example,
- * 2014-10-01T12:30:00.000-08:00
- *
- * YYYY-MM-DD, for example, 2014-10-01
- *
Unix time in seconds, for example, 1412195400. This is also referred
- * to as Unix Epoch time and represents the number of seconds since midnight, January 1,
- * 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User - * Guide.
+ *Set a start time for the time range during which you want to list SageMaker HyperPod clusters. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD, for example, 2014-10-01
Unix time in seconds, for example, 1412195400. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
* @public */ CreationTimeAfter?: Date | undefined; /** - *Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A
- * filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The
- * acceptable formats are the same as the timestamp formats for
- * CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User
- * Guide.
Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
The field by which to sort results. The default value is
- * CREATION_TIME.
The field by which to sort results. The default value is CREATION_TIME.
The Amazon Resource Name (ARN); of the training plan to filter clusters by. For more information about
- * reserving GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
The Amazon Resource Name (ARN); of the training plan to filter clusters by. For more information about reserving GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
If the result of the previous ListClusters request was truncated, the
- * response includes a NextToken. To retrieve the next set of clusters, use the
- * token in the next request.
If the result of the previous ListClusters request was truncated, the response includes a NextToken. To retrieve the next set of clusters, use the token in the next request.
Filter for after this creation time. The input for this parameter is a Unix timestamp. - * To convert a date and time into a Unix timestamp, see EpochConverter.
+ *Filter for after this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
* @public */ CreatedAfter?: Date | undefined; /** - *Filter for before this creation time. The input for this parameter is a Unix timestamp. - * To convert a date and time into a Unix timestamp, see EpochConverter.
+ *Filter for before this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
* @public */ CreatedBefore?: Date | undefined; @@ -11796,23 +10183,19 @@ export interface ListClusterSchedulerConfigsRequest { Status?: SchedulerResourceStatus | undefined; /** - *Filter for sorting the list by a given value. For example, sort by name, creation time, - * or status.
+ *Filter for sorting the list by a given value. For example, sort by name, creation time, or status.
* @public */ SortBy?: SortClusterSchedulerConfigBy | undefined; /** - *The order of the list. By default, listed in Descending order according to
- * by SortBy. To change the list order, you can specify SortOrder to
- * be Ascending.
The order of the list. By default, listed in Descending order according to by SortBy. To change the list order, you can specify SortOrder to be Ascending.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11835,8 +10218,7 @@ export interface ListClusterSchedulerConfigsResponse { ClusterSchedulerConfigSummaries?: ClusterSchedulerConfigSummary[] | undefined; /** - *If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -11847,29 +10229,25 @@ export interface ListClusterSchedulerConfigsResponse { */ export interface ListCodeRepositoriesInput { /** - *A filter that returns only Git repositories that were created after the specified - * time.
+ *A filter that returns only Git repositories that were created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only Git repositories that were created before the specified - * time.
+ *A filter that returns only Git repositories that were created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only Git repositories that were last modified after the - * specified time.
+ *A filter that returns only Git repositories that were last modified after the specified time.
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *A filter that returns only Git repositories that were last modified before the - * specified time.
+ *A filter that returns only Git repositories that were last modified before the specified time.
* @public */ LastModifiedTimeBefore?: Date | undefined; @@ -11881,16 +10259,13 @@ export interface ListCodeRepositoriesInput { MaxResults?: number | undefined; /** - *A string in the Git repositories name. This filter returns only repositories whose - * name contains the specified string.
+ *A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *If the result of a ListCodeRepositoriesOutput request was truncated, the
- * response includes a NextToken. To get the next set of Git repositories, use
- * the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
Gets a list of summaries of the Git repositories. Each summary specifies the following - * values for the repository:
- *Name
- *Amazon Resource Name (ARN)
- *Creation time
- *Last modified time
- *Configuration information, including the URL location of the repository and - * the ARN of the Amazon Web Services Secrets Manager secret that contains the - * credentials used to access the repository.
- *Gets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
If the result of a ListCodeRepositoriesOutput request was truncated, the
- * response includes a NextToken. To get the next set of Git repositories, use
- * the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of model
- * compilation jobs, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
A filter that returns the model compilation jobs that were created after a specified - * time.
+ *A filter that returns the model compilation jobs that were created after a specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns the model compilation jobs that were created before a specified - * time.
+ *A filter that returns the model compilation jobs that were created before a specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns the model compilation jobs that were modified after a specified - * time.
+ *A filter that returns the model compilation jobs that were modified after a specified time.
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *A filter that returns the model compilation jobs that were modified before a specified - * time.
+ *A filter that returns the model compilation jobs that were modified before a specified time.
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *A filter that returns the model compilation jobs whose name contains a specified - * string.
+ *A filter that returns the model compilation jobs whose name contains a specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that retrieves model compilation jobs with a specific
- * CompilationJobStatus status.
A filter that retrieves model compilation jobs with a specific CompilationJobStatus status.
An array of CompilationJobSummary objects, each describing a model compilation job. - *
+ *An array of CompilationJobSummary objects, each describing a model compilation job.
* @public */ CompilationJobSummaries: CompilationJobSummary[] | undefined; /** - *If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve
- * the next set of model compilation jobs, use this token in the next request.
If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.
Filter for after this creation time. The input for this parameter is a Unix timestamp. - * To convert a date and time into a Unix timestamp, see EpochConverter.
+ *Filter for after this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
* @public */ CreatedAfter?: Date | undefined; /** - *Filter for before this creation time. The input for this parameter is a Unix timestamp. - * To convert a date and time into a Unix timestamp, see EpochConverter.
+ *Filter for before this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
* @public */ CreatedBefore?: Date | undefined; @@ -246,23 +244,19 @@ export interface ListComputeQuotasRequest { ClusterArn?: string | undefined; /** - *Filter for sorting the list by a given value. For example, sort by name, creation time, - * or status.
+ *Filter for sorting the list by a given value. For example, sort by name, creation time, or status.
* @public */ SortBy?: SortQuotaBy | undefined; /** - *The order of the list. By default, listed in Descending order according to
- * by SortBy. To change the list order, you can specify SortOrder to
- * be Ascending.
The order of the list. By default, listed in Descending order according to by SortBy. To change the list order, you can specify SortOrder to be Ascending.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -285,8 +279,7 @@ export interface ListComputeQuotasResponse { ComputeQuotaSummaries?: ComputeQuotaSummary[] | undefined; /** - *If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -347,8 +340,7 @@ export interface ListContextsRequest { SortOrder?: SortOrder | undefined; /** - *If the previous call to ListContexts didn't return the full set of contexts,
- * the call returns a token for getting the next set of contexts.
If the previous call to ListContexts didn't return the full set of contexts, the call returns a token for getting the next set of contexts.
A filter that lists the data quality job definitions associated with the specified - * endpoint.
+ *A filter that lists the data quality job definitions associated with the specified endpoint.
* @public */ EndpointName?: string | undefined; @@ -410,44 +401,37 @@ export interface ListDataQualityJobDefinitionsRequest { SortBy?: MonitoringJobDefinitionSortKey | undefined; /** - *Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
If the result of the previous ListDataQualityJobDefinitions request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.>
The maximum number of data quality monitoring job definitions to return in the - * response.
+ *The maximum number of data quality monitoring job definitions to return in the response.
* @public */ MaxResults?: number | undefined; /** - *A string in the data quality monitoring job definition name. This filter returns only - * data quality monitoring job definitions whose name contains the specified string.
+ *A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only data quality monitoring job definitions created before the - * specified time.
+ *A filter that returns only data quality monitoring job definitions created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only data quality monitoring job definitions created after the - * specified time.
+ *A filter that returns only data quality monitoring job definitions created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; @@ -494,9 +478,7 @@ export interface ListDataQualityJobDefinitionsResponse { JobDefinitionSummaries: MonitoringJobDefinitionSummary[] | undefined; /** - *If the result of the previous ListDataQualityJobDefinitions request was
- * truncated, the response includes a NextToken. To retrieve the next set of data
- * quality monitoring job definitions, use the token in the next request.
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; /** - *This parameter defines the maximum number of results that can be return in a single
- * response. The MaxResults parameter is an upper bound, not a target. If there are
- * more results available than the value specified, a NextToken is provided in the
- * response. The NextToken indicates that the user should get the next set of
- * results by providing this token as a part of a subsequent call. The default value for
- * MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -708,8 +683,7 @@ export type ListEdgeDeploymentPlansSortBy = */ export interface ListEdgeDeploymentPlansRequest { /** - *The response from the last list when returning a list large enough to need - * tokening.
+ *The response from the last list when returning a list large enough to need tokening.
* @public */ NextToken?: string | undefined; @@ -757,9 +731,7 @@ export interface ListEdgeDeploymentPlansRequest { DeviceFleetNameContains?: string | undefined; /** - *The column by which to sort the edge deployment plans. Can be one of
- * NAME, DEVICEFLEETNAME, CREATIONTIME,
- * LASTMODIFIEDTIME.
The column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME, CREATIONTIME, LASTMODIFIEDTIME.
If the result of the previous ListEndpointConfig request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * endpoint configurations, use the token in the next request.
If the result of the previous ListEndpointConfig request was truncated, the response includes a NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.
A string in the endpoint configuration name. This filter returns only endpoint - * configurations whose name contains the specified string.
+ *A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only endpoint configurations created before the specified - * time (timestamp).
+ *A filter that returns only endpoint configurations created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only endpoint configurations with a creation time greater - * than or equal to the specified time (timestamp).
+ *A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; @@ -971,8 +938,7 @@ export interface ListEndpointConfigsOutput { EndpointConfigs: EndpointConfigSummary[] | undefined; /** - *If the response is truncated, SageMaker returns this token. To retrieve the next set of - * endpoint configurations, use it in the subsequent request
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
* @public */ NextToken?: string | undefined; @@ -995,51 +961,43 @@ export interface ListEndpointsInput { SortOrder?: OrderKey | undefined; /** - *If the result of a ListEndpoints request was truncated, the response
- * includes a NextToken. To retrieve the next set of endpoints, use the token
- * in the next request.
If the result of a ListEndpoints request was truncated, the response includes a NextToken. To retrieve the next set of endpoints, use the token in the next request.
The maximum number of endpoints to return in the response. This value defaults to - * 10.
+ *The maximum number of endpoints to return in the response. This value defaults to 10.
* @public */ MaxResults?: number | undefined; /** - *A string in endpoint names. This filter returns only endpoints whose name contains - * the specified string.
+ *A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only endpoints that were created before the specified time - * (timestamp).
+ *A filter that returns only endpoints that were created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only endpoints with a creation time greater than or equal to - * the specified time (timestamp).
+ *A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only endpoints that were modified before the specified - * timestamp.
+ *A filter that returns only endpoints that were modified before the specified timestamp.
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *A filter that returns only endpoints that were modified after the specified - * timestamp.
+ *A filter that returns only endpoints that were modified after the specified timestamp.
* @public */ LastModifiedTimeAfter?: Date | undefined; @@ -1062,8 +1020,7 @@ export interface ListEndpointsOutput { Endpoints: EndpointSummary[] | undefined; /** - *If the response is truncated, SageMaker returns this token. To retrieve the next set of - * training jobs, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -1112,15 +1069,13 @@ export interface ListExperimentsRequest { SortOrder?: SortOrder | undefined; /** - *If the previous call to ListExperiments didn't return the full set of
- * experiments, the call returns a token for getting the next set of experiments.
If the previous call to ListExperiments didn't return the full set of experiments, the call returns a token for getting the next set of experiments.
The maximum number of experiments to return in the response. The default value is - * 10.
+ *The maximum number of experiments to return in the response. The default value is 10.
* @public */ MaxResults?: number | undefined; @@ -1148,8 +1103,7 @@ export interface ListExperimentsResponse { */ export interface ListFeatureGroupsRequest { /** - *A string that partially matches one or more FeatureGroups names. Filters
- * FeatureGroups by name.
A string that partially matches one or more FeatureGroups names. Filters FeatureGroups by name.
An OfflineStore status. Filters by OfflineStore status.
- *
An OfflineStore status. Filters by OfflineStore status.
Use this parameter to search for FeatureGroupss created after a specific
- * date and time.
Use this parameter to search for FeatureGroupss created after a specific date and time.
Use this parameter to search for FeatureGroupss created before a specific
- * date and time.
Use this parameter to search for FeatureGroupss created before a specific date and time.
If the result of the previous ListHyperParameterTuningJobs request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * tuning jobs, use the token in the next request.
If the result of the previous ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
The - * maximum number of tuning jobs to return. The default value is - * 10.
+ *The maximum number of tuning jobs to return. The default value is 10.
* @public */ MaxResults?: number | undefined; @@ -1606,36 +1553,31 @@ export interface ListHyperParameterTuningJobsRequest { SortOrder?: SortOrder | undefined; /** - *A string in the tuning job name. This filter returns only tuning jobs whose name - * contains the specified string.
+ *A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only tuning jobs that were created after the specified - * time.
+ *A filter that returns only tuning jobs that were created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only tuning jobs that were created before the specified - * time.
+ *A filter that returns only tuning jobs that were created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only tuning jobs that were modified after the specified - * time.
+ *A filter that returns only tuning jobs that were modified after the specified time.
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *A filter that returns only tuning jobs that were modified before the specified - * time.
+ *A filter that returns only tuning jobs that were modified before the specified time.
* @public */ LastModifiedTimeBefore?: Date | undefined; @@ -1652,18 +1594,13 @@ export interface ListHyperParameterTuningJobsRequest { */ export interface ListHyperParameterTuningJobsResponse { /** - *A list of HyperParameterTuningJobSummary objects that
- * describe
- * the tuning jobs that the ListHyperParameterTuningJobs
- * request returned.
A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs request returned.
If the result of this ListHyperParameterTuningJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of tuning jobs,
- * use the token in the next request.
If the result of this ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
If the previous call to ListImages didn't return the full set of images,
- * the call returns a token for getting the next set of images.
If the previous call to ListImages didn't return the full set of images, the call returns a token for getting the next set of images.
If the previous call to ListImageVersions didn't return the full set of
- * versions, the call returns a token for getting the next set of versions.
If the previous call to ListImageVersions didn't return the full set of versions, the call returns a token for getting the next set of versions.
The field by which to sort the inference components in the response. The default is
- * CreationTime.
The field by which to sort the inference components in the response. The default is CreationTime.
A token that you use to get the next set of results following a truncated response. If - * the response to the previous request was truncated, that response provides the value for - * this token.
+ *A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
* @public */ NextToken?: string | undefined; /** - *The maximum number of inference components to return in the response. This value - * defaults to 10.
+ *The maximum number of inference components to return in the response. This value defaults to 10.
* @public */ MaxResults?: number | undefined; /** - *Filters the results to only those inference components with a name that contains the - * specified string.
+ *Filters the results to only those inference components with a name that contains the specified string.
* @public */ NameContains?: string | undefined; /** - *Filters the results to only those inference components that were created before the - * specified time.
+ *Filters the results to only those inference components that were created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *Filters the results to only those inference components that were created after the - * specified time.
+ *Filters the results to only those inference components that were created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *Filters the results to only those inference components that were updated before the - * specified time.
+ *Filters the results to only those inference components that were updated before the specified time.
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *Filters the results to only those inference components that were updated after the - * specified time.
+ *Filters the results to only those inference components that were updated after the specified time.
* @public */ LastModifiedTimeAfter?: Date | undefined; @@ -1897,15 +1823,13 @@ export interface ListInferenceComponentsInput { StatusEquals?: InferenceComponentStatus | undefined; /** - *An endpoint name to filter the listed inference components. The response includes only - * those inference components that are hosted at the specified endpoint.
+ *An endpoint name to filter the listed inference components. The response includes only those inference components that are hosted at the specified endpoint.
* @public */ EndpointNameEquals?: string | undefined; /** - *A production variant name to filter the listed inference components. The response - * includes only those inference components that are hosted at the specified variant.
+ *A production variant name to filter the listed inference components. The response includes only those inference components that are hosted at the specified variant.
* @public */ VariantNameEquals?: string | undefined; @@ -1916,15 +1840,13 @@ export interface ListInferenceComponentsInput { */ export interface ListInferenceComponentsOutput { /** - *A list of inference components and their properties that matches any of the filters you - * specified in the request.
+ *A list of inference components and their properties that matches any of the filters you specified in the request.
* @public */ InferenceComponents: InferenceComponentSummary[] | undefined; /** - *The token to use in a subsequent request to get the next set of results following a - * truncated response.
+ *The token to use in a subsequent request to get the next set of results following a truncated response.
* @public */ NextToken?: string | undefined; @@ -1956,17 +1878,13 @@ export interface ListInferenceExperimentsRequest { NameContains?: string | undefined; /** - *- * Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment. - *
+ *Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
* @public */ Type?: InferenceExperimentType | undefined; /** - *- * Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment. - *
+ *Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
* @public */ StatusEquals?: InferenceExperimentStatus | undefined; @@ -2008,9 +1926,7 @@ export interface ListInferenceExperimentsRequest { SortOrder?: SortOrder | undefined; /** - *- * The response from the last list when returning a list large enough to need tokening. - *
+ *The response from the last list when returning a list large enough to need tokening.
* @public */ NextToken?: string | undefined; @@ -2108,9 +2024,7 @@ export interface ListInferenceRecommendationsJobsRequest { SortOrder?: SortOrder | undefined; /** - *If the response to a previous ListInferenceRecommendationsJobsRequest request
- * was truncated, the response includes a NextToken. To retrieve the next set
- * of recommendations, use the token in the next request.
If the response to a previous ListInferenceRecommendationsJobsRequest request was truncated, the response includes a NextToken. To retrieve the next set of recommendations, use the token in the next request.
A filter to return details about the specified type of subtask.
- *
- * BENCHMARK: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
A filter that returns only labeling jobs created after the specified time - * (timestamp).
+ *A filter that returns only labeling jobs created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only labeling jobs created before the specified time - * (timestamp).
+ *A filter that returns only labeling jobs created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only labeling jobs modified after the specified time - * (timestamp).
+ *A filter that returns only labeling jobs modified after the specified time (timestamp).
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *A filter that returns only labeling jobs modified before the specified time - * (timestamp).
+ *A filter that returns only labeling jobs modified before the specified time (timestamp).
* @public */ LastModifiedTimeBefore?: Date | undefined; @@ -2259,16 +2167,13 @@ export interface ListLabelingJobsRequest { MaxResults?: number | undefined; /** - *If the result of the previous ListLabelingJobs request was truncated, the
- * response includes a NextToken. To retrieve the next set of labeling jobs,
- * use the token in the next request.
If the result of the previous ListLabelingJobs request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
A string in the labeling job name. This filter returns only labeling jobs whose name - * contains the specified string.
+ *A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
* @public */ NameContains?: string | undefined; @@ -2297,15 +2202,13 @@ export interface ListLabelingJobsRequest { */ export interface ListLabelingJobsResponse { /** - *An array of LabelingJobSummary objects, each describing a labeling
- * job.
An array of LabelingJobSummary objects, each describing a labeling job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * labeling jobs, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -2330,8 +2233,7 @@ export type ListLabelingJobsForWorkteamSortByOptions = */ export interface ListLabelingJobsForWorkteamRequest { /** - *The Amazon Resource Name (ARN) of the work team for which you want to see labeling - * jobs for.
+ *The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
* @public */ WorkteamArn: string | undefined; @@ -2343,30 +2245,25 @@ export interface ListLabelingJobsForWorkteamRequest { MaxResults?: number | undefined; /** - *If the result of the previous ListLabelingJobsForWorkteam request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * labeling jobs, use the token in the next request.
If the result of the previous ListLabelingJobsForWorkteam request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
A filter that returns only labeling jobs created after the specified time - * (timestamp).
+ *A filter that returns only labeling jobs created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only labeling jobs created before the specified time - * (timestamp).
+ *A filter that returns only labeling jobs created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter the limits jobs to only the ones whose job reference code contains the - * specified string.
+ *A filter the limits jobs to only the ones whose job reference code contains the specified string.
* @public */ JobReferenceCodeContains?: string | undefined; @@ -2389,15 +2286,13 @@ export interface ListLabelingJobsForWorkteamRequest { */ export interface ListLabelingJobsForWorkteamResponse { /** - *An array of LabelingJobSummary objects, each describing a labeling
- * job.
An array of LabelingJobSummary objects, each describing a labeling job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * labeling jobs, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -2434,8 +2329,7 @@ export interface ListLineageGroupsRequest { CreatedBefore?: Date | undefined; /** - *The parameter by which to sort the results. The default is
- * CreationTime.
The parameter by which to sort the results. The default is CreationTime.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * algorithms, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
* @public */ NextToken?: string | undefined; /** - *The maximum number of endpoints to return in the response. This value defaults to - * 10.
+ *The maximum number of endpoints to return in the response. This value defaults to 10.
* @public */ MaxResults?: number | undefined; @@ -2472,8 +2364,7 @@ export interface ListLineageGroupsResponse { LineageGroupSummaries?: LineageGroupSummary[] | undefined; /** - *If the response is truncated, SageMaker returns this token. To retrieve the next set of - * algorithms, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -2499,19 +2390,13 @@ export type SortTrackingServerBy = (typeof SortTrackingServerBy)[keyof typeof So */ export interface ListMlflowTrackingServersRequest { /** - *Use the CreatedAfter filter to only list tracking servers created after a
- * specific date and time. Listed tracking servers are shown with a date and time such as
- * "2024-03-16T01:46:56+00:00". The CreatedAfter parameter takes in a
- * Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedAfter filter to only list tracking servers created after a specific date and time. Listed tracking servers are shown with a date and time such as "2024-03-16T01:46:56+00:00". The CreatedAfter parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedBefore filter to only list tracking servers created before a
- * specific date and time. Listed tracking servers are shown with a date and time such as
- * "2024-03-16T01:46:56+00:00". The CreatedBefore parameter takes in
- * a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedBefore filter to only list tracking servers created before a specific date and time. Listed tracking servers are shown with a date and time such as "2024-03-16T01:46:56+00:00". The CreatedBefore parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Change the order of the listed tracking servers. By default, tracking servers are listed in Descending order by creation time.
- * To change the list order, you can specify SortOrder to be Ascending.
Change the order of the listed tracking servers. By default, tracking servers are listed in Descending order by creation time. To change the list order, you can specify SortOrder to be Ascending.
Whether to sort results by the Name or CreationTime field.
- * The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; /** - *The maximum number of model bias jobs to return in the response. The default value is - * 10.
+ *The maximum number of model bias jobs to return in the response. The default value is 10.
* @public */ MaxResults?: number | undefined; @@ -2687,8 +2567,7 @@ export interface ListModelBiasJobDefinitionsResponse { JobDefinitionSummaries: MonitoringJobDefinitionSummary[] | undefined; /** - *The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -2777,9 +2656,7 @@ export interface ListModelCardExportJobsRequest { SortOrder?: ModelCardExportJobSortOrder | undefined; /** - *If the response to a previous ListModelCardExportJobs request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * model card export jobs, use the token in the next request.
If the response to a previous ListModelCardExportJobs request was truncated, the response includes a NextToken. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model - * card export jobs, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -2920,9 +2796,7 @@ export interface ListModelCardsRequest { ModelCardStatus?: ModelCardStatus | undefined; /** - *If the response to a previous ListModelCards request was truncated, the
- * response includes a NextToken. To retrieve the next set of model cards, use
- * the token in the next request.
If the response to a previous ListModelCards request was truncated, the response includes a NextToken. To retrieve the next set of model cards, use the token in the next request.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model - * cards, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -3061,9 +2915,7 @@ export interface ListModelCardVersionsRequest { ModelCardStatus?: ModelCardStatus | undefined; /** - *If the response to a previous ListModelCardVersions request was truncated,
- * the response includes a NextToken. To retrieve the next set of model card
- * versions, use the token in the next request.
If the response to a previous ListModelCardVersions request was truncated, the response includes a NextToken. To retrieve the next set of model card versions, use the token in the next request.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model - * card versions, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -3171,22 +3003,19 @@ export interface ListModelExplainabilityJobDefinitionsRequest { EndpointName?: string | undefined; /** - *Whether to sort results by the Name or CreationTime field.
- * The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -3204,15 +3033,13 @@ export interface ListModelExplainabilityJobDefinitionsRequest { NameContains?: string | undefined; /** - *A filter that returns only model explainability jobs created before a specified - * time.
+ *A filter that returns only model explainability jobs created before a specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only model explainability jobs created after a specified - * time.
+ *A filter that returns only model explainability jobs created after a specified time.
* @public */ CreationTimeAfter?: Date | undefined; @@ -3229,8 +3056,7 @@ export interface ListModelExplainabilityJobDefinitionsResponse { JobDefinitionSummaries: MonitoringJobDefinitionSummary[] | undefined; /** - *The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -3253,8 +3079,7 @@ export const ModelMetadataFilterType = { export type ModelMetadataFilterType = (typeof ModelMetadataFilterType)[keyof typeof ModelMetadataFilterType]; /** - *Part of the search expression. You can specify the name and value - * (domain, task, framework, framework version, task, and model).
+ *Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
* @public */ export interface ModelMetadataFilter { @@ -3272,9 +3097,7 @@ export interface ModelMetadataFilter { } /** - *One or more filters that searches for the specified resource or resources in - * a search. All resource objects that satisfy the expression's condition are - * included in the search results
+ *One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results
* @public */ export interface ModelMetadataSearchExpression { @@ -3290,18 +3113,13 @@ export interface ModelMetadataSearchExpression { */ export interface ListModelMetadataRequest { /** - *One or more filters that searches for the specified resource or resources - * in a search. All resource objects that satisfy the expression's condition are - * included in the search results. Specify the Framework, FrameworkVersion, Domain - * or Task to filter supported. Filter names and values are case-sensitive.
+ *One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
* @public */ SearchExpression?: ModelMetadataSearchExpression | undefined; /** - *If the response to a previous ListModelMetadataResponse request was truncated,
- * the response includes a NextToken. To retrieve the next set of model metadata,
- * use the token in the next request.
If the response to a previous ListModelMetadataResponse request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A string in the model group name. This filter returns only model groups whose name - * contains the specified string.
+ *A string in the model group name. This filter returns only model groups whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *If the result of the previous ListModelPackageGroups request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * model groups, use the token in the next request.
If the result of the previous ListModelPackageGroups request was truncated, the response includes a NextToken. To retrieve the next set of model groups, use the token in the next request.
A filter that returns either model groups shared with you or model groups in your own
- * account. When the value is CrossAccount, the results show the resources
- * made discoverable to you from other accounts. When the value is SameAccount
- * or null, the results show resources from your account. The default is
- * SameAccount.
A filter that returns either model groups shared with you or model groups in your own account. When the value is CrossAccount, the results show the resources made discoverable to you from other accounts. When the value is SameAccount or null, the results show resources from your account. The default is SameAccount.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * model groups, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -3528,15 +3338,13 @@ export type ModelPackageSortBy = (typeof ModelPackageSortBy)[keyof typeof ModelP */ export interface ListModelPackagesInput { /** - *A filter that returns only model packages created after the specified time - * (timestamp).
+ *A filter that returns only model packages created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only model packages created before the specified time - * (timestamp).
+ *A filter that returns only model packages created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; @@ -3548,59 +3356,37 @@ export interface ListModelPackagesInput { MaxResults?: number | undefined; /** - *A string in the model package name. This filter returns only model packages whose name - * contains the specified string.
+ *A string in the model package name. This filter returns only model packages whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only the model packages with the specified approval - * status.
+ *A filter that returns only the model packages with the specified approval status.
* @public */ ModelApprovalStatus?: ModelApprovalStatus | undefined; /** - *A filter that returns only model versions that belong to the specified model - * group.
+ *A filter that returns only model versions that belong to the specified model group.
* @public */ ModelPackageGroupName?: string | undefined; /** - *A filter that returns only the model packages of the specified type. This can be one - * of the following values.
- *
- * UNVERSIONED - List only unversioined models. This is the default
- * value if no ModelPackageType is specified.
- * VERSIONED - List only versioned models.
- * BOTH - List both versioned and unversioned models.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED - List only unversioined models. This is the default value if no ModelPackageType is specified.
VERSIONED - List only versioned models.
BOTH - List both versioned and unversioned models.
If the response to a previous ListModelPackages request was truncated,
- * the response includes a NextToken. To retrieve the next set of model
- * packages, use the token in the next request.
If the response to a previous ListModelPackages request was truncated, the response includes a NextToken. To retrieve the next set of model packages, use the token in the next request.
The parameter by which to sort the results. The default is
- * CreationTime.
The parameter by which to sort the results. The default is CreationTime.
If the model package is a versioned model, the model group that the versioned model - * belongs to.
+ *If the model package is a versioned model, the model group that the versioned model belongs to.
* @public */ ModelPackageGroupName?: string | undefined; @@ -3661,22 +3446,7 @@ export interface ModelPackageSummary { ModelPackageStatus: ModelPackageStatus | undefined; /** - *The approval status of the model. This can be one of the following values.
- *
- * APPROVED - The model is approved
- * REJECTED - The model is rejected.
- * PENDING_MANUAL_APPROVAL - The model is waiting for manual
- * approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
An array of ModelPackageSummary objects, each of which lists a model
- * package.
An array of ModelPackageSummary objects, each of which lists a model package.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * model packages, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -3712,8 +3480,7 @@ export interface ListModelPackagesOutput { */ export interface ListModelQualityJobDefinitionsRequest { /** - *A filter that returns only model quality monitoring job definitions that are associated - * with the specified endpoint.
+ *A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
* @public */ EndpointName?: string | undefined; @@ -3725,44 +3492,37 @@ export interface ListModelQualityJobDefinitionsRequest { SortBy?: MonitoringJobDefinitionSortKey | undefined; /** - *Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
If the result of the previous ListModelQualityJobDefinitions request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * model quality monitoring job definitions, use the token in the next request.
If the result of the previous ListModelQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
The maximum number of results to return in a call to
- * ListModelQualityJobDefinitions.
The maximum number of results to return in a call to ListModelQualityJobDefinitions.
A string in the transform job name. This filter returns only model quality monitoring - * job definitions whose name contains the specified string.
+ *A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only model quality monitoring job definitions created before the - * specified time.
+ *A filter that returns only model quality monitoring job definitions created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only model quality monitoring job definitions created after the - * specified time.
+ *A filter that returns only model quality monitoring job definitions created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; @@ -3779,8 +3539,7 @@ export interface ListModelQualityJobDefinitionsResponse { JobDefinitionSummaries: MonitoringJobDefinitionSummary[] | undefined; /** - *If the response is truncated, Amazon SageMaker AI returns this token. To retrieve the - * next set of model quality monitoring job definitions, use it in the next request.
+ *If the response is truncated, Amazon SageMaker AI returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -3817,9 +3576,7 @@ export interface ListModelsInput { SortOrder?: OrderKey | undefined; /** - *If the response to a previous ListModels request was truncated, the
- * response includes a NextToken. To retrieve the next set of models, use the
- * token in the next request.
If the response to a previous ListModels request was truncated, the response includes a NextToken. To retrieve the next set of models, use the token in the next request.
A string in the model name. This filter returns only models whose name contains the - * specified string.
+ *A string in the model name. This filter returns only models whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only models created before the specified time - * (timestamp).
+ *A filter that returns only models created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only models with a creation time greater than or equal to the - * specified time (timestamp).
+ *A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; @@ -3881,15 +3635,13 @@ export interface ModelSummary { */ export interface ListModelsOutput { /** - *An array of ModelSummary objects, each of which lists a
- * model.
An array of ModelSummary objects, each of which lists a model.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * models, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -3947,16 +3699,13 @@ export interface ListMonitoringAlertHistoryRequest { SortBy?: MonitoringAlertHistorySortKey | undefined; /** - *The sort order, whether Ascending or Descending, of the alert
- * history. The default is Descending.
The sort order, whether Ascending or Descending, of the alert history. The default is Descending.
If the result of the previous ListMonitoringAlertHistory request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * alerts in the history, use the token in the next request.
If the result of the previous ListMonitoringAlertHistory request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
A timestamp that indicates when the first alert transition occurred in an alert history.
- * An alert transition can be from status InAlert to OK,
- * or from OK to InAlert.
A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK, or from OK to InAlert.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * alerts, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -4047,9 +3793,7 @@ export interface ListMonitoringAlertsRequest { MonitoringScheduleName: string | undefined; /** - *If the result of the previous ListMonitoringAlerts request was truncated,
- * the response includes a NextToken. To retrieve the next set of alerts in the
- * history, use the token in the next request.
If the result of the previous ListMonitoringAlerts request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into
- * InAlert status.
An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert status.
A list of alert actions taken in response to an alert going into
- * InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into
- * InAlert status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.
Within EvaluationPeriod, how many execution failures will raise an
- * alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
The number of most recent monitoring executions to consider when evaluating alert - * status.
+ *The number of most recent monitoring executions to consider when evaluating alert status.
* @public */ EvaluationPeriod: number | undefined; /** - *A list of alert actions taken in response to an alert going into
- * InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * alerts, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -4189,22 +3926,19 @@ export interface ListMonitoringExecutionsRequest { EndpointName?: string | undefined; /** - *Whether to sort the results by the Status, CreationTime, or
- * ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -4258,15 +3992,13 @@ export interface ListMonitoringExecutionsRequest { StatusEquals?: ExecutionStatus | undefined; /** - *Gets a list of the monitoring job runs of the specified monitoring job - * definitions.
+ *Gets a list of the monitoring job runs of the specified monitoring job definitions.
* @public */ MonitoringJobDefinitionName?: string | undefined; /** - *A filter that returns only the monitoring job runs of the specified monitoring - * type.
+ *A filter that returns only the monitoring job runs of the specified monitoring type.
* @public */ MonitoringTypeEquals?: MonitoringType | undefined; @@ -4283,8 +4015,7 @@ export interface ListMonitoringExecutionsResponse { MonitoringExecutionSummaries: MonitoringExecutionSummary[] | undefined; /** - *The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -4316,22 +4047,19 @@ export interface ListMonitoringSchedulesRequest { EndpointName?: string | undefined; /** - *Whether to sort the results by the Status, CreationTime, or
- * ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order.
- * The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -4379,15 +4107,13 @@ export interface ListMonitoringSchedulesRequest { StatusEquals?: ScheduleStatus | undefined; /** - *Gets a list of the monitoring schedules for the specified monitoring job - * definition.
+ *Gets a list of the monitoring schedules for the specified monitoring job definition.
* @public */ MonitoringJobDefinitionName?: string | undefined; /** - *A filter that returns only the monitoring schedules for the specified monitoring - * type.
+ *A filter that returns only the monitoring schedules for the specified monitoring type.
* @public */ MonitoringTypeEquals?: MonitoringType | undefined; @@ -4458,8 +4184,7 @@ export interface ListMonitoringSchedulesResponse { MonitoringScheduleSummaries: MonitoringScheduleSummary[] | undefined; /** - *The token returned if the response is truncated. To retrieve the next set of job executions, use - * it in the next request.
+ *The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -4501,9 +4226,7 @@ export type NotebookInstanceLifecycleConfigSortOrder = */ export interface ListNotebookInstanceLifecycleConfigsInput { /** - *If the result of a ListNotebookInstanceLifecycleConfigs request was
- * truncated, the response includes a NextToken. To get the next set of
- * lifecycle configurations, use the token in the next request.
If the result of a ListNotebookInstanceLifecycleConfigs request was truncated, the response includes a NextToken. To get the next set of lifecycle configurations, use the token in the next request.
A string in the lifecycle configuration name. This filter returns only lifecycle - * configurations whose name contains the specified string.
+ *A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only lifecycle configurations that were created before the - * specified time (timestamp).
+ *A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only lifecycle configurations that were created after the - * specified time (timestamp).
+ *A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only lifecycle configurations that were modified before the - * specified time (timestamp).
+ *A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *A filter that returns only lifecycle configurations that were modified after the - * specified time (timestamp).
+ *A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
* @public */ LastModifiedTimeAfter?: Date | undefined; @@ -4597,15 +4315,13 @@ export interface NotebookInstanceLifecycleConfigSummary { */ export interface ListNotebookInstanceLifecycleConfigsOutput { /** - *If the response is truncated, SageMaker AI returns this token. To get the next - * set of lifecycle configurations, use it in the next request.
+ *If the response is truncated, SageMaker AI returns this token. To get the next set of lifecycle configurations, use it in the next request.
* @public */ NextToken?: string | undefined; /** - *An array of NotebookInstanceLifecycleConfiguration objects, each listing
- * a lifecycle configuration.
An array of NotebookInstanceLifecycleConfiguration objects, each listing a lifecycle configuration.
If the previous call to the ListNotebookInstances is truncated, the
- * response includes a NextToken. You can use this token in your subsequent
- * ListNotebookInstances request to fetch the next set of notebook
- * instances.
You might specify a filter or a sort order in your request. When response is - * truncated, you must use the same values for the filer and sort order in the next - * request.
- * If the previous call to the ListNotebookInstances is truncated, the response includes a NextToken. You can use this token in your subsequent ListNotebookInstances request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
A string in the notebook instances' name. This filter returns only notebook - * instances whose name contains the specified string.
+ *A string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A filter that returns only notebook instances that were created before the - * specified time (timestamp).
+ *A filter that returns only notebook instances that were created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only notebook instances that were created after the specified - * time (timestamp).
+ *A filter that returns only notebook instances that were created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only notebook instances that were modified before the - * specified time (timestamp).
+ *A filter that returns only notebook instances that were modified before the specified time (timestamp).
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *A filter that returns only notebook instances that were modified after the - * specified time (timestamp).
+ *A filter that returns only notebook instances that were modified after the specified time (timestamp).
* @public */ LastModifiedTimeAfter?: Date | undefined; @@ -4718,24 +4421,19 @@ export interface ListNotebookInstancesInput { StatusEquals?: NotebookInstanceStatus | undefined; /** - *A string in the name of a notebook instances lifecycle configuration associated with - * this notebook instance. This filter returns only notebook instances associated with a - * lifecycle configuration with a name that contains the specified string.
+ *A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
* @public */ NotebookInstanceLifecycleConfigNameContains?: string | undefined; /** - *A string in the name or URL of a Git repository associated with this notebook - * instance. This filter returns only notebook instances associated with a git repository - * with a name that contains the specified string.
+ *A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
* @public */ DefaultCodeRepositoryContains?: string | undefined; /** - *A filter that returns only notebook instances with associated with the specified git - * repository.
+ *A filter that returns only notebook instances with associated with the specified git repository.
* @public */ AdditionalCodeRepositoryEquals?: string | undefined; @@ -4765,8 +4463,7 @@ export interface NotebookInstanceSummary { NotebookInstanceStatus?: NotebookInstanceStatus | undefined; /** - *The URL that you use to connect to the Jupyter notebook running in your notebook - * instance.
+ *The URL that you use to connect to the Jupyter notebook running in your notebook instance.
* @public */ Url?: string | undefined; @@ -4790,32 +4487,19 @@ export interface NotebookInstanceSummary { LastModifiedTime?: Date | undefined; /** - *The name of a notebook instance lifecycle configuration associated with this notebook - * instance.
- *For information about notebook instance lifestyle configurations, see Step - * 2.1: (Optional) Customize a Notebook Instance.
+ *The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @public */ NotebookInstanceLifecycleConfigName?: string | undefined; /** - *The Git repository associated with the notebook instance as its default code - * repository. This can be either the name of a Git repository stored as a resource in your - * account, or the URL of a Git repository in Amazon Web Services CodeCommit - * or in any other Git repository. When you open a notebook instance, it opens in the - * directory that contains this repository. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ DefaultCodeRepository?: string | undefined; /** - *An array of up to three Git repositories associated with the notebook instance. These - * can be either the names of Git repositories stored as resources in your account, or the - * URL of Git repositories in Amazon Web Services CodeCommit - * or in any other Git repository. These repositories are cloned at the same level as the - * default repository of your notebook instance. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ AdditionalCodeRepositories?: string[] | undefined; @@ -4826,16 +4510,13 @@ export interface NotebookInstanceSummary { */ export interface ListNotebookInstancesOutput { /** - *If the response to the previous ListNotebookInstances request was
- * truncated, SageMaker AI returns this token. To retrieve the next set of notebook
- * instances, use the token in the next request.
If the response to the previous ListNotebookInstances request was truncated, SageMaker AI returns this token. To retrieve the next set of notebook instances, use the token in the next request.
An array of NotebookInstanceSummary objects, one for each notebook
- * instance.
An array of NotebookInstanceSummary objects, one for each notebook instance.
A token that you use to get the next set of results following a truncated response. If - * the response to the previous request was truncated, that response provides the value for - * this token.
+ *A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
* @public */ NextToken?: string | undefined; /** - *The maximum number of optimization jobs to return in the response. The default is - * 50.
+ *The maximum number of optimization jobs to return in the response. The default is 50.
* @public */ MaxResults?: number | undefined; /** - *Filters the results to only those optimization jobs that were created after the - * specified time.
+ *Filters the results to only those optimization jobs that were created after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *Filters the results to only those optimization jobs that were created before the - * specified time.
+ *Filters the results to only those optimization jobs that were created before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *Filters the results to only those optimization jobs that were updated after the - * specified time.
+ *Filters the results to only those optimization jobs that were updated after the specified time.
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *Filters the results to only those optimization jobs that were updated before the - * specified time.
+ *Filters the results to only those optimization jobs that were updated before the specified time.
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *Filters the results to only those optimization jobs that apply the specified
- * optimization techniques. You can specify either Quantization or
- * Compilation.
Filters the results to only those optimization jobs that apply the specified optimization techniques. You can specify either Quantization or Compilation.
Filters the results to only those optimization jobs with a name that contains the - * specified string.
+ *Filters the results to only those optimization jobs with a name that contains the specified string.
* @public */ NameContains?: string | undefined; @@ -4925,16 +4596,13 @@ export interface ListOptimizationJobsRequest { StatusEquals?: OptimizationJobStatus | undefined; /** - *The field by which to sort the optimization jobs in the response. The default is
- * CreationTime
- *
The field by which to sort the optimization jobs in the response. The default is CreationTime
The sort order for results. The default is Ascending
- *
The sort order for results. The default is Ascending
A list of optimization jobs and their properties that matches any of the filters you - * specified in the request.
+ *A list of optimization jobs and their properties that matches any of the filters you specified in the request.
* @public */ OptimizationJobSummaries: OptimizationJobSummary[] | undefined; /** - *The token to use in a subsequent request to get the next set of results following a - * truncated response.
+ *The token to use in a subsequent request to get the next set of results following a truncated response.
* @public */ NextToken?: string | undefined; @@ -5024,19 +4690,13 @@ export interface ListOptimizationJobsResponse { */ export interface ListPartnerAppsRequest { /** - *This parameter defines the maximum number of results that can be returned in a single
- * response. The MaxResults parameter is an upper bound, not a target. If there are
- * more results available than the value specified, a NextToken is provided in the
- * response. The NextToken indicates that the user should get the next set of
- * results by providing this token as a part of a subsequent call. The default value for
- * MaxResults is 10.
This parameter defines the maximum number of results that can be returned in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -5089,8 +4749,7 @@ export interface ListPartnerAppsResponse { Summaries?: PartnerAppSummary[] | undefined; /** - *If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -5121,15 +4780,13 @@ export interface ListPipelineExecutionsRequest { PipelineName: string | undefined; /** - *A filter that returns the pipeline executions that were created after a specified - * time.
+ *A filter that returns the pipeline executions that were created after a specified time.
* @public */ CreatedAfter?: Date | undefined; /** - *A filter that returns the pipeline executions that were created before a specified - * time.
+ *A filter that returns the pipeline executions that were created before a specified time.
* @public */ CreatedBefore?: Date | undefined; @@ -5147,8 +4804,7 @@ export interface ListPipelineExecutionsRequest { SortOrder?: SortOrder | undefined; /** - *If the result of the previous ListPipelineExecutions request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
Contains a sorted list of pipeline execution summary objects matching the specified - * filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, - * and the status. This list can be empty.
+ *Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
* @public */ PipelineExecutionSummaries?: PipelineExecutionSummary[] | undefined; /** - *If the result of the previous ListPipelineExecutions request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
Container for the metadata for a Quality check step. For more information, see - * the topic on QualityCheck step in the Amazon SageMaker Developer Guide. - *
+ *Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
* @public */ export interface QualityCheckStepMetadata { @@ -5332,18 +4982,13 @@ export interface QualityCheckStepMetadata { CheckJobArn?: string | undefined; /** - *This flag indicates if the drift check against the previous baseline will be skipped or not.
- * If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties
- * BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics.
- * If it is set to False, the previous baseline of the configured check type must also be available.
- * These can be accessed through the BaselineUsedForDriftCheckConstraints and
- * BaselineUsedForDriftCheckStatistics properties.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics properties.
The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, - * and a list of output parameters.
+ *The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
* @public */ Callback?: CallbackStepMetadata | undefined; /** - *The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of - * output parameters.
+ *The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
* @public */ Lambda?: LambdaStepMetadata | undefined; @@ -5465,68 +5108,13 @@ export interface PipelineExecutionStepMetadata { EMR?: EMRStepMetadata | undefined; /** - *The configurations and outcomes of the check step execution. This includes:
- *The type of the check conducted.
- *The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
- *The Amazon S3 URIs of newly calculated baseline constraints and statistics.
- *The model package group name provided.
- *The Amazon S3 URI of the violation report if violations detected.
- *The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
- *The Boolean flags indicating if the drift check is skipped.
- *If step property BaselineUsedForDriftCheck is set the same as
- * CalculatedBaseline.
The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
Container for the metadata for a Clarify check step. The configurations - * and outcomes of the check step execution. This includes:
- *The type of the check conducted,
- *The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
- *The Amazon S3 URIs of newly calculated baseline constraints and statistics.
- *The model package group name provided.
- *The Amazon S3 URI of the violation report if violations detected.
- *The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
- *The boolean flags indicating if the drift check is skipped.
- *If step property BaselineUsedForDriftCheck is set the same as
- * CalculatedBaseline.
Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
The ARN from an execution of the current pipeline from which - * results are reused for this step.
+ *The ARN from an execution of the current pipeline from which results are reused for this step.
* @public */ SelectiveExecutionResult?: SelectiveExecutionResult | undefined; @@ -5664,17 +5251,13 @@ export interface PipelineExecutionStep { */ export interface ListPipelineExecutionStepsResponse { /** - *A list of PipeLineExecutionStep objects. Each
- * PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus,
- * and Metadata. Metadata is an object with properties for each job that contains relevant
- * information about the job created by the step.
A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
If the result of the previous ListPipelineExecutionSteps request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated,
- * the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
The name of the parameter to assign a value to. This - * parameter name must match a named parameter in the - * pipeline definition.
+ *The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
* @public */ Name: string | undefined; @@ -5735,8 +5315,7 @@ export interface ListPipelineParametersForExecutionResponse { PipelineParameters?: Parameter[] | undefined; /** - *If the result of the previous ListPipelineParametersForExecution request was truncated,
- * the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
A filter that returns the pipelines that were created after a specified - * time.
+ *A filter that returns the pipelines that were created after a specified time.
* @public */ CreatedAfter?: Date | undefined; /** - *A filter that returns the pipelines that were created before a specified - * time.
+ *A filter that returns the pipelines that were created before a specified time.
* @public */ CreatedBefore?: Date | undefined; @@ -5793,8 +5370,7 @@ export interface ListPipelinesRequest { SortOrder?: SortOrder | undefined; /** - *If the result of the previous ListPipelines request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
Contains a sorted list of PipelineSummary objects matching the specified
- * filters. Each PipelineSummary consists of PipelineArn, PipelineName,
- * ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and
- * RoleArn. This list can be empty.
Contains a sorted list of PipelineSummary objects matching the specified filters. Each PipelineSummary consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
If the result of the previous ListPipelines request was truncated,
- * the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
A string in the processing job name. This filter returns only processing jobs whose - * name contains the specified string.
+ *A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
* @public */ NameContains?: string | undefined; @@ -5935,9 +5506,7 @@ export interface ListProcessingJobsRequest { SortOrder?: SortOrder | undefined; /** - *If the result of the previous ListProcessingJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of processing
- * jobs, use the token in the next request.
If the result of the previous ListProcessingJobs request was truncated, the response includes a NextToken. To retrieve the next set of processing jobs, use the token in the next request.
A string, up to one KB in size, that contains the reason a processing job failed, if - * it failed.
+ *A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
* @public */ FailureReason?: string | undefined; /** - *An optional string, up to one KB in size, that contains metadata from the processing - * container when the processing job exits.
+ *An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
* @public */ ExitMessage?: string | undefined; @@ -6010,15 +5577,13 @@ export interface ProcessingJobSummary { */ export interface ListProcessingJobsResponse { /** - *An array of ProcessingJobSummary objects, each listing a processing
- * job.
An array of ProcessingJobSummary objects, each listing a processing job.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of - * processing jobs, use it in the subsequent request.
+ *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -6057,15 +5622,13 @@ export type ProjectSortOrder = (typeof ProjectSortOrder)[keyof typeof ProjectSor */ export interface ListProjectsInput { /** - *A filter that returns the projects that were created after a specified - * time.
+ *A filter that returns the projects that were created after a specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns the projects that were created before a specified - * time.
+ *A filter that returns the projects that were created before a specified time.
* @public */ CreationTimeBefore?: Date | undefined; @@ -6077,15 +5640,13 @@ export interface ListProjectsInput { MaxResults?: number | undefined; /** - *A filter that returns the projects whose name contains a specified - * string.
+ *A filter that returns the projects whose name contains a specified string.
* @public */ NameContains?: string | undefined; /** - *If the result of the previous ListProjects request was truncated,
- * the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListProjects request was truncated, the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of model
- * compilation jobs, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
A string that partially matches one or more ResourceCatalogs names.
- * Filters ResourceCatalog by name.
A string that partially matches one or more ResourceCatalogs names. Filters ResourceCatalog by name.
Use this parameter to search for ResourceCatalogs created after a
- * specific date and time.
Use this parameter to search for ResourceCatalogs created after a specific date and time.
Use this parameter to search for ResourceCatalogs created before a
- * specific date and time.
Use this parameter to search for ResourceCatalogs created before a specific date and time.
A resource catalog containing all of the resources of a specific resource type within
- * a resource owner account. For an example on sharing the Amazon SageMaker Feature Store
- * DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
- *
A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; /** - *This parameter defines the maximum number of results that can be return in a single
- * response. The MaxResults parameter is an upper bound, not a target. If there are
- * more results available than the value specified, a NextToken is provided in the
- * response. The NextToken indicates that the user should get the next set of
- * results by providing this token as a part of a subsequent call. The default value for
- * MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
The parameter by which to sort the results. The default is
- * CreationTime.
The parameter by which to sort the results. The default is CreationTime.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -6478,8 +6023,7 @@ export interface ListSpacesResponse { */ export interface ListStageDevicesRequest { /** - *The response from the last list when returning a list large enough to neeed - * tokening.
+ *The response from the last list when returning a list large enough to neeed tokening.
* @public */ NextToken?: string | undefined; @@ -6547,60 +6091,49 @@ export type StudioLifecycleConfigSortKey = */ export interface ListStudioLifecycleConfigsRequest { /** - *The total number of items to return in the response. If the total number of items
- * available is more than the value specified, a NextToken is provided in the
- * response. To resume pagination, provide the NextToken value in the as part of a
- * subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle - * Configurations, the call returns a token for getting the next set of Lifecycle - * Configurations.
+ *If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
* @public */ NextToken?: string | undefined; /** - *A string in the Lifecycle Configuration name. This filter returns only Lifecycle - * Configurations whose name contains the specified string.
+ *A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *A parameter to search for the App Type to which the Lifecycle Configuration is - * attached.
+ *A parameter to search for the App Type to which the Lifecycle Configuration is attached.
* @public */ AppTypeEquals?: StudioLifecycleConfigAppType | undefined; /** - *A filter that returns only Lifecycle Configurations created on or before the specified - * time.
+ *A filter that returns only Lifecycle Configurations created on or before the specified time.
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only Lifecycle Configurations created on or after the specified - * time.
+ *A filter that returns only Lifecycle Configurations created on or after the specified time.
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only Lifecycle Configurations modified before the specified - * time.
+ *A filter that returns only Lifecycle Configurations modified before the specified time.
* @public */ ModifiedTimeBefore?: Date | undefined; /** - *A filter that returns only Lifecycle Configurations modified after the specified - * time.
+ *A filter that returns only Lifecycle Configurations modified after the specified time.
* @public */ ModifiedTimeAfter?: Date | undefined; @@ -6642,8 +6175,7 @@ export interface StudioLifecycleConfigDetails { CreationTime?: Date | undefined; /** - *This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle - * Configurations are immutable.
+ *This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.
* @public */ LastModifiedTime?: Date | undefined; @@ -6660,8 +6192,7 @@ export interface StudioLifecycleConfigDetails { */ export interface ListStudioLifecycleConfigsResponse { /** - *If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -6678,16 +6209,13 @@ export interface ListStudioLifecycleConfigsResponse { */ export interface ListSubscribedWorkteamsRequest { /** - *A string in the work team name. This filter returns only work teams whose name - * contains the specified string.
+ *A string in the work team name. This filter returns only work teams whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *If the result of the previous ListSubscribedWorkteams request was
- * truncated, the response includes a NextToken. To retrieve the next set of
- * labeling jobs, use the token in the next request.
If the result of the previous ListSubscribedWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of - * work teams, use it in the subsequent request.
+ *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -6722,16 +6249,13 @@ export interface ListSubscribedWorkteamsResponse { */ export interface ListTagsInput { /** - *The Amazon Resource Name (ARN) of the resource whose tags you want to - * retrieve.
+ *The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
* @public */ ResourceArn: string | undefined; /** - * If the response to the previous ListTags request is truncated, SageMaker
- * returns this token. To retrieve the next set of tags, use it in the subsequent request.
- *
If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this - * token in your subsequent request to fetch next set of tokens.
+ *If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
* @public */ NextToken?: string | undefined; @@ -6766,9 +6289,7 @@ export interface ListTagsOutput { */ export interface ListTrainingJobsRequest { /** - *If the result of the previous ListTrainingJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of training
- * jobs, use the token in the next request.
If the result of the previous ListTrainingJobs request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
A filter that returns only training jobs created after the specified time - * (timestamp).
+ *A filter that returns only training jobs created after the specified time (timestamp).
* @public */ CreationTimeAfter?: Date | undefined; /** - *A filter that returns only training jobs created before the specified time - * (timestamp).
+ *A filter that returns only training jobs created before the specified time (timestamp).
* @public */ CreationTimeBefore?: Date | undefined; /** - *A filter that returns only training jobs modified after the specified time - * (timestamp).
+ *A filter that returns only training jobs modified after the specified time (timestamp).
* @public */ LastModifiedTimeAfter?: Date | undefined; /** - *A filter that returns only training jobs modified before the specified time - * (timestamp).
+ *A filter that returns only training jobs modified before the specified time (timestamp).
* @public */ LastModifiedTimeBefore?: Date | undefined; /** - *A string in the training job name. This filter returns only training jobs whose - * name contains the specified string.
+ *A string in the training job name. This filter returns only training jobs whose name contains the specified string.
* @public */ NameContains?: string | undefined; @@ -6839,10 +6355,7 @@ export interface ListTrainingJobsRequest { WarmPoolStatusEquals?: WarmPoolResourceStatus | undefined; /** - *The Amazon Resource Name (ARN); of the training plan to filter training jobs by. For more information
- * about reserving GPU capacity for your SageMaker training jobs using Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
The Amazon Resource Name (ARN); of the training plan to filter training jobs by. For more information about reserving GPU capacity for your SageMaker training jobs using Amazon SageMaker Training Plan, see CreateTrainingPlan .
A timestamp that shows when the training job ended. This field is set only if the
- * training job has one of the terminal statuses (Completed,
- * Failed, or Stopped).
A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed, Failed, or Stopped).
The Amazon Resource Name (ARN); of the training plan associated with this training job.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
The Amazon Resource Name (ARN); of the training plan associated with this training job.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
An array of TrainingJobSummary objects, each listing a training
- * job.
An array of TrainingJobSummary objects, each listing a training job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of - * training jobs, use it in the subsequent request.
+ *If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -6960,9 +6465,7 @@ export interface ListTrainingJobsForHyperParameterTuningJobRequest { HyperParameterTuningJobName: string | undefined; /** - *If the result of the previous ListTrainingJobsForHyperParameterTuningJob
- * request was truncated, the response includes a NextToken. To retrieve the
- * next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training
- * jobs that did not return an objective metric are not listed.
The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.
A list of TrainingJobSummary objects that
- * describe
- * the training jobs that the
- * ListTrainingJobsForHyperParameterTuningJob request returned.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob request returned.
If the result of this ListTrainingJobsForHyperParameterTuningJob request
- * was truncated, the response includes a NextToken. To retrieve the next set
- * of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
A filter to apply when listing or searching for training plans.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
A filter to apply when listing or searching for training plans.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
Details of the training plan.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
Details of the training plan.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The current status of the training plan (e.g., Pending, Active, Expired). To see the
- * complete list of status values available for a training plan, refer to the
- * Status attribute within the
- * TrainingPlanSummary
- * object.
The current status of the training plan (e.g., Pending, Active, Expired). To see the complete list of status values available for a training plan, refer to the Status attribute within the TrainingPlanSummary object.
A message providing additional information about the current status of the training - * plan.
+ *A message providing additional information about the current status of the training plan.
* @public */ StatusMessage?: string | undefined; @@ -7172,8 +6655,7 @@ export interface TrainingPlanSummary { DurationHours?: number | undefined; /** - *The additional minutes beyond whole hours in the total duration for this training - * plan.
+ *The additional minutes beyond whole hours in the total duration for this training plan.
* @public */ DurationMinutes?: number | undefined; @@ -7221,26 +6703,13 @@ export interface TrainingPlanSummary { InUseInstanceCount?: number | undefined; /** - *The target resources (e.g., training jobs, HyperPod clusters) that can use this training - * plan.
- *Training plans are specific to their target resource.
- *A training plan designed for SageMaker training jobs can only be used to schedule and - * run training jobs.
- *A training plan for HyperPod clusters can be used exclusively to provide - * compute resources to a cluster's instance group.
- *The target resources (e.g., training jobs, HyperPod clusters) that can use this training plan.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
A list of reserved capacities associated with this training plan, including details such - * as instance types, counts, and availability zones.
+ *A list of reserved capacities associated with this training plan, including details such as instance types, counts, and availability zones.
* @public */ ReservedCapacitySummaries?: ReservedCapacitySummary[] | undefined; @@ -7292,8 +6761,7 @@ export interface ListTransformJobsRequest { LastModifiedTimeBefore?: Date | undefined; /** - *A string in the transform job name. This filter returns only transform jobs whose name - * contains the specified string.
+ *A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
* @public */ NameContains?: string | undefined; @@ -7317,9 +6785,7 @@ export interface ListTransformJobsRequest { SortOrder?: SortOrder | undefined; /** - *If the result of the previous ListTransformJobs request was truncated,
- * the response includes a NextToken. To retrieve the next set of transform
- * jobs, use the token in the next request.
If the result of the previous ListTransformJobs request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.
Provides a
- * summary
- * of a transform job. Multiple TransformJobSummary objects are returned as a
- * list after in response to a ListTransformJobs call.
Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.
Indicates when the transform - * job - * ends on compute instances. For successful jobs and stopped jobs, this - * is the exact time - * recorded - * after the results are uploaded. For failed jobs, this is when Amazon SageMaker - * detected that the job failed.
+ *Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
* @public */ TransformEndTime?: Date | undefined; @@ -7382,9 +6839,7 @@ export interface TransformJobSummary { TransformJobStatus: TransformJobStatus | undefined; /** - *If the transform job failed, - * the - * reason it failed.
+ *If the transform job failed, the reason it failed.
* @public */ FailureReason?: string | undefined; @@ -7395,16 +6850,13 @@ export interface TransformJobSummary { */ export interface ListTransformJobsResponse { /** - *An array of
- * TransformJobSummary
- * objects.
An array of TransformJobSummary objects.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of - * transform jobs, use it in the next request.
+ *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
* @public */ NextToken?: string | undefined; @@ -7429,25 +6881,19 @@ export type SortTrialComponentsBy = (typeof SortTrialComponentsBy)[keyof typeof */ export interface ListTrialComponentsRequest { /** - *A filter that returns only components that are part of the specified experiment. If you
- * specify ExperimentName, you can't filter by SourceArn or
- * TrialName.
A filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can't filter by SourceArn or TrialName.
A filter that returns only components that are part of the specified trial. If you specify
- * TrialName, you can't filter by ExperimentName or
- * SourceArn.
A filter that returns only components that are part of the specified trial. If you specify TrialName, you can't filter by ExperimentName or SourceArn.
A filter that returns only components that have the specified source Amazon Resource Name (ARN).
- * If you specify SourceArn, you can't filter by ExperimentName
- * or TrialName.
A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn, you can't filter by ExperimentName or TrialName.
The maximum number of components to return in the response. The default value is - * 10.
+ *The maximum number of components to return in the response. The default value is 10.
* @public */ MaxResults?: number | undefined; /** - *If the previous call to ListTrialComponents didn't return the full set of
- * components, the call returns a token for getting the next set of components.
If the previous call to ListTrialComponents didn't return the full set of components, the call returns a token for getting the next set of components.
A summary of the properties of a trial component. To get all the properties, call the
- * DescribeTrialComponent API and provide the
- * TrialComponentName.
A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.
The name of the component as displayed. If DisplayName isn't specified,
- * TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
- *InProgress
- *Completed
- *Failed
- *The status of the component. States include:
InProgress
Completed
Failed
A filter that returns only trials that are associated with the specified trial - * component.
+ *A filter that returns only trials that are associated with the specified trial component.
* @public */ TrialComponentName?: string | undefined; @@ -7656,16 +7085,14 @@ export interface ListTrialsRequest { MaxResults?: number | undefined; /** - *If the previous call to ListTrials didn't return the full set of trials, the
- * call returns a token for getting the next set of trials.
If the previous call to ListTrials didn't return the full set of trials, the call returns a token for getting the next set of trials.
A summary of the properties of a trial. To get the complete set of properties, call the
- * DescribeTrial API and provide the TrialName.
A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.
The name of the trial as displayed. If DisplayName isn't specified,
- * TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; /** - *This parameter defines the maximum number of results that can be return in a single
- * response. The MaxResults parameter is an upper bound, not a target. If there are
- * more results available than the value specified, a NextToken is provided in the
- * response. The NextToken indicates that the user should get the next set of
- * results by providing this token as a part of a subsequent call. The default value for
- * MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next - * request to receive the next set of results.
+ *If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
* @public */ NextToken?: string | undefined; @@ -7937,16 +7356,13 @@ export interface ListWorkteamsRequest { SortOrder?: SortOrder | undefined; /** - *A string in the work team's name. This filter returns only work teams whose name - * contains the specified string.
+ *A string in the work team's name. This filter returns only work teams whose name contains the specified string.
* @public */ NameContains?: string | undefined; /** - *If the result of the previous ListWorkteams request was truncated, the
- * response includes a NextToken. To retrieve the next set of labeling jobs,
- * use the token in the next request.
If the result of the previous ListWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of - * work teams, use it in the subsequent request.
+ *If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
* @public */ NextToken?: string | undefined; @@ -8006,17 +7421,13 @@ export interface Model { InferenceExecutionConfig?: InferenceExecutionConfig | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that you specified for the - * model.
+ *The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
* @public */ ExecutionRoleArn?: string | undefined; /** - *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources - * have access to. You can control access to and from your resources by configuring a VPC. - * For more information, see Give SageMaker Access to - * Resources in your Amazon VPC.
+ *Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
* @public */ VpcConfig?: VpcConfig | undefined; @@ -8034,16 +7445,13 @@ export interface Model { ModelArn?: string | undefined; /** - *Isolates the model container. No inbound or outbound network calls can be made to or - * from the model container.
+ *Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
* @public */ EnableNetworkIsolation?: boolean | undefined; /** - *A list of key-value pairs associated with the model. For more information, see - * Tagging Amazon Web Services - * resources in the Amazon Web Services General Reference Guide.
+ *A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -8085,26 +7493,7 @@ export interface ModelCard { Content?: string | undefined; /** - *The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -8135,8 +7523,7 @@ export interface ModelCard { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -8160,8 +7547,7 @@ export interface ModelCard { RiskRating?: string | undefined; /** - *The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry. - *
+ *The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
* @public */ ModelPackageGroupName?: string | undefined; @@ -8204,8 +7590,7 @@ export interface ModelDashboardEndpoint { } /** - *A batch transform job. For information about SageMaker batch transform, see Use Batch - * Transform.
+ *A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
* @public */ export interface TransformJob { @@ -8222,32 +7607,7 @@ export interface TransformJob { TransformJobArn?: string | undefined; /** - *The status of the transform job.
- *Transform job statuses are:
- *
- * InProgress - The job is in progress.
- * Completed - The job has completed.
- * Failed - The transform job has failed. To see the reason for the failure,
- * see the FailureReason field in the response to a
- * DescribeTransformJob call.
- * Stopping - The transform job is stopping.
- * Stopped - The transform job has stopped.
The status of the transform job.
Transform job statuses are:
InProgress - The job is in progress.
Completed - The job has completed.
Failed - The transform job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTransformJob call.
Stopping - The transform job is stopping.
Stopped - The transform job has stopped.
The maximum number of parallel requests that can be sent to each instance in a transform
- * job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the
- * optional execution-parameters to determine the settings for your chosen algorithm. If the
- * execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms,
- * you don't need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.
Configures the timeout and maximum number of retries for processing a transform job - * invocation.
+ *Configures the timeout and maximum number of retries for processing a transform job invocation.
* @public */ ModelClientConfig?: ModelClientConfig | undefined; /** - *The maximum allowed size of the payload, in MB. A payload is the data portion of a record
- * (without metadata). The value in MaxPayloadInMB must be greater than, or equal
- * to, the size of a single record. To estimate the size of a record in MB, divide the size of
- * your dataset by the number of records. To ensure that the records fit within the maximum
- * payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases
- * where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding,
- * set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in
- * algorithms do not support HTTP chunked encoding.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
Specifies the number of records to include in a mini-batch for an HTTP inference request. - * A record is a single unit of input data that inference can be made on. For example, a single - * line in a CSV file is a record.
+ *Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
* @public */ BatchStrategy?: BatchStrategy | undefined; /** - *The environment variables to set in the Docker container. We support up to 16 key and - * values entries in the map.
+ *The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
* @public */ Environment?: RecordDescribes the input source of a transform job and the way the transform job consumes - * it.
+ *Describes the input source of a transform job and the way the transform job consumes it.
* @public */ TransformInput?: TransformInput | undefined; @@ -8329,8 +7673,7 @@ export interface TransformJob { DataCaptureConfig?: BatchDataCaptureConfig | undefined; /** - *Describes the resources, including ML instance types and ML instance count, to use for - * transform job.
+ *Describes the resources, including ML instance types and ML instance count, to use for transform job.
* @public */ TransformResources?: TransformResources | undefined; @@ -8342,22 +7685,19 @@ export interface TransformJob { CreationTime?: Date | undefined; /** - *Indicates when the transform job starts on ML instances. You are billed for the time
- * interval between this time and the value of TransformEndTime.
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are
- * billed for the time interval between this time and the value of
- * TransformStartTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
The Amazon Resource Name (ARN) of the labeling job that created the transform job.
+ *The Amazon Resource Name (ARN) of the labeling job that created the transform job.
* @public */ LabelingJobArn?: string | undefined; @@ -8369,37 +7709,13 @@ export interface TransformJob { AutoMLJobArn?: string | undefined; /** - *The data structure used to specify the data to be used for inference in a batch - * transform job and to associate the data that is relevant to the prediction results in - * the output. The input filter provided allows you to exclude input data that is not - * needed for inference in a batch transform job. The output filter provided allows you to - * include input data relevant to interpreting the predictions in the output from the job. - * For more information, see Associate Prediction - * Results with their Corresponding Input Records.
+ *The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
* @public */ DataProcessing?: DataProcessing | undefined; /** - *Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -8453,8 +7769,7 @@ export interface ModelDashboardModelCard { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -8466,8 +7781,7 @@ export interface ModelDashboardModelCard { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -8479,8 +7793,7 @@ export interface ModelDashboardModelCard { Tags?: Tag[] | undefined; /** - *For models created in SageMaker, this is the model ARN. For models created - * outside of SageMaker, this is a user-customized string.
+ *For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
* @public */ ModelId?: string | undefined; @@ -8588,8 +7901,7 @@ export interface ModelDashboardModel { Endpoints?: ModelDashboardEndpoint[] | undefined; /** - *A batch transform job. For information about SageMaker batch transform, see Use Batch - * Transform.
+ *A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
* @public */ LastBatchTransformJob?: TransformJob | undefined; @@ -8608,35 +7920,12 @@ export interface ModelDashboardModel { } /** - *A container for your trained model that can be deployed for SageMaker inference. This can - * include inference code, artifacts, and metadata. The model package type can be one of - * the following.
- *Versioned model: A part of a model package group in Model Registry.
- *Unversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
- *For more information, see
- * CreateModelPackage
- * .
A container for your trained model that can be deployed for SageMaker inference. This can include inference code, artifacts, and metadata. The model package type can be one of the following.
Versioned model: A part of a model package group in Model Registry.
Unversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
For more information, see CreateModelPackage .
The name of the model package. The name can be as follows:
- *For a versioned model, the name is automatically generated by SageMaker Model Registry and
- * follows the format
- * 'ModelPackageGroupName/ModelPackageVersion'.
For an unversioned model, you must provide the name.
- *The name of the model package. The name can be as follows:
For a versioned model, the name is automatically generated by SageMaker Model Registry and follows the format 'ModelPackageGroupName/ModelPackageVersion'.
For an unversioned model, you must provide the name.
Specifies batch transform jobs that SageMaker runs to validate your model - * package.
+ *Specifies batch transform jobs that SageMaker runs to validate your model package.
* @public */ ValidationSpecification?: ModelPackageValidationSpecification | undefined; /** - *The status of the model package. This can be one of the following values.
- *
- * PENDING - The model package is pending being created.
- * IN_PROGRESS - The model package is in the process of being
- * created.
- * COMPLETED - The model package was successfully created.
- * FAILED - The model package failed.
- * DELETING - The model package is in the process of being
- * deleted.
The status of the model package. This can be one of the following values.
PENDING - The model package is pending being created.
IN_PROGRESS - The model package is in the process of being created.
COMPLETED - The model package was successfully created.
FAILED - The model package failed.
DELETING - The model package is in the process of being deleted.
Whether the model package is to be certified to be listed on Amazon Web Services - * Marketplace. For information about listing model packages on Amazon Web Services - * Marketplace, see List Your Algorithm or Model - * Package on Amazon Web Services Marketplace.
+ *Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
* @public */ CertifyForMarketplace?: boolean | undefined; /** - *The approval status of the model. This can be one of the following values.
- *
- * APPROVED - The model is approved
- * REJECTED - The model is rejected.
- * PENDING_MANUAL_APPROVAL - The model is waiting for manual
- * approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, or project.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
* @public */ CreatedBy?: UserContext | undefined; @@ -8782,8 +8027,7 @@ export interface ModelPackage { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, or project.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -8795,22 +8039,19 @@ export interface ModelPackage { ApprovalDescription?: string | undefined; /** - *The machine learning domain of your model package and its components. Common machine - * learning domains include computer vision and natural language processing.
+ *The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
* @public */ Domain?: string | undefined; /** - *The machine learning task your model package accomplishes. Common machine learning - * tasks include object detection and image classification.
+ *The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
* @public */ Task?: string | undefined; /** - *The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a - * single gzip compressed tar archive (.tar.gz suffix).
+ *The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
* @public */ SamplePayloadUrl?: string | undefined; @@ -8828,23 +8069,13 @@ export interface ModelPackage { SourceUri?: string | undefined; /** - *An optional Key Management Service key to encrypt, decrypt, and re-encrypt model - * package information for regulated workloads with highly sensitive data.
+ *An optional Key Management Service key to encrypt, decrypt, and re-encrypt model package information for regulated workloads with highly sensitive data.
* @public */ SecurityConfig?: ModelPackageSecurityConfig | undefined; /** - *The model card associated with the model package. Since
- * ModelPackageModelCard is tied to a model package, it is a specific
- * usage of a model card and its schema is simplified compared to the schema of
- * ModelCard. The ModelPackageModelCard schema does not
- * include model_package_details, and model_overview is composed
- * of the model_creator and model_artifact properties. For more
- * information about the model package model card schema, see Model
- * package model card schema. For more information about the model card
- * associated with the model package, see View the Details of a Model
- * Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
+ *A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -8869,8 +8099,7 @@ export interface ModelPackage { CustomerMetadataProperties?: RecordRepresents the drift check baselines that can be used when the model monitor is set - * using the model package.
+ *Represents the drift check baselines that can be used when the model monitor is set using the model package.
* @public */ DriftCheckBaselines?: DriftCheckBaselines | undefined; @@ -8912,49 +8141,19 @@ export interface ModelPackageGroup { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; /** - *The status of the model group. This can be one of the following values.
- *
- * PENDING - The model group is pending being created.
- * IN_PROGRESS - The model group is in the process of being
- * created.
- * COMPLETED - The model group was successfully created.
- * FAILED - The model group failed.
- * DELETING - The model group is in the process of being
- * deleted.
- * DELETE_FAILED - SageMaker failed to delete the model group.
The status of the model group. This can be one of the following values.
PENDING - The model group is pending being created.
IN_PROGRESS - The model group is in the process of being created.
COMPLETED - The model group was successfully created.
FAILED - The model group failed.
DELETING - The model group is in the process of being deleted.
DELETE_FAILED - SageMaker failed to delete the model group.
A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General - * Reference Guide.
+ *A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
* @public */ Tags?: Tag[] | undefined; @@ -8976,39 +8175,18 @@ export const ModelVariantAction = { export type ModelVariantAction = (typeof ModelVariantAction)[keyof typeof ModelVariantAction]; /** - *A list of nested Filter objects. A resource must - * satisfy the conditions of all filters to be included in the results returned from the Search - * API.
- *For example, to filter on a training job's InputDataConfig property with a
- * specific channel name and S3Uri prefix, define the following filters:
- * '\{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"\}',
- *
- * '\{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains",
- * "Value":"mybucket/catdata"\}'
- *
A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job's InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:
'\{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"\}',
'\{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"\}'
The name of the property to use in the nested filters. The value must match a listed
- * property name, such as InputDataConfig.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.
A list of filters. Each filter acts on a property. Filters must contain at least one
- * Filters value. For example, a NestedFilters call might include a
- * filter on the PropertyName parameter of the InputDataConfig
- * property: InputDataConfig.DataSource.S3DataSource.S3Uri.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a NestedFilters call might include a filter on the PropertyName parameter of the InputDataConfig property: InputDataConfig.DataSource.S3DataSource.S3Uri.
Time to live duration, where the record is hard deleted after the expiration time is
- * reached; ExpiresAt = EventTime + TtlDuration. For
- * information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
The trial that a trial component is associated with and the experiment the trial is part - * of. A component might not be associated with a trial. A component can be associated with - * multiple trials.
+ *The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
* @public */ export interface Parent { @@ -9108,15 +8282,13 @@ export interface Pipeline { LastRunTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -9194,15 +8366,13 @@ export interface PipelineExecution { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -9227,9 +8397,7 @@ export interface PipelineExecution { } /** - *An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more - * information, see Process Data and Evaluate - * Models.
+ *An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
* @public */ export interface ProcessingJob { @@ -9252,16 +8420,13 @@ export interface ProcessingJob { ProcessingJobName?: string | undefined; /** - *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a - * processing job. In distributed training, you specify more than one instance.
+ *Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
* @public */ ProcessingResources?: ProcessingResources | undefined; /** - *Configures conditions under which the processing job should be stopped, such as how - * long the processing job has been running. After the condition is met, the processing job - * is stopped.
+ *Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
* @public */ StoppingCondition?: ProcessingStoppingCondition | undefined; @@ -9279,9 +8444,7 @@ export interface ProcessingJob { Environment?: RecordNetworking options for a job, such as network traffic encryption between containers, - * whether to allow inbound and outbound network calls to and from containers, and the VPC - * subnets and security groups to use for VPC-enabled jobs.
+ *Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
* @public */ NetworkConfig?: NetworkConfig | undefined; @@ -9293,25 +8456,7 @@ export interface ProcessingJob { RoleArn?: string | undefined; /** - *Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -9329,15 +8474,13 @@ export interface ProcessingJob { ProcessingJobStatus?: ProcessingJobStatus | undefined; /** - *A string, up to one KB in size, that contains metadata from the processing container - * when the processing job exits.
+ *A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
* @public */ ExitMessage?: string | undefined; /** - *A string, up to one KB in size, that contains the reason a processing job failed, if - * it failed.
+ *A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
* @public */ FailureReason?: string | undefined; @@ -9367,15 +8510,13 @@ export interface ProcessingJob { CreationTime?: Date | undefined; /** - *The ARN of a monitoring schedule for an endpoint associated with this processing - * job.
+ *The ARN of a monitoring schedule for an endpoint associated with this processing job.
* @public */ MonitoringScheduleArn?: string | undefined; /** - *The Amazon Resource Name (ARN) of the AutoML job associated with this processing - * job.
+ *The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
* @public */ AutoMLJobArn?: string | undefined; @@ -9387,16 +8528,14 @@ export interface ProcessingJob { TrainingJobArn?: string | undefined; /** - *An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and - * Cost Management User Guide.
+ *An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
* @public */ Tags?: Tag[] | undefined; } /** - *Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and - * storage paths.
+ *Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
* @public */ export interface ProfilerConfigForUpdate { @@ -9407,19 +8546,13 @@ export interface ProfilerConfigForUpdate { S3OutputPath?: string | undefined; /** - *A time interval for capturing system metrics in milliseconds. Available values are - * 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
+ *A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
* @public */ ProfilingIntervalInMilliseconds?: number | undefined; /** - *Configuration information for capturing framework metrics. Available key strings for different profiling options are
- * DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig.
- * The following codes are configuration structures for the ProfilingParameters parameter. To learn more about
- * how to configure the ProfilingParameters parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
- *
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Details that you specify to provision a service catalog product. For information about - * service catalog, see What is Amazon Web Services Service - * Catalog.
+ *Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
* @public */ ServiceCatalogProvisioningDetails?: ServiceCatalogProvisioningDetails | undefined; /** - *Details of a provisioned service catalog product. For information about service catalog, - * see What is Amazon Web Services Service - * Catalog.
+ *Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
* @public */ ServiceCatalogProvisionedProductDetails?: ServiceCatalogProvisionedProductDetails | undefined; @@ -9495,9 +8624,7 @@ export interface Project { CreationTime?: Date | undefined; /** - *An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -9509,8 +8636,7 @@ export interface Project { LastModifiedTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -9545,14 +8671,12 @@ export interface PutModelPackageGroupPolicyOutput { } /** - *A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the
- * QueryLineage API action.
A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the QueryLineage API action.
Filter the lineage entities connected to the StartArn by type. For example: DataSet,
- * Model, Endpoint, or ModelDeployment.
Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs.
- * If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Associations between lineage entities have a direction. This parameter determines the direction from the - * StartArn(s) that the query traverses.
+ *Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
* @public */ Direction?: Direction | undefined; /** - * Setting this value to True retrieves not only the entities of interest but also the
- * Associations and
- * lineage entities on the path. Set to False to only return lineage entities that match your query.
Setting this value to True retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False to only return lineage entities that match your query.
A set of filtering parameters that allow you to specify which entities should be returned.
- *Properties - Key-value pairs to match on the lineage entities' properties.
- *LineageTypes - A set of lineage entity types to match on. For example: TrialComponent,
- * Artifact, or Context.
CreatedBefore - Filter entities created before this date.
- *ModifiedBefore - Filter entities modified before this date.
- *ModifiedAfter - Filter entities modified after this date.
- *A set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number
- * of Associations from the StartArn entity to the matched results.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number of Associations from the StartArn entity to the matched results.
The type of the lineage entity resource. For example: DataSet, Model, Endpoint,
- * etc...
The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...
Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging - * functionality of SageMaker, see Access a training container - * through Amazon Web Services Systems Manager (SSM) for remote - * debugging.
+ *Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
* @public */ export interface RemoteDebugConfigForUpdate { @@ -9770,10 +8867,7 @@ export interface RemoteDebugConfigForUpdate { */ export interface RenderableTask { /** - *A JSON object that contains values for the variables defined in the template. It is
- * made available to the template under the substitution variable task.input.
- * For example, if you define a variable task.input.text in your template, you
- * can supply the variable in the JSON object as "text": "sample text".
A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input. For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as "text": "sample text".
A RenderableTask object containing a representative task to
- * render.
A RenderableTask object containing a representative task to render.
The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the - * template.
+ *The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
* @public */ RoleArn: string | undefined; /** - *The HumanTaskUiArn of the worker UI that you want to render. Do not
- * provide a HumanTaskUiArn if you use the UiTemplate
- * parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
+ *The HumanTaskUiArn of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the UiTemplate parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
* @public */ HumanTaskUiArn?: string | undefined; @@ -9842,19 +8931,14 @@ export interface RenderUiTemplateResponse { RenderedContent: string | undefined; /** - *A list of one or more RenderingError objects if any were encountered
- * while rendering the template. If there were no errors, the list is empty.
A list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.
Details about a reserved capacity offering for a training plan offering.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
Details about a reserved capacity offering for a training plan offering.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The number of whole hours in the total duration for this reserved capacity - * offering.
+ *The number of whole hours in the total duration for this reserved capacity offering.
* @public */ DurationHours?: number | undefined; /** - *The additional minutes beyond whole hours in the total duration for this reserved - * capacity offering.
+ *The additional minutes beyond whole hours in the total duration for this reserved capacity offering.
* @public */ DurationMinutes?: number | undefined; @@ -9904,14 +8986,12 @@ export interface ReservedCapacityOffering { } /** - *The ResourceConfig to update KeepAlivePeriodInSeconds. Other
- * fields in the ResourceConfig cannot be updated.
The ResourceConfig to update KeepAlivePeriodInSeconds. Other fields in the ResourceConfig cannot be updated.
The KeepAlivePeriodInSeconds value specified in the
- * ResourceConfig to update.
The KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.
A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than once.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
* @public */ ClientRequestToken?: string | undefined; /** - *This configuration, if specified, overrides the parallelism configuration - * of the parent pipeline.
+ *This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
* @public */ ParallelismConfiguration?: ParallelismConfiguration | undefined; @@ -9968,17 +9046,12 @@ export const SearchSortOrder = { export type SearchSortOrder = (typeof SearchSortOrder)[keyof typeof SearchSortOrder]; /** - *The list of key-value pairs used to filter your search results. If a search result - * contains a key from your list, it is included in the final search response if the value - * associated with the key in the result matches the value you specified. If the value doesn't - * match, the result is excluded from the search response. Any resources that don't have a key - * from the list that you've provided will also be included in the search response.
+ *The list of key-value pairs used to filter your search results. If a search result contains a key from your list, it is included in the final search response if the value associated with the key in the result matches the value you specified. If the value doesn't match, the result is excluded from the search response. Any resources that don't have a key from the list that you've provided will also be included in the search response.
* @public */ export interface VisibilityConditions { /** - *The key that specifies the tag that you're using to filter the search results. It must be
- * in the following format: Tags..
The key that specifies the tag that you're using to filter the search results. It must be in the following format: Tags.<key>.
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the - * training job was launched by a hyperparameter tuning job.
+ *The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
* @public */ TuningJobArn?: string | undefined; @@ -10027,144 +9099,19 @@ export interface TrainingJob { AutoMLJobArn?: string | undefined; /** - *Information about the Amazon S3 location that is configured for storing model - * artifacts.
+ *Information about the Amazon S3 location that is configured for storing model artifacts.
* @public */ ModelArtifacts?: ModelArtifacts | undefined; /** - *The status of the - * training - * job.
- *Training job statuses are:
- *
- * InProgress - The training is in progress.
- * Completed - The training job has completed.
- * Failed - The training job has failed. To see the reason for the
- * failure, see the FailureReason field in the response to a
- * DescribeTrainingJobResponse call.
- * Stopping - The training job is stopping.
- * Stopped - The training job has stopped.
For
- * more detailed information, see SecondaryStatus.
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
Provides detailed information about the state of the training job. For detailed
- * information about the secondary status of the training job, see
- * StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of - * them:
- *
- * Starting
- * - Starting the training job.
- * Downloading - An optional stage for algorithms that
- * support File training input mode. It indicates that
- * data is being downloaded to the ML storage volumes.
- * Training - Training is in progress.
- * Uploading - Training is complete and the model
- * artifacts are being uploaded to the S3 location.
- * Completed - The training job has completed.
- * Failed - The training job has failed. The reason for
- * the failure is returned in the FailureReason field of
- * DescribeTrainingJobResponse.
- * MaxRuntimeExceeded - The job stopped because it
- * exceeded the maximum allowed runtime.
- * Stopped - The training job has stopped.
- * Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
- *
- * LaunchingMLInstances
- *
- * PreparingTrainingStack
- *
- * DownloadingTrainingImage
- *
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
The Amazon Web Services Identity and Access Management (IAM) role configured for the - * training job.
+ *The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
* @public */ RoleArn?: string | undefined; /** - *An array of Channel objects that describes each data input
- * channel.
Your input must be in the same Amazon Web Services region as your training job.
+ *An array of Channel objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
* @public */ InputDataConfig?: Channel[] | undefined; /** - *The S3 path where model artifacts that you configured when creating the job are - * stored. SageMaker creates subfolders for model artifacts.
+ *The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
* @public */ OutputDataConfig?: OutputDataConfig | undefined; /** - *Resources, including ML compute instances and ML storage volumes, that are configured - * for model training.
+ *Resources, including ML compute instances and ML storage volumes, that are configured for model training.
* @public */ ResourceConfig?: ResourceConfig | undefined; /** - *A VpcConfig object that specifies the VPC that this training job has access - * to. For more information, see Protect Training Jobs by Using an Amazon - * Virtual Private Cloud.
+ *A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
* @public */ VpcConfig?: VpcConfig | undefined; /** - *Specifies a limit to how long a model training job can run. It also specifies how long - * a managed Spot training job has to complete. When the job reaches the time limit, SageMaker - * ends the training job. Use this API to cap model training costs.
- *To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays
- * job termination for 120 seconds. Algorithms can use this 120-second window to save the
- * model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Indicates the time when the training job starts on training instances. You are billed
- * for the time interval between this time and the value of TrainingEndTime.
- * The start time in CloudWatch Logs might be later than this time. The difference is due to the time
- * it takes to download the training data and to the size of the training container.
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed
- * for the time interval between the value of TrainingStartTime and this time.
- * For successful jobs and stopped jobs, this is the time after model artifacts are
- * uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last - * modified.
+ *A timestamp that indicates when the status of the training job was last modified.
* @public */ LastModifiedTime?: Date | undefined; /** - *A history of all of the secondary statuses that the training job has transitioned - * through.
+ *A history of all of the secondary statuses that the training job has transitioned through.
* @public */ SecondaryStatusTransitions?: SecondaryStatusTransition[] | undefined; /** - *A list of final metric values that are set when the training job completes. Used only - * if the training job was configured to use metrics.
+ *A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
* @public */ FinalMetricDataList?: MetricData[] | undefined; /** - *If the TrainingJob was created with network isolation, the value is set
- * to true. If network isolation is enabled, nodes can't communicate beyond
- * the VPC they run in.
If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training,
- * choose True. Encryption provides greater security for distributed training,
- * but training might take longer. How long it takes depends on the amount of communication
- * between compute instances, especially if you use a deep learning algorithm in
- * distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run - * training jobs instead of on-demand instances. For more information, see Managed Spot Training.
+ *When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
* @public */ EnableManagedSpotTraining?: boolean | undefined; /** - *Contains information about the output location for managed spot training checkpoint - * data.
+ *Contains information about the output location for managed spot training checkpoint data.
* @public */ CheckpointConfig?: CheckpointConfig | undefined; @@ -10325,34 +9243,13 @@ export interface TrainingJob { BillableTimeInSeconds?: number | undefined; /** - *Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and
- * storage paths. To learn more about
- * how to configure the DebugHookConfig parameter,
- * see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Associates a SageMaker job as a trial component with an experiment and trial. Specified when - * you call the following APIs:
- *- * CreateProcessingJob - *
- *- * CreateTrainingJob - *
- *- * CreateTransformJob - *
- *Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
* @public */ ExperimentConfig?: ExperimentConfig | undefined; @@ -10376,8 +9273,7 @@ export interface TrainingJob { DebugRuleEvaluationStatuses?: DebugRuleEvaluationStatus[] | undefined; /** - *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and - * storage paths.
+ *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
* @public */ ProfilerConfig?: ProfilerConfig | undefined; @@ -10389,16 +9285,13 @@ export interface TrainingJob { Environment?: RecordThe number of times to retry the job when the job fails due to an
- * InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services - * resources in different ways, for example, by purpose, owner, or environment. For more - * information, see Tagging Amazon Web Services Resources.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
* @public */ Tags?: Tag[] | undefined; @@ -10434,8 +9327,7 @@ export interface TrialComponentSimpleSummary { CreationTime?: Date | undefined; /** - *Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ CreatedBy?: UserContext | undefined; @@ -10459,8 +9351,7 @@ export interface Trial { TrialArn?: string | undefined; /** - *The name of the trial as displayed. If DisplayName isn't specified,
- * TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -10509,23 +9399,20 @@ export interface Trial { MetadataProperties?: MetadataProperties | undefined; /** - *The list of tags that are associated with the trial. You can use Search - * API to search on the tags.
+ *The list of tags that are associated with the trial. You can use Search API to search on the tags.
* @public */ Tags?: Tag[] | undefined; /** - *A list of the components associated with the trial. For each component, a summary of the - * component's properties is included.
+ *A list of the components associated with the trial. For each component, a summary of the component's properties is included.
* @public */ TrialComponentSummaries?: TrialComponentSimpleSummary[] | undefined; } /** - *Detailed information about the source of a trial component. Either
- * ProcessingJob or TrainingJob is returned.
Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
The properties of a trial component as returned by the Search - * API.
+ *The properties of a trial component as returned by the Search API.
* @public */ export interface TrialComponent { @@ -10567,8 +9453,7 @@ export interface TrialComponent { TrialComponentName?: string | undefined; /** - *The name of the component as displayed. If DisplayName isn't specified,
- * TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
Information about the user who created or modified an experiment, trial, trial - * component, lineage group, project, or model card.
+ *Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
* @public */ LastModifiedBy?: UserContext | undefined; @@ -10677,8 +9561,7 @@ export interface TrialComponent { Tags?: Tag[] | undefined; /** - *An array of the parents of the component. A parent is a trial the component is associated - * with and the experiment the trial is part of. A component might not have any parents.
+ *An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
* @public */ Parents?: Parent[] | undefined; @@ -10726,20 +9609,7 @@ export interface SearchRecord { Endpoint?: Endpoint | undefined; /** - *A container for your trained model that can be deployed for SageMaker inference. This can - * include inference code, artifacts, and metadata. The model package type can be one of - * the following.
- *Versioned model: A part of a model package group in Model Registry.
- *Unversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
- *For more information, see
- * CreateModelPackage
- * .
A container for your trained model that can be deployed for SageMaker inference. This can include inference code, artifacts, and metadata. The model package type can be one of the following.
Versioned model: A part of a model package group in Model Registry.
Unversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
For more information, see CreateModelPackage .
Amazon SageMaker Feature Store stores features in a collection called Feature Group. A - * Feature Group can be visualized as a table which has rows, with a unique identifier for - * each row where each column in the table is a feature. In principle, a Feature Group is - * composed of features and values per features.
+ *Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
* @public */ FeatureGroup?: FeatureGroup | undefined; @@ -10803,37 +9670,18 @@ export interface SearchRecord { } /** - *Represents the total number of matching results and indicates how accurate that count - * is.
- *The Value field provides the count, which may be exact or estimated. The
- * Relation field indicates whether it's an exact figure or a lower bound. This
- * helps understand the full scope of search results, especially when dealing with large result
- * sets.
Represents the total number of matching results and indicates how accurate that count is.
The Value field provides the count, which may be exact or estimated. The Relation field indicates whether it's an exact figure or a lower bound. This helps understand the full scope of search results, especially when dealing with large result sets.
The total number of matching results. This value may be exact or an estimate, depending on
- * the Relation field.
The total number of matching results. This value may be exact or an estimate, depending on the Relation field.
Indicates the relationship between the returned Value and the actual total
- * number of matching results. Possible values are:
- * EqualTo: The Value is the exact count of matching
- * results.
- * GreaterThanOrEqualTo: The Value is a lower bound of the
- * actual count of matching results.
Indicates the relationship between the returned Value and the actual total number of matching results. Possible values are:
EqualTo: The Value is the exact count of matching results.
GreaterThanOrEqualTo: The Value is a lower bound of the actual count of matching results.
If the result of the previous Search request was truncated, the response
- * includes a NextToken. To retrieve the next set of results, use the token in the next
- * request.
If the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
The type of instance you want to search for in the available training plan offerings. - * This field allows you to filter the search results based on the specific compute resources - * you require for your SageMaker training jobs or SageMaker HyperPod clusters. When searching for training - * plan offerings, specifying the instance type helps you find Reserved Instances that match - * your computational needs.
+ *The type of instance you want to search for in the available training plan offerings. This field allows you to filter the search results based on the specific compute resources you require for your SageMaker training jobs or SageMaker HyperPod clusters. When searching for training plan offerings, specifying the instance type helps you find Reserved Instances that match your computational needs.
* @public */ InstanceType?: ReservedCapacityInstanceType | undefined; /** - *The number of instances you want to reserve in the training plan offerings. This allows - * you to specify the quantity of compute resources needed for your SageMaker training jobs or - * SageMaker HyperPod clusters, helping you find reserved capacity offerings that match your - * requirements.
+ *The number of instances you want to reserve in the training plan offerings. This allows you to specify the quantity of compute resources needed for your SageMaker training jobs or SageMaker HyperPod clusters, helping you find reserved capacity offerings that match your requirements.
* @public */ InstanceCount?: number | undefined; /** - *A filter to search for training plan offerings with a start time after a specified - * date.
+ *A filter to search for training plan offerings with a start time after a specified date.
* @public */ StartTimeAfter?: Date | undefined; /** - *A filter to search for reserved capacity offerings with an end time before a specified - * date.
+ *A filter to search for reserved capacity offerings with an end time before a specified date.
* @public */ EndTimeBefore?: Date | undefined; @@ -10908,30 +9745,14 @@ export interface SearchTrainingPlanOfferingsRequest { DurationHours: number | undefined; /** - *The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) to search for in the - * offerings.
- *Training plans are specific to their target resource.
- *A training plan designed for SageMaker training jobs can only be used to schedule and - * run training jobs.
- *A training plan for HyperPod clusters can be used exclusively to provide - * compute resources to a cluster's instance group.
- *The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) to search for in the offerings.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
Details about a training plan offering.
- *For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using
- * Amazon SageMaker Training Plan, see
- * CreateTrainingPlan
- * .
Details about a training plan offering.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) for this training plan - * offering.
- *Training plans are specific to their target resource.
- *A training plan designed for SageMaker training jobs can only be used to schedule and - * run training jobs.
- *A training plan for HyperPod clusters can be used exclusively to provide - * compute resources to a cluster's instance group.
- *The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) for this training plan offering.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
The requested start time that the user specified when searching for the training plan - * offering.
+ *The requested start time that the user specified when searching for the training plan offering.
* @public */ RequestedStartTimeAfter?: Date | undefined; /** - *The requested end time that the user specified when searching for the training plan - * offering.
+ *The requested end time that the user specified when searching for the training plan offering.
* @public */ RequestedEndTimeBefore?: Date | undefined; @@ -10980,8 +9787,7 @@ export interface TrainingPlanOffering { DurationHours?: number | undefined; /** - *The additional minutes beyond whole hours in the total duration for this training plan - * offering.
+ *The additional minutes beyond whole hours in the total duration for this training plan offering.
* @public */ DurationMinutes?: number | undefined; @@ -10999,8 +9805,7 @@ export interface TrainingPlanOffering { CurrencyCode?: string | undefined; /** - *A list of reserved capacity offerings associated with this training plan - * offering.
+ *A list of reserved capacity offerings associated with this training plan offering.
* @public */ ReservedCapacityOfferings?: ReservedCapacityOffering[] | undefined; @@ -11034,8 +9839,7 @@ export interface SendPipelineExecutionStepFailureRequest { FailureReason?: string | undefined; /** - *A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than one time.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
* @public */ ClientRequestToken?: string | undefined; @@ -11069,8 +9873,7 @@ export interface SendPipelineExecutionStepSuccessRequest { OutputParameters?: OutputParameter[] | undefined; /** - *A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than one time.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
* @public */ ClientRequestToken?: string | undefined; @@ -11199,15 +10002,13 @@ export interface StartPipelineExecutionRequest { PipelineExecutionDescription?: string | undefined; /** - *A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than once.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
* @public */ ClientRequestToken?: string | undefined; /** - *This configuration, if specified, overrides the parallelism configuration - * of the parent pipeline for this specific run.
+ *This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
* @public */ ParallelismConfiguration?: ParallelismConfiguration | undefined; @@ -11302,51 +10103,19 @@ export interface StopInferenceExperimentRequest { Name: string | undefined; /** - *- * Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following: - *
- *
- * Promote - Promote the shadow variant to a production variant
- * Remove - Delete the variant
- * Retain - Keep the variant as it is
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote - Promote the shadow variant to a production variant
Remove - Delete the variant
Retain - Keep the variant as it is
- * An array of ModelVariantConfig objects. There is one for each variant that you want to deploy
- * after the inference experiment stops. Each ModelVariantConfig describes the infrastructure
- * configuration for deploying the corresponding variant.
- *
An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.
- * The desired state of the experiment after stopping. The possible states are the following: - *
- *
- * Completed: The experiment completed successfully
- * Cancelled: The experiment was canceled
The desired state of the experiment after stopping. The possible states are the following:
Completed: The experiment completed successfully
Cancelled: The experiment was canceled
A unique, case-sensitive identifier that you provide to ensure the idempotency of the - * operation. An idempotent operation completes no more than once.
+ *A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
* @public */ ClientRequestToken?: string | undefined; @@ -397,8 +396,7 @@ export interface UpdateClusterRequest { NodeRecovery?: ClusterNodeRecovery | undefined; /** - *Specify the names of the instance groups to delete.
- * Use a single , as the separator between multiple names.
Specify the names of the instance groups to delete. Use a single , as the separator between multiple names.
Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security - * patching.
+ *Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security patching.
* @public */ ClusterName: string | undefined; @@ -519,14 +516,7 @@ export interface UpdateCodeRepositoryInput { CodeRepositoryName: string | undefined; /** - *The configuration of the git repository, including the URL and the Amazon Resource
- * Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the
- * credentials used to access the repository. The secret must have a staging label of
- * AWSCURRENT and must be in the following format:
- * \{"username": UserName, "password":
- * Password\}
- *
The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
\{"username": UserName, "password": Password\}
Configuration of the compute allocation definition. This includes the resource sharing - * option, and the setting to preempt low priority tasks.
+ *Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
* @public */ ComputeQuotaConfig?: ComputeQuotaConfig | undefined; @@ -573,9 +562,7 @@ export interface UpdateComputeQuotaRequest { ComputeQuotaTarget?: ComputeQuotaTarget | undefined; /** - *The state of the compute allocation being described. Use to enable or disable compute - * allocation.
- *Default is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
Output configuration for storing sample data collected by the fleet.
+ *Output configuration for storing sample data collected by the fleet.
* @public */ OutputConfig: EdgeOutputConfig | undefined; /** - *Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. - * The name of the role alias generated will match this pattern: - * "SageMakerEdge-\{DeviceFleetName\}".
- *For example, if your device fleet is called "demo-fleet", the name of - * the role alias will be "SageMakerEdge-demo-fleet".
+ *Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: "SageMakerEdge-\{DeviceFleetName\}".
For example, if your device fleet is called "demo-fleet", the name of the role alias will be "SageMakerEdge-demo-fleet".
* @public */ EnableIotRoleAlias?: boolean | undefined; @@ -723,12 +706,7 @@ export interface UpdateDomainRequest { DomainSettingsForUpdate?: DomainSettingsForUpdate | undefined; /** - *The entity that creates and manages the required security groups for inter-app
- * communication in VPCOnly mode. Required when
- * CreateDomain.AppNetworkAccessType is VPCOnly and
- * DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is
- * provided. If setting up the domain for use with RStudio, this value must be set to
- * Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The VPC subnets that Studio uses for communication.
- *If removing subnets, ensure there are no apps in the InService,
- * Pending, or Deleting state.
The VPC subnets that Studio uses for communication.
If removing subnets, ensure there are no apps in the InService, Pending, or Deleting state.
Specifies the VPC used for non-EFS traffic.
- *
- * PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access.
- * VpcOnly - All Studio traffic is through the specified VPC and
- * subnets.
This configuration can only be modified if there are no apps in the
- * InService, Pending, or Deleting state. The
- * configuration cannot be updated if
- * DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already
- * set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is
- * provided as part of the same request.
Specifies the VPC used for non-EFS traffic.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access.
VpcOnly - All Studio traffic is through the specified VPC and subnets.
This configuration can only be modified if there are no apps in the InService, Pending, or Deleting state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided as part of the same request.
Indicates whether custom tag propagation is supported for the domain. Defaults to
- * DISABLED.
Indicates whether custom tag propagation is supported for the domain. Defaults to DISABLED.
Specifies a production variant property type for an Endpoint.
- *If you are updating an endpoint with the RetainAllVariantProperties
- * option of UpdateEndpointInput set to true, the
- * VariantProperty objects listed in the
- * ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the
- * endpoint.
Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties option of UpdateEndpointInput set to true, the VariantProperty objects listed in the ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
The type of variant property. The supported values are:
- *
- * DesiredInstanceCount: Overrides the existing variant instance
- * counts using the InitialInstanceCount values in the
- * ProductionVariants of CreateEndpointConfig.
- * DesiredWeight: Overrides the existing variant weights using the
- * InitialVariantWeight values in the
- * ProductionVariants of CreateEndpointConfig.
- * DataCaptureConfig: (Not currently supported.)
The type of variant property. The supported values are:
DesiredInstanceCount: Overrides the existing variant instance counts using the InitialInstanceCount values in the ProductionVariants of CreateEndpointConfig.
DesiredWeight: Overrides the existing variant weights using the InitialVariantWeight values in the ProductionVariants of CreateEndpointConfig.
DataCaptureConfig: (Not currently supported.)
When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To
- * retain the variant properties of an endpoint when updating it, set
- * RetainAllVariantProperties to true. To use the variant
- * properties specified in a new EndpointConfig call when updating an
- * endpoint, set RetainAllVariantProperties to false. The default
- * is false.
When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true. To use the variant properties specified in a new EndpointConfig call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.
When you are updating endpoint resources with RetainAllVariantProperties,
- * whose value is set to true, ExcludeRetainedVariantProperties
- * specifies the list of type VariantProperty
- * to override with the values provided by EndpointConfig. If you don't
- * specify a value for ExcludeRetainedVariantProperties, no variant properties
- * are overridden.
When you are updating endpoint resources with RetainAllVariantProperties, whose value is set to true, ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig. If you don't specify a value for ExcludeRetainedVariantProperties, no variant properties are overridden.
The deployment configuration for an endpoint, which contains the desired deployment - * strategy and rollback configurations.
+ *The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
* @public */ DeploymentConfig?: DeploymentConfig | undefined; /** - *Specifies whether to reuse the last deployment configuration. The default value is - * false (the configuration is not reused).
+ *Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
* @public */ RetainDeploymentConfig?: boolean | undefined; @@ -942,8 +865,7 @@ export interface UpdateExperimentRequest { ExperimentName: string | undefined; /** - *The name of the experiment as displayed. The name doesn't need to be unique. If
- * DisplayName isn't specified, ExperimentName is displayed.
The name of the experiment as displayed. The name doesn't need to be unique. If DisplayName isn't specified, ExperimentName is displayed.
The new throughput configuration for the feature group. You can switch between on-demand - * and provisioned modes or update the read / write capacity of provisioned feature groups. - * You can switch a feature group to on-demand only once in a 24 hour period.
+ *The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
* @public */ export interface ThroughputConfigUpdate { /** - *Target throughput mode of the feature group. Throughput update is an asynchronous
- * operation, and the outcome should be monitored by polling LastUpdateStatus
- * field in DescribeFeatureGroup response. You cannot update a feature group's
- * throughput while another update is in progress.
Target throughput mode of the feature group. Throughput update is an asynchronous operation, and the outcome should be monitored by polling LastUpdateStatus field in DescribeFeatureGroup response. You cannot update a feature group's throughput while another update is in progress.
For provisioned feature groups with online store enabled, this indicates the read - * throughput you are billed for and can consume without throttling.
+ *For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
* @public */ ProvisionedReadCapacityUnits?: number | undefined; /** - *For provisioned feature groups, this indicates the write throughput you are billed for - * and can consume without throttling.
+ *For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
* @public */ ProvisionedWriteCapacityUnits?: number | undefined; @@ -1008,9 +923,7 @@ export interface UpdateFeatureGroupRequest { FeatureGroupName: string | undefined; /** - *Updates the feature group. Updating a feature group is an asynchronous operation. When - * you get an HTTP 200 response, you've made a valid request. It takes some time after you've - * made a valid request for Feature Store to update the feature group.
+ *Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.
* @public */ FeatureAdditions?: FeatureDefinition[] | undefined; @@ -1022,9 +935,7 @@ export interface UpdateFeatureGroupRequest { OnlineStoreConfig?: OnlineStoreConfigUpdate | undefined; /** - *The new throughput configuration for the feature group. You can switch between on-demand - * and provisioned modes or update the read / write capacity of provisioned feature groups. - * You can switch a feature group to on-demand only once in a 24 hour period.
+ *The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
* @public */ ThroughputConfig?: ThroughputConfigUpdate | undefined; @@ -1046,8 +957,7 @@ export interface UpdateFeatureGroupResponse { */ export interface UpdateFeatureMetadataRequest { /** - *The name or Amazon Resource Name (ARN) of the feature group containing the feature that - * you're updating.
+ *The name or Amazon Resource Name (ARN) of the feature group containing the feature that you're updating.
* @public */ FeatureGroupName: string | undefined; @@ -1071,8 +981,7 @@ export interface UpdateFeatureMetadataRequest { ParameterAdditions?: FeatureParameter[] | undefined; /** - *A list of parameter keys that you can specify to remove parameters that describe your - * feature.
+ *A list of parameter keys that you can specify to remove parameters that describe your feature.
* @public */ ParameterRemovals?: string[] | undefined; @@ -1123,8 +1032,7 @@ export interface UpdateHubResponse { */ export interface UpdateHubContentRequest { /** - *The name of the SageMaker hub that contains the hub content you want to update. - * You can optionally use the hub ARN instead.
+ *The name of the SageMaker hub that contains the hub content you want to update. You can optionally use the hub ARN instead.
* @public */ HubName: string | undefined; @@ -1136,17 +1044,13 @@ export interface UpdateHubContentRequest { HubContentName: string | undefined; /** - *The content type of the resource that you want to update. Only specify a
- * Model or Notebook resource for this API. To
- * update a ModelReference, use the
- * UpdateHubContentReference API instead.
The content type of the resource that you want to update. Only specify a Model or Notebook resource for this API. To update a ModelReference, use the UpdateHubContentReference API instead.
The hub content version that you want to update. For example, if you have - * two versions of a resource in your hub, you can update the second version.
+ *The hub content version that you want to update. For example, if you have two versions of a resource in your hub, you can update the second version.
* @public */ HubContentVersion: string | undefined; @@ -1216,17 +1120,13 @@ export interface UpdateHubContentReferenceRequest { HubContentName: string | undefined; /** - *The content type of the resource that you want to update. Only specify a
- * ModelReference resource for this API. To update a Model
- * or Notebook resource, use the UpdateHubContent API instead.
The content type of the resource that you want to update. Only specify a ModelReference resource for this API. To update a Model or Notebook resource, use the UpdateHubContent API instead.
The minimum hub content version of the referenced model that you want to use.
- * The minimum version must be older than the latest available version of the referenced model.
- * To support all versions of a model, set the value to 1.0.0.
The minimum hub content version of the referenced model that you want to use. The minimum version must be older than the latest available version of the referenced model. To support all versions of a model, set the value to 1.0.0.
A list of properties to delete. Only the Description and
- * DisplayName properties can be deleted.
A list of properties to delete. Only the Description and DisplayName properties can be deleted.
The availability of the image version specified by the maintainer.
- *
- * NOT_PROVIDED: The maintainers did not provide a status for image version stability.
- * STABLE: The image version is stable.
- * TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
- * ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
- *
- * TRAINING: The image version is compatible with SageMaker AI training jobs.
- * INFERENCE: The image version is compatible with SageMaker AI inference jobs.
- * NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
- *
- * CPU: The image version is compatible with CPU.
- * GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Details about the resources to deploy with this inference component, including the - * model, container, and compute resources.
+ *Details about the resources to deploy with this inference component, including the model, container, and compute resources.
* @public */ Specification?: InferenceComponentSpecification | undefined; @@ -1450,8 +1306,7 @@ export interface UpdateInferenceComponentInput { RuntimeConfig?: InferenceComponentRuntimeConfig | undefined; /** - *The deployment configuration for the inference component. The configuration contains the - * desired deployment strategy and rollback settings.
+ *The deployment configuration for the inference component. The configuration contains the desired deployment strategy and rollback settings.
* @public */ DeploymentConfig?: InferenceComponentDeploymentConfig | undefined; @@ -1507,11 +1362,7 @@ export interface UpdateInferenceExperimentRequest { Name: string | undefined; /** - *
- * The duration for which the inference experiment will run. If the status of the inference experiment is
- * Created, then you can update both the start and end dates. If the status of the inference
- * experiment is Running, then you can update only the end date.
- *
The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.
- * An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure
- * configuration you want to update.
- *
An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.
- * The configuration of ShadowMode inference experiment type. Use this field to specify a
- * production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a
- * percentage of the inference requests. For the shadow variant also specify the percentage of requests that
- * Amazon SageMaker replicates.
- *
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow - * Tracking Server.
+ *The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow Tracking Server.
* @public */ ArtifactStoreUri?: string | undefined; @@ -1584,18 +1426,13 @@ export interface UpdateMlflowTrackingServerRequest { TrackingServerSize?: TrackingServerSize | undefined; /** - *Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry.
- * To enable automatic model registration, set this value to True.
- * To disable automatic model registration, set this value to False.
- * If not specified, AutomaticModelRegistration defaults to False
- *
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False
The new weekly maintenance window start day and time to update. The maintenance window day and time should be - * in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
+ *The new weekly maintenance window start day and time to update. The maintenance window day and time should be in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
* @public */ WeeklyMaintenanceWindowStart?: string | undefined; @@ -1623,33 +1460,13 @@ export interface UpdateModelCardRequest { ModelCardName: string | undefined; /** - *The updated model card content. Content must be in model card JSON schema and provided as a string.
- *When updating model card content, be sure to include the full content and not just updated content.
+ *The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
* @public */ Content?: string | undefined; /** - *The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
- *
- * Draft: The model card is a work in progress.
- * PendingReview: The model card is pending review.
- * Approved: The model card is approved.
- * Archived: The model card is archived. No more updates should be made to the model
- * card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
An array of additional Inference Specification objects to be added to the - * existing array additional Inference Specification. Total number of additional - * Inference Specifications can not exceed 15. Each additional Inference Specification - * specifies artifacts based on this model package that can be used on inference endpoints. - * Generally used with SageMaker Neo to store the compiled artifacts.
+ *An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
* @public */ AdditionalInferenceSpecificationsToAdd?: AdditionalInferenceSpecificationDefinition[] | undefined; /** - *Specifies details about inference jobs that you can run with models based on this - * model package, including the following information:
- *The Amazon ECR paths of containers that contain the inference code and model - * artifacts.
- *The instance types that the model package supports for transform jobs and - * real-time endpoints used for inference.
- *The input and output content formats that the model package supports for - * inference.
- *Specifies details about inference jobs that you can run with models based on this model package, including the following information:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
The model card associated with the model package. Since
- * ModelPackageModelCard is tied to a model package, it is a specific
- * usage of a model card and its schema is simplified compared to the schema of
- * ModelCard. The ModelPackageModelCard schema does not
- * include model_package_details, and model_overview is composed
- * of the model_creator and model_artifact properties. For more
- * information about the model package model card schema, see Model
- * package model card schema. For more information about the model card
- * associated with the model package, see View the Details of a Model
- * Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
Within EvaluationPeriod, how many execution failures will raise an
- * alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
The number of most recent monitoring executions to consider when evaluating alert - * status.
+ *The number of most recent monitoring executions to consider when evaluating alert status.
* @public */ EvaluationPeriod: number | undefined; @@ -1829,15 +1616,13 @@ export interface UpdateMonitoringAlertResponse { */ export interface UpdateMonitoringScheduleRequest { /** - *The name of the monitoring schedule. The name must be unique within an Amazon Web Services - * Region within an Amazon Web Services account.
+ *The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
* @public */ MonitoringScheduleName: string | undefined; /** - *The configuration object that specifies the monitoring schedule and defines the monitoring - * job.
+ *The configuration object that specifies the monitoring schedule and defines the monitoring job.
* @public */ MonitoringScheduleConfig: MonitoringScheduleConfig | undefined; @@ -1871,109 +1656,67 @@ export interface UpdateNotebookInstanceInput { InstanceType?: _InstanceType | undefined; /** - *The Amazon Resource Name (ARN) of the IAM role that SageMaker AI can assume to - * access the notebook instance. For more information, see SageMaker AI Roles.
- *To be able to pass this role to SageMaker AI, the caller of this API must
- * have the iam:PassRole permission.
The Amazon Resource Name (ARN) of the IAM role that SageMaker AI can assume to access the notebook instance. For more information, see SageMaker AI Roles.
To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
The name of a lifecycle configuration to associate with the notebook instance. For - * information about lifestyle configurations, see Step 2.1: (Optional) - * Customize a Notebook Instance.
+ *The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
* @public */ LifecycleConfigName?: string | undefined; /** - *Set to true to remove the notebook instance lifecycle configuration
- * currently associated with the notebook instance. This operation is idempotent. If you
- * specify a lifecycle configuration that is not associated with the notebook instance when
- * you call this method, it does not throw an error.
Set to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
The size, in GB, of the ML storage volume to attach to the notebook instance. The - * default value is 5 GB. ML storage volumes are encrypted, so SageMaker AI can't - * determine the amount of available free space on the volume. Because of this, you can - * increase the volume size when you update a notebook instance, but you can't decrease the - * volume size. If you want to decrease the size of the ML storage volume in use, create a - * new notebook instance with the desired size.
+ *The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker AI can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
* @public */ VolumeSizeInGB?: number | undefined; /** - *The Git repository to associate with the notebook instance as its default code - * repository. This can be either the name of a Git repository stored as a resource in your - * account, or the URL of a Git repository in Amazon Web Services CodeCommit - * or in any other Git repository. When you open a notebook instance, it opens in the - * directory that contains this repository. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ DefaultCodeRepository?: string | undefined; /** - *An array of up to three Git repositories to associate with the notebook instance. - * These can be either the names of Git repositories stored as resources in your account, - * or the URL of Git repositories in Amazon Web Services CodeCommit - * or in any other Git repository. These repositories are cloned at the same level as the - * default repository of your notebook instance. For more information, see Associating Git - * Repositories with SageMaker AI Notebook Instances.
+ *An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
* @public */ AdditionalCodeRepositories?: string[] | undefined; /** - *This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify a list of the EI instance types to associate with - * this notebook instance.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types to associate with this notebook instance.
* @public */ AcceleratorTypes?: NotebookInstanceAcceleratorType[] | undefined; /** - *This parameter is no longer supported. Elastic Inference (EI) is no longer - * available.
- *This parameter was used to specify a list of the EI instance types to remove from this notebook - * instance.
+ *This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types to remove from this notebook instance.
* @public */ DisassociateAcceleratorTypes?: boolean | undefined; /** - *The name or URL of the default Git repository to remove from this notebook instance. - * This operation is idempotent. If you specify a Git repository that is not associated - * with the notebook instance when you call this method, it does not throw an error.
+ *The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
* @public */ DisassociateDefaultCodeRepository?: boolean | undefined; /** - *A list of names or URLs of the default Git repositories to remove from this notebook - * instance. This operation is idempotent. If you specify a Git repository that is not - * associated with the notebook instance when you call this method, it does not throw an - * error.
+ *A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
* @public */ DisassociateAdditionalCodeRepositories?: boolean | undefined; /** - *Whether root access is enabled or disabled for users of the notebook instance. The
- * default value is Enabled.
If you set this to Disabled, users don't have root access on the
- * notebook instance, but lifecycle configuration scripts still run with root
- * permissions.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
If you set this to Disabled, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
The shell script that runs only once, when you create a notebook instance. The shell - * script must be a base64-encoded string.
+ *The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
* @public */ OnCreate?: NotebookInstanceLifecycleHook[] | undefined; /** - *The shell script that runs every time you start a notebook instance, including when - * you create the notebook instance. The shell script must be a base64-encoded - * string.
+ *The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
* @public */ OnStart?: NotebookInstanceLifecycleHook[] | undefined; @@ -2062,8 +1802,7 @@ export interface UpdatePartnerAppRequest { ClientToken?: string | undefined; /** - *Each tag consists of a key and an optional value. Tag keys must be unique per - * resource.
+ *Each tag consists of a key and an optional value. Tag keys must be unique per resource.
* @public */ Tags?: Tag[] | undefined; @@ -2103,8 +1842,7 @@ export interface UpdatePipelineRequest { PipelineDefinition?: string | undefined; /** - *The location of the pipeline definition stored in Amazon S3. If specified, - * SageMaker will retrieve the pipeline definition from this location.
+ *The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
* @public */ PipelineDefinitionS3Location?: PipelineDefinitionS3Location | undefined; @@ -2162,8 +1900,7 @@ export interface UpdatePipelineExecutionRequest { PipelineExecutionDisplayName?: string | undefined; /** - *This configuration, if specified, overrides the parallelism configuration - * of the parent pipeline for this specific run.
+ *This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
* @public */ ParallelismConfiguration?: ParallelismConfiguration | undefined; @@ -2181,9 +1918,7 @@ export interface UpdatePipelineExecutionResponse { } /** - *Details that you specify to provision a service catalog product. - * For information about service catalog, see What is Amazon Web Services Service Catalog. - *
+ *Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
* @public */ export interface ServiceCatalogProvisioningUpdateDetails { @@ -2217,22 +1952,13 @@ export interface UpdateProjectInput { ProjectDescription?: string | undefined; /** - *The product ID and provisioning artifact ID to provision a service catalog. - * The provisioning artifact ID will default to the latest provisioning artifact - * ID of the product, if you don't provide the provisioning artifact ID. For more - * information, see What is Amazon Web Services Service Catalog. - *
+ *The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
* @public */ ServiceCatalogProvisioningUpdateDetails?: ServiceCatalogProvisioningUpdateDetails | undefined; /** - *An array of key-value pairs. You can use tags to categorize your - * Amazon Web Services resources in different ways, for example, by purpose, owner, or - * environment. For more information, see Tagging Amazon Web Services Resources. - * In addition, the project must have tag update constraints set in order to include this - * parameter in the request. For more information, see Amazon Web Services Service - * Catalog Tag Update Constraints.
+ *An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
* @public */ Tags?: Tag[] | undefined; @@ -2300,33 +2026,25 @@ export interface UpdateTrainingJobRequest { TrainingJobName: string | undefined; /** - *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and - * storage paths.
+ *Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
* @public */ ProfilerConfig?: ProfilerConfigForUpdate | undefined; /** - *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework - * metrics.
+ *Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
* @public */ ProfilerRuleConfigurations?: ProfilerRuleConfiguration[] | undefined; /** - *The training job ResourceConfig to update warm pool retention
- * length.
The training job ResourceConfig to update warm pool retention length.
Configuration for remote debugging while the training job is running. You can update
- * the remote debugging configuration when the SecondaryStatus of the job is
- * Downloading or Training.To learn more about the remote
- * debugging functionality of SageMaker, see Access a training container
- * through Amazon Web Services Systems Manager (SSM) for remote
- * debugging.
Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the SecondaryStatus of the job is Downloading or Training.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
The name of the trial as displayed. The name doesn't need to be unique. If
- * DisplayName isn't specified, TrialName is displayed.
The name of the trial as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialName is displayed.
The name of the component as displayed. The name doesn't need to be unique. If
- * DisplayName isn't specified, TrialComponentName is
- * displayed.
The name of the component as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialComponentName is displayed.
The name of the private workforce that you want to update. You can find your workforce - * name by using the ListWorkforces operation.
+ *The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
* @public */ WorkforceName: string | undefined; /** - *A list of one to ten worker IP address ranges (CIDRs) that can be used to - * access tasks assigned to this workforce.
- *Maximum: Ten CIDR values
+ *A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
* @public */ SourceIpConfig?: SourceIpConfig | undefined; /** - *Use this parameter to update your OIDC Identity Provider (IdP) - * configuration for a workforce made using your own IdP.
+ *Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
* @public */ OidcConfig?: OidcConfig | undefined; @@ -2528,9 +2239,7 @@ export interface UpdateWorkforceRequest { */ export interface UpdateWorkforceResponse { /** - *A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, - * any workforce-related API operation used in a specific region will apply to the - * workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
+ *A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
* @public */ Workforce: Workforce | undefined; @@ -2547,26 +2256,7 @@ export interface UpdateWorkteamRequest { WorkteamName: string | undefined; /** - *A list of MemberDefinition objects that contains objects that identify
- * the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP).
- * For private workforces created using Amazon Cognito use
- * CognitoMemberDefinition. For workforces created using your own OIDC identity
- * provider (IdP) use OidcMemberDefinition. You should not provide input
- * for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito
- * user groups within the user pool used to create a workforce. All of the
- * CognitoMemberDefinition objects that make up the member definition must
- * have the same ClientId and UserPool values. To add a Amazon
- * Cognito user group to an existing worker pool, see Adding groups to a User
- * Pool. For more information about user pools, see Amazon Cognito User
- * Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want
- * to include in your private work team in OidcMemberDefinition by listing
- * those groups in Groups. Be aware that user groups that are already in the
- * work team must also be listed in Groups when you make this request to
- * remain on the work team. If you do not include these user groups, they will no longer be
- * associated with the work team you update.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
A multi-expression that searches for the specified resource or resources in a search. All
- * resource objects that satisfy the expression's condition are included in the search results.
- * You must specify at least one subexpression, filter, or nested filter. A
- * SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression
- * comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of
- * Boolean expressions using a list of resource properties. A nested filter is satisfied if a
- * single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be
- * nested in a list of search expression objects.
A Boolean operator: And or Or.
A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And or Or.
A Boolean operator used to evaluate the search expression. If you want every conditional
- * statement in all lists to be satisfied for the entire search expression to be true, specify
- * And. If only a single conditional statement needs to be true for the entire
- * search expression to be true, specify Or. The default value is
- * And.
A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or. The default value is And.
A Boolean conditional statement. Resources must satisfy this condition to be included in
- * search results. You must provide at least one subexpression, filter, or nested filter. The
- * maximum number of recursive SubExpressions, NestedFilters, and
- * Filters that can be included in a SearchExpression object is
- * 50.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions, NestedFilters, and Filters that can be included in a SearchExpression object is 50.
The name of the resource property used to sort the SearchResults. The default
- * is LastModifiedTime.
The name of the resource property used to sort the SearchResults. The default is LastModifiedTime.
How SearchResults are ordered. Valid values are Ascending or
- * Descending. The default is Descending.
How SearchResults are ordered. Valid values are Ascending or Descending. The default is Descending.
If more than MaxResults resources match the specified
- * SearchExpression, the response includes a NextToken. The
- * NextToken can be passed to the next SearchRequest to continue
- * retrieving results.
If more than MaxResults resources match the specified SearchExpression, the response includes a NextToken. The NextToken can be passed to the next SearchRequest to continue retrieving results.
A cross account filter option. When the value is "CrossAccount" the search
- * results will only include resources made discoverable to you from other accounts. When the
- * value is "SameAccount" or null the search results will only include
- * resources from your account. Default is null. For more information on searching
- * for resources made discoverable to your account, see Search
- * discoverable resources in the SageMaker Developer Guide. The maximum number of
- * ResourceCatalogs viewable is 1000.
A cross account filter option. When the value is "CrossAccount" the search results will only include resources made discoverable to you from other accounts. When the value is "SameAccount" or null the search results will only include resources from your account. Default is null. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalogs viewable is 1000.
Unexpected error during processing of request.
* + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * * @throws {@link ServiceQuotaExceededException} (client fault) *Request would cause a service quota to be exceeded.
* @@ -104,9 +137,6 @@ export interface CreateDataLakeDatasetCommandOutput extends CreateDataLakeDatase * @throws {@link ValidationException} (client fault) *The input does not satisfy the constraints specified by an AWS service.
* - * @throws {@link ResourceNotFoundException} (client fault) - *Request references a resource which does not exist.
- * * @throws {@link SupplyChainServiceException} *Base exception class for all service exceptions from SupplyChain service.
* @@ -304,6 +334,22 @@ export interface CreateDataLakeDatasetCommandOutput extends CreateDataLakeDatase * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", * name: "my_dataset", * namespace: "default", + * partitionSpec: { + * fields: [ + * { + * name: "creation_time", + * transform: { + * type: "DAY" + * } + * }, + * { + * name: "description", + * transform: { + * type: "IDENTITY" + * } + * } + * ] + * }, * schema: { * fields: [ * { @@ -325,9 +371,19 @@ export interface CreateDataLakeDatasetCommandOutput extends CreateDataLakeDatase * isRequired: false, * name: "creation_time", * type: "TIMESTAMP" + * }, + * { + * isRequired: false, + * name: "quantity", + * type: "LONG" * } * ], - * name: "MyDataset" + * name: "MyDataset", + * primaryKeys: [ + * { + * name: "id" + * } + * ] * }, * tags: { * tagKey1: "tagValue1", @@ -346,6 +402,22 @@ export interface CreateDataLakeDatasetCommandOutput extends CreateDataLakeDatase * lastModifiedTime: 1.727116807751E9, * name: "my_dataset", * namespace: "default", + * partitionSpec: { + * fields: [ + * { + * name: "creation_time", + * transform: { + * type: "DAY" + * } + * }, + * { + * name: "description", + * transform: { + * type: "IDENTITY" + * } + * } + * ] + * }, * schema: { * fields: [ * { @@ -367,9 +439,19 @@ export interface CreateDataLakeDatasetCommandOutput extends CreateDataLakeDatase * isRequired: false, * name: "creation_time", * type: "TIMESTAMP" + * }, + * { + * isRequired: false, + * name: "quantity", + * type: "LONG" * } * ], - * name: "MyDataset" + * name: "MyDataset", + * primaryKeys: [ + * { + * name: "id" + * } + * ] * } * } * } diff --git a/clients/client-supplychain/src/commands/CreateDataLakeNamespaceCommand.ts b/clients/client-supplychain/src/commands/CreateDataLakeNamespaceCommand.ts new file mode 100644 index 000000000000..d9bb053337de --- /dev/null +++ b/clients/client-supplychain/src/commands/CreateDataLakeNamespaceCommand.ts @@ -0,0 +1,154 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { CreateDataLakeNamespaceRequest, CreateDataLakeNamespaceResponse } from "../models/models_0"; +import { de_CreateDataLakeNamespaceCommand, se_CreateDataLakeNamespaceCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link CreateDataLakeNamespaceCommand}. + */ +export interface CreateDataLakeNamespaceCommandInput extends CreateDataLakeNamespaceRequest {} +/** + * @public + * + * The output of {@link CreateDataLakeNamespaceCommand}. + */ +export interface CreateDataLakeNamespaceCommandOutput extends CreateDataLakeNamespaceResponse, __MetadataBearer {} + +/** + *Enables you to programmatically create an Amazon Web Services Supply Chain data lake namespace. Developers can create the namespaces for a given instance ID.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, CreateDataLakeNamespaceCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, CreateDataLakeNamespaceCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // CreateDataLakeNamespaceRequest + * instanceId: "STRING_VALUE", // required + * name: "STRING_VALUE", // required + * description: "STRING_VALUE", + * tags: { // TagMap + * "You do not have the required privileges to perform this action.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Create a data lake namespace + * ```javascript + * // + * const input = { + * description: "This is my AWS Supply Chain namespace", + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "my_namespace", + * tags: { + * tagKey1: "tagValue1", + * tagKey2: "tagValue2" + * } + * }; + * const command = new CreateDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespace: { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + * createdTime: 1.736892560751E9, + * description: "This is my AWS Supply Chain namespace", + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892560751E9, + * name: "my_namespace" + * } + * } + * *\/ + * ``` + * + * @public + */ +export class CreateDataLakeNamespaceCommand extends $Command + .classBuilder< + CreateDataLakeNamespaceCommandInput, + CreateDataLakeNamespaceCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "CreateDataLakeNamespace", {}) + .n("SupplyChainClient", "CreateDataLakeNamespaceCommand") + .f(void 0, void 0) + .ser(se_CreateDataLakeNamespaceCommand) + .de(de_CreateDataLakeNamespaceCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: CreateDataLakeNamespaceRequest; + output: CreateDataLakeNamespaceResponse; + }; + sdk: { + input: CreateDataLakeNamespaceCommandInput; + output: CreateDataLakeNamespaceCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/DeleteDataLakeNamespaceCommand.ts b/clients/client-supplychain/src/commands/DeleteDataLakeNamespaceCommand.ts new file mode 100644 index 000000000000..23b414d6b5e3 --- /dev/null +++ b/clients/client-supplychain/src/commands/DeleteDataLakeNamespaceCommand.ts @@ -0,0 +1,133 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { DeleteDataLakeNamespaceRequest, DeleteDataLakeNamespaceResponse } from "../models/models_0"; +import { de_DeleteDataLakeNamespaceCommand, se_DeleteDataLakeNamespaceCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link DeleteDataLakeNamespaceCommand}. + */ +export interface DeleteDataLakeNamespaceCommandInput extends DeleteDataLakeNamespaceRequest {} +/** + * @public + * + * The output of {@link DeleteDataLakeNamespaceCommand}. + */ +export interface DeleteDataLakeNamespaceCommandOutput extends DeleteDataLakeNamespaceResponse, __MetadataBearer {} + +/** + *Enables you to programmatically delete an Amazon Web Services Supply Chain data lake namespace and its underling datasets. Developers can delete the existing namespaces for a given instance ID and namespace name.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, DeleteDataLakeNamespaceCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, DeleteDataLakeNamespaceCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // DeleteDataLakeNamespaceRequest + * instanceId: "STRING_VALUE", // required + * name: "STRING_VALUE", // required + * }; + * const command = new DeleteDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * // { // DeleteDataLakeNamespaceResponse + * // instanceId: "STRING_VALUE", // required + * // name: "STRING_VALUE", // required + * // }; + * + * ``` + * + * @param DeleteDataLakeNamespaceCommandInput - {@link DeleteDataLakeNamespaceCommandInput} + * @returns {@link DeleteDataLakeNamespaceCommandOutput} + * @see {@link DeleteDataLakeNamespaceCommandInput} for command's `input` shape. + * @see {@link DeleteDataLakeNamespaceCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Delete an AWS Supply Chain namespace + * ```javascript + * // + * const input = { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "my_namespace" + * }; + * const command = new DeleteDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * /* response is + * { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "my_namespace" + * } + * *\/ + * ``` + * + * @public + */ +export class DeleteDataLakeNamespaceCommand extends $Command + .classBuilder< + DeleteDataLakeNamespaceCommandInput, + DeleteDataLakeNamespaceCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "DeleteDataLakeNamespace", {}) + .n("SupplyChainClient", "DeleteDataLakeNamespaceCommand") + .f(void 0, void 0) + .ser(se_DeleteDataLakeNamespaceCommand) + .de(de_DeleteDataLakeNamespaceCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: DeleteDataLakeNamespaceRequest; + output: DeleteDataLakeNamespaceResponse; + }; + sdk: { + input: DeleteDataLakeNamespaceCommandInput; + output: DeleteDataLakeNamespaceCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/GetDataIntegrationEventCommand.ts b/clients/client-supplychain/src/commands/GetDataIntegrationEventCommand.ts new file mode 100644 index 000000000000..941e2a6f72c7 --- /dev/null +++ b/clients/client-supplychain/src/commands/GetDataIntegrationEventCommand.ts @@ -0,0 +1,158 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { GetDataIntegrationEventRequest, GetDataIntegrationEventResponse } from "../models/models_0"; +import { de_GetDataIntegrationEventCommand, se_GetDataIntegrationEventCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link GetDataIntegrationEventCommand}. + */ +export interface GetDataIntegrationEventCommandInput extends GetDataIntegrationEventRequest {} +/** + * @public + * + * The output of {@link GetDataIntegrationEventCommand}. + */ +export interface GetDataIntegrationEventCommandOutput extends GetDataIntegrationEventResponse, __MetadataBearer {} + +/** + *Enables you to programmatically view an Amazon Web Services Supply Chain Data Integration Event. Developers can view the eventType, eventGroupId, eventTimestamp, datasetTarget, datasetLoadExecution.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, GetDataIntegrationEventCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, GetDataIntegrationEventCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // GetDataIntegrationEventRequest + * instanceId: "STRING_VALUE", // required + * eventId: "STRING_VALUE", // required + * }; + * const command = new GetDataIntegrationEventCommand(input); + * const response = await client.send(command); + * // { // GetDataIntegrationEventResponse + * // event: { // DataIntegrationEvent + * // instanceId: "STRING_VALUE", // required + * // eventId: "STRING_VALUE", // required + * // eventType: "scn.data.forecast" || "scn.data.inventorylevel" || "scn.data.inboundorder" || "scn.data.inboundorderline" || "scn.data.inboundorderlineschedule" || "scn.data.outboundorderline" || "scn.data.outboundshipment" || "scn.data.processheader" || "scn.data.processoperation" || "scn.data.processproduct" || "scn.data.reservation" || "scn.data.shipment" || "scn.data.shipmentstop" || "scn.data.shipmentstoporder" || "scn.data.supplyplan" || "scn.data.dataset", // required + * // eventGroupId: "STRING_VALUE", // required + * // eventTimestamp: new Date("TIMESTAMP"), // required + * // datasetTargetDetails: { // DataIntegrationEventDatasetTargetDetails + * // datasetIdentifier: "STRING_VALUE", // required + * // operationType: "APPEND" || "UPSERT" || "DELETE", // required + * // datasetLoadExecution: { // DataIntegrationEventDatasetLoadExecutionDetails + * // status: "SUCCEEDED" || "IN_PROGRESS" || "FAILED", // required + * // message: "STRING_VALUE", + * // }, + * // }, + * // }, + * // }; + * + * ``` + * + * @param GetDataIntegrationEventCommandInput - {@link GetDataIntegrationEventCommandInput} + * @returns {@link GetDataIntegrationEventCommandOutput} + * @see {@link GetDataIntegrationEventCommandInput} for command's `input` shape. + * @see {@link GetDataIntegrationEventCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Successful GetDataIntegrationEvent + * ```javascript + * // + * const input = { + * eventId: "19739c8e-cd2e-4cbc-a2f7-0dc43239f042", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new GetDataIntegrationEventCommand(input); + * const response = await client.send(command); + * /* response is + * { + * event: { + * datasetTargetDetails: { + * datasetIdentifier: "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + * datasetLoadExecution: { + * status: "SUCCEEDED" + * }, + * operationType: "APPEND" + * }, + * eventGroupId: "datasetId", + * eventId: "19739c8e-cd2e-4cbc-a2f7-0dc43239f042", + * eventTimestamp: 1.515531081123E9, + * eventType: "scn.data.dataset", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * } + * } + * *\/ + * ``` + * + * @public + */ +export class GetDataIntegrationEventCommand extends $Command + .classBuilder< + GetDataIntegrationEventCommandInput, + GetDataIntegrationEventCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "GetDataIntegrationEvent", {}) + .n("SupplyChainClient", "GetDataIntegrationEventCommand") + .f(void 0, void 0) + .ser(se_GetDataIntegrationEventCommand) + .de(de_GetDataIntegrationEventCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: GetDataIntegrationEventRequest; + output: GetDataIntegrationEventResponse; + }; + sdk: { + input: GetDataIntegrationEventCommandInput; + output: GetDataIntegrationEventCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/GetDataIntegrationFlowCommand.ts b/clients/client-supplychain/src/commands/GetDataIntegrationFlowCommand.ts index 154adef2fc02..30e0b1d98ff6 100644 --- a/clients/client-supplychain/src/commands/GetDataIntegrationFlowCommand.ts +++ b/clients/client-supplychain/src/commands/GetDataIntegrationFlowCommand.ts @@ -5,7 +5,11 @@ import { Command as $Command } from "@smithy/smithy-client"; import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { commonParams } from "../endpoint/EndpointParameters"; -import { GetDataIntegrationFlowRequest, GetDataIntegrationFlowResponse } from "../models/models_0"; +import { + GetDataIntegrationFlowRequest, + GetDataIntegrationFlowResponse, + GetDataIntegrationFlowResponseFilterSensitiveLog, +} from "../models/models_0"; import { de_GetDataIntegrationFlowCommand, se_GetDataIntegrationFlowCommand } from "../protocols/Aws_restJson1"; import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; @@ -61,6 +65,17 @@ export interface GetDataIntegrationFlowCommandOutput extends GetDataIntegrationF * // options: { // DataIntegrationFlowDatasetOptions * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { // DataIntegrationFlowDedupeStrategy + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { // DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration + * // fields: [ // DataIntegrationFlowFieldPriorityDedupeFieldList // required + * // { // DataIntegrationFlowFieldPriorityDedupeField + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -85,6 +100,17 @@ export interface GetDataIntegrationFlowCommandOutput extends GetDataIntegrationF * // options: { * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { + * // fields: [ // required + * // { + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -188,7 +214,7 @@ export class GetDataIntegrationFlowCommand extends $Command }) .s("GalaxyPublicAPIGateway", "GetDataIntegrationFlow", {}) .n("SupplyChainClient", "GetDataIntegrationFlowCommand") - .f(void 0, void 0) + .f(void 0, GetDataIntegrationFlowResponseFilterSensitiveLog) .ser(se_GetDataIntegrationFlowCommand) .de(de_GetDataIntegrationFlowCommand) .build() { diff --git a/clients/client-supplychain/src/commands/GetDataIntegrationFlowExecutionCommand.ts b/clients/client-supplychain/src/commands/GetDataIntegrationFlowExecutionCommand.ts new file mode 100644 index 000000000000..d9469da45c3b --- /dev/null +++ b/clients/client-supplychain/src/commands/GetDataIntegrationFlowExecutionCommand.ts @@ -0,0 +1,203 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { GetDataIntegrationFlowExecutionRequest, GetDataIntegrationFlowExecutionResponse } from "../models/models_0"; +import { + de_GetDataIntegrationFlowExecutionCommand, + se_GetDataIntegrationFlowExecutionCommand, +} from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link GetDataIntegrationFlowExecutionCommand}. + */ +export interface GetDataIntegrationFlowExecutionCommandInput extends GetDataIntegrationFlowExecutionRequest {} +/** + * @public + * + * The output of {@link GetDataIntegrationFlowExecutionCommand}. + */ +export interface GetDataIntegrationFlowExecutionCommandOutput + extends GetDataIntegrationFlowExecutionResponse, + __MetadataBearer {} + +/** + *Get the flow execution.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, GetDataIntegrationFlowExecutionCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, GetDataIntegrationFlowExecutionCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // GetDataIntegrationFlowExecutionRequest + * instanceId: "STRING_VALUE", // required + * flowName: "STRING_VALUE", // required + * executionId: "STRING_VALUE", // required + * }; + * const command = new GetDataIntegrationFlowExecutionCommand(input); + * const response = await client.send(command); + * // { // GetDataIntegrationFlowExecutionResponse + * // flowExecution: { // DataIntegrationFlowExecution + * // instanceId: "STRING_VALUE", // required + * // flowName: "STRING_VALUE", // required + * // executionId: "STRING_VALUE", // required + * // status: "SUCCEEDED" || "IN_PROGRESS" || "FAILED", + * // sourceInfo: { // DataIntegrationFlowExecutionSourceInfo + * // sourceType: "S3" || "DATASET", // required + * // s3Source: { // DataIntegrationFlowS3Source + * // bucketName: "STRING_VALUE", // required + * // key: "STRING_VALUE", // required + * // }, + * // datasetSource: { // DataIntegrationFlowDatasetSource + * // datasetIdentifier: "STRING_VALUE", // required + * // }, + * // }, + * // message: "STRING_VALUE", + * // startTime: new Date("TIMESTAMP"), + * // endTime: new Date("TIMESTAMP"), + * // outputMetadata: { // DataIntegrationFlowExecutionOutputMetadata + * // diagnosticReportsRootS3URI: "STRING_VALUE", + * // }, + * // }, + * // }; + * + * ``` + * + * @param GetDataIntegrationFlowExecutionCommandInput - {@link GetDataIntegrationFlowExecutionCommandInput} + * @returns {@link GetDataIntegrationFlowExecutionCommandOutput} + * @see {@link GetDataIntegrationFlowExecutionCommandInput} for command's `input` shape. + * @see {@link GetDataIntegrationFlowExecutionCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Successful GetDataIntegrationFlowExecution for S3 source + * ```javascript + * // + * const input = { + * executionId: "edbbdd3f-c0f9-49d9-ab01-f64542f803b7", + * flowName: "source-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new GetDataIntegrationFlowExecutionCommand(input); + * const response = await client.send(command); + * /* response is + * { + * flowExecution: { + * endTime: 1.515531090123E9, + * executionId: "edbbdd3f-c0f9-49d9-ab01-f64542f803b7", + * flowName: "source-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a", + * sourceInfo: { + * s3Source: { + * bucketName: "galaxy-raw-input-test-data-prod-pdx-1", + * key: "sources/product-sources.csv" + * }, + * sourceType: "S3" + * }, + * startTime: 1.515531081123E9, + * status: "SUCCEEDED" + * } + * } + * *\/ + * ``` + * + * @example Successful GetDataIntegrationFlowExecution for DATASET source + * ```javascript + * // + * const input = { + * executionId: "9daf6071-d12c-4eef-864c-73cea2557825", + * flowName: "target-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new GetDataIntegrationFlowExecutionCommand(input); + * const response = await client.send(command); + * /* response is + * { + * flowExecution: { + * endTime: 1.515531090123E9, + * executionId: "9daf6071-d12c-4eef-864c-73cea2557825", + * flowName: "target-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a", + * sourceInfo: { + * datasetSource: { + * datasetIdentifier: "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/default/datasets/product" + * }, + * sourceType: "DATASET" + * }, + * startTime: 1.515531081123E9, + * status: "SUCCEEDED" + * } + * } + * *\/ + * ``` + * + * @public + */ +export class GetDataIntegrationFlowExecutionCommand extends $Command + .classBuilder< + GetDataIntegrationFlowExecutionCommandInput, + GetDataIntegrationFlowExecutionCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "GetDataIntegrationFlowExecution", {}) + .n("SupplyChainClient", "GetDataIntegrationFlowExecutionCommand") + .f(void 0, void 0) + .ser(se_GetDataIntegrationFlowExecutionCommand) + .de(de_GetDataIntegrationFlowExecutionCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: GetDataIntegrationFlowExecutionRequest; + output: GetDataIntegrationFlowExecutionResponse; + }; + sdk: { + input: GetDataIntegrationFlowExecutionCommandInput; + output: GetDataIntegrationFlowExecutionCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/GetDataLakeDatasetCommand.ts b/clients/client-supplychain/src/commands/GetDataLakeDatasetCommand.ts index 23c3703c9b09..89f9b6f3d06b 100644 --- a/clients/client-supplychain/src/commands/GetDataLakeDatasetCommand.ts +++ b/clients/client-supplychain/src/commands/GetDataLakeDatasetCommand.ts @@ -53,12 +53,27 @@ export interface GetDataLakeDatasetCommandOutput extends GetDataLakeDatasetRespo * // fields: [ // DataLakeDatasetSchemaFieldList // required * // { // DataLakeDatasetSchemaField * // name: "STRING_VALUE", // required - * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP", // required + * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP" || "LONG", // required * // isRequired: true || false, // required * // }, * // ], + * // primaryKeys: [ // DataLakeDatasetPrimaryKeyFieldList + * // { // DataLakeDatasetPrimaryKeyField + * // name: "STRING_VALUE", // required + * // }, + * // ], * // }, * // description: "STRING_VALUE", + * // partitionSpec: { // DataLakeDatasetPartitionSpec + * // fields: [ // DataLakeDatasetPartitionFieldList // required + * // { // DataLakeDatasetPartitionField + * // name: "STRING_VALUE", // required + * // transform: { // DataLakeDatasetPartitionFieldTransform + * // type: "YEAR" || "MONTH" || "DAY" || "HOUR" || "IDENTITY", // required + * // }, + * // }, + * // ], + * // }, * // createdTime: new Date("TIMESTAMP"), // required * // lastModifiedTime: new Date("TIMESTAMP"), // required * // }, @@ -297,6 +312,22 @@ export interface GetDataLakeDatasetCommandOutput extends GetDataLakeDatasetRespo * lastModifiedTime: 1.727116807751E9, * name: "my_dataset", * namespace: "default", + * partitionSpec: { + * fields: [ + * { + * name: "creation_time", + * transform: { + * type: "DAY" + * } + * }, + * { + * name: "description", + * transform: { + * type: "IDENTITY" + * } + * } + * ] + * }, * schema: { * fields: [ * { @@ -318,9 +349,19 @@ export interface GetDataLakeDatasetCommandOutput extends GetDataLakeDatasetRespo * isRequired: false, * name: "creation_time", * type: "TIMESTAMP" + * }, + * { + * isRequired: false, + * name: "quantity", + * type: "LONG" * } * ], - * name: "MyDataset" + * name: "MyDataset", + * primaryKeys: [ + * { + * name: "id" + * } + * ] * } * } * } diff --git a/clients/client-supplychain/src/commands/GetDataLakeNamespaceCommand.ts b/clients/client-supplychain/src/commands/GetDataLakeNamespaceCommand.ts new file mode 100644 index 000000000000..90348d8f09e4 --- /dev/null +++ b/clients/client-supplychain/src/commands/GetDataLakeNamespaceCommand.ts @@ -0,0 +1,167 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { GetDataLakeNamespaceRequest, GetDataLakeNamespaceResponse } from "../models/models_0"; +import { de_GetDataLakeNamespaceCommand, se_GetDataLakeNamespaceCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link GetDataLakeNamespaceCommand}. + */ +export interface GetDataLakeNamespaceCommandInput extends GetDataLakeNamespaceRequest {} +/** + * @public + * + * The output of {@link GetDataLakeNamespaceCommand}. + */ +export interface GetDataLakeNamespaceCommandOutput extends GetDataLakeNamespaceResponse, __MetadataBearer {} + +/** + *Enables you to programmatically view an Amazon Web Services Supply Chain data lake namespace. Developers can view the data lake namespace information such as description for a given instance ID and namespace name.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, GetDataLakeNamespaceCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, GetDataLakeNamespaceCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // GetDataLakeNamespaceRequest + * instanceId: "STRING_VALUE", // required + * name: "STRING_VALUE", // required + * }; + * const command = new GetDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * // { // GetDataLakeNamespaceResponse + * // namespace: { // DataLakeNamespace + * // instanceId: "STRING_VALUE", // required + * // name: "STRING_VALUE", // required + * // arn: "STRING_VALUE", // required + * // description: "STRING_VALUE", + * // createdTime: new Date("TIMESTAMP"), // required + * // lastModifiedTime: new Date("TIMESTAMP"), // required + * // }, + * // }; + * + * ``` + * + * @param GetDataLakeNamespaceCommandInput - {@link GetDataLakeNamespaceCommandInput} + * @returns {@link GetDataLakeNamespaceCommandOutput} + * @see {@link GetDataLakeNamespaceCommandInput} for command's `input` shape. + * @see {@link GetDataLakeNamespaceCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Get properties of an existing AWS Supply Chain namespace + * ```javascript + * // + * const input = { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "my_namespace" + * }; + * const command = new GetDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespace: { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + * createdTime: 1.736892560751E9, + * description: "This is my AWS Supply Chain namespace", + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892560751E9, + * name: "my_namespace" + * } + * } + * *\/ + * ``` + * + * @example Get proporties of an existing pre-defined AWS Supply Chain namespace + * ```javascript + * // + * const input = { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "asc" + * }; + * const command = new GetDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespace: { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/asc", + * createdTime: 1.736892430234E9, + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892430234E9, + * name: "asc" + * } + * } + * *\/ + * ``` + * + * @public + */ +export class GetDataLakeNamespaceCommand extends $Command + .classBuilder< + GetDataLakeNamespaceCommandInput, + GetDataLakeNamespaceCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "GetDataLakeNamespace", {}) + .n("SupplyChainClient", "GetDataLakeNamespaceCommand") + .f(void 0, void 0) + .ser(se_GetDataLakeNamespaceCommand) + .de(de_GetDataLakeNamespaceCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: GetDataLakeNamespaceRequest; + output: GetDataLakeNamespaceResponse; + }; + sdk: { + input: GetDataLakeNamespaceCommandInput; + output: GetDataLakeNamespaceCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/ListDataIntegrationEventsCommand.ts b/clients/client-supplychain/src/commands/ListDataIntegrationEventsCommand.ts new file mode 100644 index 000000000000..ed54a165cde6 --- /dev/null +++ b/clients/client-supplychain/src/commands/ListDataIntegrationEventsCommand.ts @@ -0,0 +1,164 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { ListDataIntegrationEventsRequest, ListDataIntegrationEventsResponse } from "../models/models_0"; +import { de_ListDataIntegrationEventsCommand, se_ListDataIntegrationEventsCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link ListDataIntegrationEventsCommand}. + */ +export interface ListDataIntegrationEventsCommandInput extends ListDataIntegrationEventsRequest {} +/** + * @public + * + * The output of {@link ListDataIntegrationEventsCommand}. + */ +export interface ListDataIntegrationEventsCommandOutput extends ListDataIntegrationEventsResponse, __MetadataBearer {} + +/** + *Enables you to programmatically list all data integration events for the provided Amazon Web Services Supply Chain instance.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, ListDataIntegrationEventsCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, ListDataIntegrationEventsCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // ListDataIntegrationEventsRequest + * instanceId: "STRING_VALUE", // required + * eventType: "scn.data.forecast" || "scn.data.inventorylevel" || "scn.data.inboundorder" || "scn.data.inboundorderline" || "scn.data.inboundorderlineschedule" || "scn.data.outboundorderline" || "scn.data.outboundshipment" || "scn.data.processheader" || "scn.data.processoperation" || "scn.data.processproduct" || "scn.data.reservation" || "scn.data.shipment" || "scn.data.shipmentstop" || "scn.data.shipmentstoporder" || "scn.data.supplyplan" || "scn.data.dataset", + * nextToken: "STRING_VALUE", + * maxResults: Number("int"), + * }; + * const command = new ListDataIntegrationEventsCommand(input); + * const response = await client.send(command); + * // { // ListDataIntegrationEventsResponse + * // events: [ // DataIntegrationEventList // required + * // { // DataIntegrationEvent + * // instanceId: "STRING_VALUE", // required + * // eventId: "STRING_VALUE", // required + * // eventType: "scn.data.forecast" || "scn.data.inventorylevel" || "scn.data.inboundorder" || "scn.data.inboundorderline" || "scn.data.inboundorderlineschedule" || "scn.data.outboundorderline" || "scn.data.outboundshipment" || "scn.data.processheader" || "scn.data.processoperation" || "scn.data.processproduct" || "scn.data.reservation" || "scn.data.shipment" || "scn.data.shipmentstop" || "scn.data.shipmentstoporder" || "scn.data.supplyplan" || "scn.data.dataset", // required + * // eventGroupId: "STRING_VALUE", // required + * // eventTimestamp: new Date("TIMESTAMP"), // required + * // datasetTargetDetails: { // DataIntegrationEventDatasetTargetDetails + * // datasetIdentifier: "STRING_VALUE", // required + * // operationType: "APPEND" || "UPSERT" || "DELETE", // required + * // datasetLoadExecution: { // DataIntegrationEventDatasetLoadExecutionDetails + * // status: "SUCCEEDED" || "IN_PROGRESS" || "FAILED", // required + * // message: "STRING_VALUE", + * // }, + * // }, + * // }, + * // ], + * // nextToken: "STRING_VALUE", + * // }; + * + * ``` + * + * @param ListDataIntegrationEventsCommandInput - {@link ListDataIntegrationEventsCommandInput} + * @returns {@link ListDataIntegrationEventsCommandOutput} + * @see {@link ListDataIntegrationEventsCommandInput} for command's `input` shape. + * @see {@link ListDataIntegrationEventsCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Successful ListDataIntegrationEvents + * ```javascript + * // + * const input = { + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new ListDataIntegrationEventsCommand(input); + * const response = await client.send(command); + * /* response is + * { + * events: [ + * { + * datasetTargetDetails: { + * datasetIdentifier: "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + * datasetLoadExecution: { + * status: "SUCCEEDED" + * }, + * operationType: "APPEND" + * }, + * eventGroupId: "datasetId", + * eventId: "19739c8e-cd2e-4cbc-a2f7-0dc43239f042", + * eventTimestamp: 1.515531081123E9, + * eventType: "scn.data.dataset", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * } + * ] + * } + * *\/ + * ``` + * + * @public + */ +export class ListDataIntegrationEventsCommand extends $Command + .classBuilder< + ListDataIntegrationEventsCommandInput, + ListDataIntegrationEventsCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "ListDataIntegrationEvents", {}) + .n("SupplyChainClient", "ListDataIntegrationEventsCommand") + .f(void 0, void 0) + .ser(se_ListDataIntegrationEventsCommand) + .de(de_ListDataIntegrationEventsCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: ListDataIntegrationEventsRequest; + output: ListDataIntegrationEventsResponse; + }; + sdk: { + input: ListDataIntegrationEventsCommandInput; + output: ListDataIntegrationEventsCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/ListDataIntegrationFlowExecutionsCommand.ts b/clients/client-supplychain/src/commands/ListDataIntegrationFlowExecutionsCommand.ts new file mode 100644 index 000000000000..de87875dcc4e --- /dev/null +++ b/clients/client-supplychain/src/commands/ListDataIntegrationFlowExecutionsCommand.ts @@ -0,0 +1,181 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { + ListDataIntegrationFlowExecutionsRequest, + ListDataIntegrationFlowExecutionsResponse, +} from "../models/models_0"; +import { + de_ListDataIntegrationFlowExecutionsCommand, + se_ListDataIntegrationFlowExecutionsCommand, +} from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link ListDataIntegrationFlowExecutionsCommand}. + */ +export interface ListDataIntegrationFlowExecutionsCommandInput extends ListDataIntegrationFlowExecutionsRequest {} +/** + * @public + * + * The output of {@link ListDataIntegrationFlowExecutionsCommand}. + */ +export interface ListDataIntegrationFlowExecutionsCommandOutput + extends ListDataIntegrationFlowExecutionsResponse, + __MetadataBearer {} + +/** + *List flow executions.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, ListDataIntegrationFlowExecutionsCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, ListDataIntegrationFlowExecutionsCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // ListDataIntegrationFlowExecutionsRequest + * instanceId: "STRING_VALUE", // required + * flowName: "STRING_VALUE", // required + * nextToken: "STRING_VALUE", + * maxResults: Number("int"), + * }; + * const command = new ListDataIntegrationFlowExecutionsCommand(input); + * const response = await client.send(command); + * // { // ListDataIntegrationFlowExecutionsResponse + * // flowExecutions: [ // DataIntegrationFlowExecutionList // required + * // { // DataIntegrationFlowExecution + * // instanceId: "STRING_VALUE", // required + * // flowName: "STRING_VALUE", // required + * // executionId: "STRING_VALUE", // required + * // status: "SUCCEEDED" || "IN_PROGRESS" || "FAILED", + * // sourceInfo: { // DataIntegrationFlowExecutionSourceInfo + * // sourceType: "S3" || "DATASET", // required + * // s3Source: { // DataIntegrationFlowS3Source + * // bucketName: "STRING_VALUE", // required + * // key: "STRING_VALUE", // required + * // }, + * // datasetSource: { // DataIntegrationFlowDatasetSource + * // datasetIdentifier: "STRING_VALUE", // required + * // }, + * // }, + * // message: "STRING_VALUE", + * // startTime: new Date("TIMESTAMP"), + * // endTime: new Date("TIMESTAMP"), + * // outputMetadata: { // DataIntegrationFlowExecutionOutputMetadata + * // diagnosticReportsRootS3URI: "STRING_VALUE", + * // }, + * // }, + * // ], + * // nextToken: "STRING_VALUE", + * // }; + * + * ``` + * + * @param ListDataIntegrationFlowExecutionsCommandInput - {@link ListDataIntegrationFlowExecutionsCommandInput} + * @returns {@link ListDataIntegrationFlowExecutionsCommandOutput} + * @see {@link ListDataIntegrationFlowExecutionsCommandInput} for command's `input` shape. + * @see {@link ListDataIntegrationFlowExecutionsCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Successful ListDataIntegrationFlowExecutions + * ```javascript + * // + * const input = { + * flowName: "source-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new ListDataIntegrationFlowExecutionsCommand(input); + * const response = await client.send(command); + * /* response is + * { + * flowExecutions: [ + * { + * endTime: 1.515531090123E9, + * executionId: "edbbdd3f-c0f9-49d9-ab01-f64542f803b7", + * flowName: "source-product", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a", + * sourceInfo: { + * s3Source: { + * bucketName: "galaxy-raw-input-test-data-prod-pdx-1", + * key: "sources/product-sources.csv" + * }, + * sourceType: "S3" + * }, + * startTime: 1.515531081123E9, + * status: "SUCCEEDED" + * } + * ] + * } + * *\/ + * ``` + * + * @public + */ +export class ListDataIntegrationFlowExecutionsCommand extends $Command + .classBuilder< + ListDataIntegrationFlowExecutionsCommandInput, + ListDataIntegrationFlowExecutionsCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "ListDataIntegrationFlowExecutions", {}) + .n("SupplyChainClient", "ListDataIntegrationFlowExecutionsCommand") + .f(void 0, void 0) + .ser(se_ListDataIntegrationFlowExecutionsCommand) + .de(de_ListDataIntegrationFlowExecutionsCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: ListDataIntegrationFlowExecutionsRequest; + output: ListDataIntegrationFlowExecutionsResponse; + }; + sdk: { + input: ListDataIntegrationFlowExecutionsCommandInput; + output: ListDataIntegrationFlowExecutionsCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/ListDataIntegrationFlowsCommand.ts b/clients/client-supplychain/src/commands/ListDataIntegrationFlowsCommand.ts index 29247c6ce93e..e61acc0339dd 100644 --- a/clients/client-supplychain/src/commands/ListDataIntegrationFlowsCommand.ts +++ b/clients/client-supplychain/src/commands/ListDataIntegrationFlowsCommand.ts @@ -5,7 +5,11 @@ import { Command as $Command } from "@smithy/smithy-client"; import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { commonParams } from "../endpoint/EndpointParameters"; -import { ListDataIntegrationFlowsRequest, ListDataIntegrationFlowsResponse } from "../models/models_0"; +import { + ListDataIntegrationFlowsRequest, + ListDataIntegrationFlowsResponse, + ListDataIntegrationFlowsResponseFilterSensitiveLog, +} from "../models/models_0"; import { de_ListDataIntegrationFlowsCommand, se_ListDataIntegrationFlowsCommand } from "../protocols/Aws_restJson1"; import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; @@ -63,6 +67,17 @@ export interface ListDataIntegrationFlowsCommandOutput extends ListDataIntegrati * // options: { // DataIntegrationFlowDatasetOptions * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { // DataIntegrationFlowDedupeStrategy + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { // DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration + * // fields: [ // DataIntegrationFlowFieldPriorityDedupeFieldList // required + * // { // DataIntegrationFlowFieldPriorityDedupeField + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -87,6 +102,17 @@ export interface ListDataIntegrationFlowsCommandOutput extends ListDataIntegrati * // options: { * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { + * // fields: [ // required + * // { + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -192,7 +218,22 @@ export interface ListDataIntegrationFlowsCommandOutput extends ListDataIntegrati * ], * target: { * datasetTarget: { - * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + * options: { + * dedupeRecords: true, + * dedupeStrategy: { + * fieldPriority: { + * fields: [ + * { + * name: "eff_start_date", + * sortOrder: "DESC" + * } + * ] + * }, + * type: "FIELD_PRIORITY" + * }, + * loadType: "REPLACE" + * } * }, * targetType: "DATASET" * }, @@ -227,7 +268,7 @@ export class ListDataIntegrationFlowsCommand extends $Command }) .s("GalaxyPublicAPIGateway", "ListDataIntegrationFlows", {}) .n("SupplyChainClient", "ListDataIntegrationFlowsCommand") - .f(void 0, void 0) + .f(void 0, ListDataIntegrationFlowsResponseFilterSensitiveLog) .ser(se_ListDataIntegrationFlowsCommand) .de(de_ListDataIntegrationFlowsCommand) .build() { diff --git a/clients/client-supplychain/src/commands/ListDataLakeDatasetsCommand.ts b/clients/client-supplychain/src/commands/ListDataLakeDatasetsCommand.ts index b02da7d8254a..1ca4409c033c 100644 --- a/clients/client-supplychain/src/commands/ListDataLakeDatasetsCommand.ts +++ b/clients/client-supplychain/src/commands/ListDataLakeDatasetsCommand.ts @@ -55,12 +55,27 @@ export interface ListDataLakeDatasetsCommandOutput extends ListDataLakeDatasetsR * // fields: [ // DataLakeDatasetSchemaFieldList // required * // { // DataLakeDatasetSchemaField * // name: "STRING_VALUE", // required - * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP", // required + * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP" || "LONG", // required * // isRequired: true || false, // required * // }, * // ], + * // primaryKeys: [ // DataLakeDatasetPrimaryKeyFieldList + * // { // DataLakeDatasetPrimaryKeyField + * // name: "STRING_VALUE", // required + * // }, + * // ], * // }, * // description: "STRING_VALUE", + * // partitionSpec: { // DataLakeDatasetPartitionSpec + * // fields: [ // DataLakeDatasetPartitionFieldList // required + * // { // DataLakeDatasetPartitionField + * // name: "STRING_VALUE", // required + * // transform: { // DataLakeDatasetPartitionFieldTransform + * // type: "YEAR" || "MONTH" || "DAY" || "HOUR" || "IDENTITY", // required + * // }, + * // }, + * // ], + * // }, * // createdTime: new Date("TIMESTAMP"), // required * // lastModifiedTime: new Date("TIMESTAMP"), // required * // }, @@ -304,6 +319,22 @@ export interface ListDataLakeDatasetsCommandOutput extends ListDataLakeDatasetsR * lastModifiedTime: 1.727116807751E9, * name: "my_dataset", * namespace: "default", + * partitionSpec: { + * fields: [ + * { + * name: "creation_time", + * transform: { + * type: "DAY" + * } + * }, + * { + * name: "description", + * transform: { + * type: "IDENTITY" + * } + * } + * ] + * }, * schema: { * fields: [ * { @@ -325,9 +356,19 @@ export interface ListDataLakeDatasetsCommandOutput extends ListDataLakeDatasetsR * isRequired: false, * name: "creation_time", * type: "TIMESTAMP" + * }, + * { + * isRequired: false, + * name: "quantity", + * type: "LONG" * } * ], - * name: "MyDataset" + * name: "MyDataset", + * primaryKeys: [ + * { + * name: "id" + * } + * ] * } * }, * { diff --git a/clients/client-supplychain/src/commands/ListDataLakeNamespacesCommand.ts b/clients/client-supplychain/src/commands/ListDataLakeNamespacesCommand.ts new file mode 100644 index 000000000000..da9807e58547 --- /dev/null +++ b/clients/client-supplychain/src/commands/ListDataLakeNamespacesCommand.ts @@ -0,0 +1,182 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { ListDataLakeNamespacesRequest, ListDataLakeNamespacesResponse } from "../models/models_0"; +import { de_ListDataLakeNamespacesCommand, se_ListDataLakeNamespacesCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link ListDataLakeNamespacesCommand}. + */ +export interface ListDataLakeNamespacesCommandInput extends ListDataLakeNamespacesRequest {} +/** + * @public + * + * The output of {@link ListDataLakeNamespacesCommand}. + */ +export interface ListDataLakeNamespacesCommandOutput extends ListDataLakeNamespacesResponse, __MetadataBearer {} + +/** + *Enables you to programmatically view the list of Amazon Web Services Supply Chain data lake namespaces. Developers can view the namespaces and the corresponding information such as description for a given instance ID. Note that this API only return custom namespaces, instance pre-defined namespaces are not included.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, ListDataLakeNamespacesCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, ListDataLakeNamespacesCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // ListDataLakeNamespacesRequest + * instanceId: "STRING_VALUE", // required + * nextToken: "STRING_VALUE", + * maxResults: Number("int"), + * }; + * const command = new ListDataLakeNamespacesCommand(input); + * const response = await client.send(command); + * // { // ListDataLakeNamespacesResponse + * // namespaces: [ // DataLakeNamespaceList // required + * // { // DataLakeNamespace + * // instanceId: "STRING_VALUE", // required + * // name: "STRING_VALUE", // required + * // arn: "STRING_VALUE", // required + * // description: "STRING_VALUE", + * // createdTime: new Date("TIMESTAMP"), // required + * // lastModifiedTime: new Date("TIMESTAMP"), // required + * // }, + * // ], + * // nextToken: "STRING_VALUE", + * // }; + * + * ``` + * + * @param ListDataLakeNamespacesCommandInput - {@link ListDataLakeNamespacesCommandInput} + * @returns {@link ListDataLakeNamespacesCommandOutput} + * @see {@link ListDataLakeNamespacesCommandInput} for command's `input` shape. + * @see {@link ListDataLakeNamespacesCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example List AWS Supply Chain namespaces + * ```javascript + * // + * const input = { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5" + * }; + * const command = new ListDataLakeNamespacesCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespaces: [ + * { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/custom_namespace", + * createdTime: 1.736892060751E9, + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892060751E9, + * name: "custom_namespace" + * }, + * { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + * createdTime: 1.736892560751E9, + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892586156E9, + * name: "my_namespace" + * } + * ] + * } + * *\/ + * ``` + * + * @example List AWS Supply Chain namespaces using pagination + * ```javascript + * // + * const input = { + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * maxResults: 1, + * nextToken: "next_token_returned_from_previous_list_request" + * }; + * const command = new ListDataLakeNamespacesCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespaces: [ + * { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + * createdTime: 1.736892560751E9, + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892586156E9, + * name: "my_namespace" + * } + * ], + * nextToken: "next_token_for_next_list_request" + * } + * *\/ + * ``` + * + * @public + */ +export class ListDataLakeNamespacesCommand extends $Command + .classBuilder< + ListDataLakeNamespacesCommandInput, + ListDataLakeNamespacesCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "ListDataLakeNamespaces", {}) + .n("SupplyChainClient", "ListDataLakeNamespacesCommand") + .f(void 0, void 0) + .ser(se_ListDataLakeNamespacesCommand) + .de(de_ListDataLakeNamespacesCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: ListDataLakeNamespacesRequest; + output: ListDataLakeNamespacesResponse; + }; + sdk: { + input: ListDataLakeNamespacesCommandInput; + output: ListDataLakeNamespacesCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/SendDataIntegrationEventCommand.ts b/clients/client-supplychain/src/commands/SendDataIntegrationEventCommand.ts index 9d836c13c4f9..e575f1c24a6a 100644 --- a/clients/client-supplychain/src/commands/SendDataIntegrationEventCommand.ts +++ b/clients/client-supplychain/src/commands/SendDataIntegrationEventCommand.ts @@ -32,7 +32,7 @@ export interface SendDataIntegrationEventCommandInput extends SendDataIntegratio export interface SendDataIntegrationEventCommandOutput extends SendDataIntegrationEventResponse, __MetadataBearer {} /** - *Send the transactional data payload for the event with real-time data for analysis or monitoring. The real-time data events are stored in an Amazon Web Services service before being processed and stored in data lake. New data events are synced with data lake at 5 PM GMT everyday. The updated transactional data is available in data lake after ingestion.
+ *Send the data payload for the event with real-time data for analysis or monitoring. The real-time data events are stored in an Amazon Web Services service before being processed and stored in data lake.
* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript @@ -41,11 +41,15 @@ export interface SendDataIntegrationEventCommandOutput extends SendDataIntegrati * const client = new SupplyChainClient(config); * const input = { // SendDataIntegrationEventRequest * instanceId: "STRING_VALUE", // required - * eventType: "scn.data.forecast" || "scn.data.inventorylevel" || "scn.data.inboundorder" || "scn.data.inboundorderline" || "scn.data.inboundorderlineschedule" || "scn.data.outboundorderline" || "scn.data.outboundshipment" || "scn.data.processheader" || "scn.data.processoperation" || "scn.data.processproduct" || "scn.data.reservation" || "scn.data.shipment" || "scn.data.shipmentstop" || "scn.data.shipmentstoporder" || "scn.data.supplyplan", // required + * eventType: "scn.data.forecast" || "scn.data.inventorylevel" || "scn.data.inboundorder" || "scn.data.inboundorderline" || "scn.data.inboundorderlineschedule" || "scn.data.outboundorderline" || "scn.data.outboundshipment" || "scn.data.processheader" || "scn.data.processoperation" || "scn.data.processproduct" || "scn.data.reservation" || "scn.data.shipment" || "scn.data.shipmentstop" || "scn.data.shipmentstoporder" || "scn.data.supplyplan" || "scn.data.dataset", // required * data: "STRING_VALUE", // required * eventGroupId: "STRING_VALUE", // required * eventTimestamp: new Date("TIMESTAMP"), * clientToken: "STRING_VALUE", + * datasetTarget: { // DataIntegrationEventDatasetTargetConfiguration + * datasetIdentifier: "STRING_VALUE", // required + * operationType: "APPEND" || "UPSERT" || "DELETE", // required + * }, * }; * const command = new SendDataIntegrationEventCommand(input); * const response = await client.send(command); @@ -371,6 +375,29 @@ export interface SendDataIntegrationEventCommandOutput extends SendDataIntegrati * *\/ * ``` * + * @example Successful SendDataIntegrationEvent for dataset event type + * ```javascript + * // + * const input = { + * data: `{"dataset_id": "datset-id-test-123" }`, + * datasetTarget: { + * datasetIdentifier: "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + * operationType: "APPEND" + * }, + * eventGroupId: "datasetId", + * eventTimestamp: 1.515531081123E9, + * eventType: "scn.data.dataset", + * instanceId: "8928ae12-15e5-4441-825d-ec2184f0a43a" + * }; + * const command = new SendDataIntegrationEventCommand(input); + * const response = await client.send(command); + * /* response is + * { + * eventId: "19739c8e-cd2e-4cbc-a2f7-0dc43239f042" + * } + * *\/ + * ``` + * * @public */ export class SendDataIntegrationEventCommand extends $Command diff --git a/clients/client-supplychain/src/commands/UpdateDataIntegrationFlowCommand.ts b/clients/client-supplychain/src/commands/UpdateDataIntegrationFlowCommand.ts index fd5a9493bae8..dc535e7dc542 100644 --- a/clients/client-supplychain/src/commands/UpdateDataIntegrationFlowCommand.ts +++ b/clients/client-supplychain/src/commands/UpdateDataIntegrationFlowCommand.ts @@ -5,7 +5,12 @@ import { Command as $Command } from "@smithy/smithy-client"; import { MetadataBearer as __MetadataBearer } from "@smithy/types"; import { commonParams } from "../endpoint/EndpointParameters"; -import { UpdateDataIntegrationFlowRequest, UpdateDataIntegrationFlowResponse } from "../models/models_0"; +import { + UpdateDataIntegrationFlowRequest, + UpdateDataIntegrationFlowRequestFilterSensitiveLog, + UpdateDataIntegrationFlowResponse, + UpdateDataIntegrationFlowResponseFilterSensitiveLog, +} from "../models/models_0"; import { de_UpdateDataIntegrationFlowCommand, se_UpdateDataIntegrationFlowCommand } from "../protocols/Aws_restJson1"; import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; @@ -54,6 +59,17 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * options: { // DataIntegrationFlowDatasetOptions * loadType: "INCREMENTAL" || "REPLACE", * dedupeRecords: true || false, + * dedupeStrategy: { // DataIntegrationFlowDedupeStrategy + * type: "FIELD_PRIORITY", // required + * fieldPriority: { // DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration + * fields: [ // DataIntegrationFlowFieldPriorityDedupeFieldList // required + * { // DataIntegrationFlowFieldPriorityDedupeField + * name: "STRING_VALUE", // required + * sortOrder: "ASC" || "DESC", // required + * }, + * ], + * }, + * }, * }, * }, * }, @@ -78,6 +94,17 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * options: { * loadType: "INCREMENTAL" || "REPLACE", * dedupeRecords: true || false, + * dedupeStrategy: { + * type: "FIELD_PRIORITY", // required + * fieldPriority: { + * fields: [ // required + * { + * name: "STRING_VALUE", // required + * sortOrder: "ASC" || "DESC", // required + * }, + * ], + * }, + * }, * }, * }, * }, @@ -104,6 +131,17 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * // options: { // DataIntegrationFlowDatasetOptions * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { // DataIntegrationFlowDedupeStrategy + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { // DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration + * // fields: [ // DataIntegrationFlowFieldPriorityDedupeFieldList // required + * // { // DataIntegrationFlowFieldPriorityDedupeField + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -128,6 +166,17 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * // options: { * // loadType: "INCREMENTAL" || "REPLACE", * // dedupeRecords: true || false, + * // dedupeStrategy: { + * // type: "FIELD_PRIORITY", // required + * // fieldPriority: { + * // fields: [ // required + * // { + * // name: "STRING_VALUE", // required + * // sortOrder: "ASC" || "DESC", // required + * // }, + * // ], + * // }, + * // }, * // }, * // }, * // }, @@ -258,7 +307,22 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * ], * target: { * datasetTarget: { - * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + * options: { + * dedupeRecords: true, + * dedupeStrategy: { + * fieldPriority: { + * fields: [ + * { + * name: "eff_start_date", + * sortOrder: "ASC" + * } + * ] + * }, + * type: "FIELD_PRIORITY" + * }, + * loadType: "REPLACE" + * } * }, * targetType: "DATASET" * }, @@ -296,7 +360,22 @@ export interface UpdateDataIntegrationFlowCommandOutput extends UpdateDataIntegr * ], * target: { * datasetTarget: { - * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + * datasetIdentifier: "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + * options: { + * dedupeRecords: true, + * dedupeStrategy: { + * fieldPriority: { + * fields: [ + * { + * name: "eff_start_date", + * sortOrder: "ASC" + * } + * ] + * }, + * type: "FIELD_PRIORITY" + * }, + * loadType: "REPLACE" + * } * }, * targetType: "DATASET" * }, @@ -330,7 +409,7 @@ export class UpdateDataIntegrationFlowCommand extends $Command }) .s("GalaxyPublicAPIGateway", "UpdateDataIntegrationFlow", {}) .n("SupplyChainClient", "UpdateDataIntegrationFlowCommand") - .f(void 0, void 0) + .f(UpdateDataIntegrationFlowRequestFilterSensitiveLog, UpdateDataIntegrationFlowResponseFilterSensitiveLog) .ser(se_UpdateDataIntegrationFlowCommand) .de(de_UpdateDataIntegrationFlowCommand) .build() { diff --git a/clients/client-supplychain/src/commands/UpdateDataLakeDatasetCommand.ts b/clients/client-supplychain/src/commands/UpdateDataLakeDatasetCommand.ts index 684c4cd25345..59b88a873cd5 100644 --- a/clients/client-supplychain/src/commands/UpdateDataLakeDatasetCommand.ts +++ b/clients/client-supplychain/src/commands/UpdateDataLakeDatasetCommand.ts @@ -54,12 +54,27 @@ export interface UpdateDataLakeDatasetCommandOutput extends UpdateDataLakeDatase * // fields: [ // DataLakeDatasetSchemaFieldList // required * // { // DataLakeDatasetSchemaField * // name: "STRING_VALUE", // required - * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP", // required + * // type: "INT" || "DOUBLE" || "STRING" || "TIMESTAMP" || "LONG", // required * // isRequired: true || false, // required * // }, * // ], + * // primaryKeys: [ // DataLakeDatasetPrimaryKeyFieldList + * // { // DataLakeDatasetPrimaryKeyField + * // name: "STRING_VALUE", // required + * // }, + * // ], * // }, * // description: "STRING_VALUE", + * // partitionSpec: { // DataLakeDatasetPartitionSpec + * // fields: [ // DataLakeDatasetPartitionFieldList // required + * // { // DataLakeDatasetPartitionField + * // name: "STRING_VALUE", // required + * // transform: { // DataLakeDatasetPartitionFieldTransform + * // type: "YEAR" || "MONTH" || "DAY" || "HOUR" || "IDENTITY", // required + * // }, + * // }, + * // ], + * // }, * // createdTime: new Date("TIMESTAMP"), // required * // lastModifiedTime: new Date("TIMESTAMP"), // required * // }, @@ -300,6 +315,22 @@ export interface UpdateDataLakeDatasetCommandOutput extends UpdateDataLakeDatase * lastModifiedTime: 1.727117453568E9, * name: "my_dataset", * namespace: "default", + * partitionSpec: { + * fields: [ + * { + * name: "creation_time", + * transform: { + * type: "DAY" + * } + * }, + * { + * name: "description", + * transform: { + * type: "IDENTITY" + * } + * } + * ] + * }, * schema: { * fields: [ * { @@ -321,9 +352,19 @@ export interface UpdateDataLakeDatasetCommandOutput extends UpdateDataLakeDatase * isRequired: false, * name: "creation_time", * type: "TIMESTAMP" + * }, + * { + * isRequired: false, + * name: "quantity", + * type: "LONG" * } * ], - * name: "MyDataset" + * name: "MyDataset", + * primaryKeys: [ + * { + * name: "id" + * } + * ] * } * } * } diff --git a/clients/client-supplychain/src/commands/UpdateDataLakeNamespaceCommand.ts b/clients/client-supplychain/src/commands/UpdateDataLakeNamespaceCommand.ts new file mode 100644 index 000000000000..1e61a259c8f7 --- /dev/null +++ b/clients/client-supplychain/src/commands/UpdateDataLakeNamespaceCommand.ts @@ -0,0 +1,147 @@ +// smithy-typescript generated code +import { getEndpointPlugin } from "@smithy/middleware-endpoint"; +import { getSerdePlugin } from "@smithy/middleware-serde"; +import { Command as $Command } from "@smithy/smithy-client"; +import { MetadataBearer as __MetadataBearer } from "@smithy/types"; + +import { commonParams } from "../endpoint/EndpointParameters"; +import { UpdateDataLakeNamespaceRequest, UpdateDataLakeNamespaceResponse } from "../models/models_0"; +import { de_UpdateDataLakeNamespaceCommand, se_UpdateDataLakeNamespaceCommand } from "../protocols/Aws_restJson1"; +import { ServiceInputTypes, ServiceOutputTypes, SupplyChainClientResolvedConfig } from "../SupplyChainClient"; + +/** + * @public + */ +export type { __MetadataBearer }; +export { $Command }; +/** + * @public + * + * The input for {@link UpdateDataLakeNamespaceCommand}. + */ +export interface UpdateDataLakeNamespaceCommandInput extends UpdateDataLakeNamespaceRequest {} +/** + * @public + * + * The output of {@link UpdateDataLakeNamespaceCommand}. + */ +export interface UpdateDataLakeNamespaceCommandOutput extends UpdateDataLakeNamespaceResponse, __MetadataBearer {} + +/** + *Enables you to programmatically update an Amazon Web Services Supply Chain data lake namespace. Developers can update the description of a data lake namespace for a given instance ID and namespace name.
+ * @example + * Use a bare-bones client and the command you need to make an API call. + * ```javascript + * import { SupplyChainClient, UpdateDataLakeNamespaceCommand } from "@aws-sdk/client-supplychain"; // ES Modules import + * // const { SupplyChainClient, UpdateDataLakeNamespaceCommand } = require("@aws-sdk/client-supplychain"); // CommonJS import + * const client = new SupplyChainClient(config); + * const input = { // UpdateDataLakeNamespaceRequest + * instanceId: "STRING_VALUE", // required + * name: "STRING_VALUE", // required + * description: "STRING_VALUE", + * }; + * const command = new UpdateDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * // { // UpdateDataLakeNamespaceResponse + * // namespace: { // DataLakeNamespace + * // instanceId: "STRING_VALUE", // required + * // name: "STRING_VALUE", // required + * // arn: "STRING_VALUE", // required + * // description: "STRING_VALUE", + * // createdTime: new Date("TIMESTAMP"), // required + * // lastModifiedTime: new Date("TIMESTAMP"), // required + * // }, + * // }; + * + * ``` + * + * @param UpdateDataLakeNamespaceCommandInput - {@link UpdateDataLakeNamespaceCommandInput} + * @returns {@link UpdateDataLakeNamespaceCommandOutput} + * @see {@link UpdateDataLakeNamespaceCommandInput} for command's `input` shape. + * @see {@link UpdateDataLakeNamespaceCommandOutput} for command's `response` shape. + * @see {@link SupplyChainClientResolvedConfig | config} for SupplyChainClient's `config` shape. + * + * @throws {@link AccessDeniedException} (client fault) + *You do not have the required privileges to perform this action.
+ * + * @throws {@link InternalServerException} (server fault) + *Unexpected error during processing of request.
+ * + * @throws {@link ResourceNotFoundException} (client fault) + *Request references a resource which does not exist.
+ * + * @throws {@link ThrottlingException} (client fault) + *Request was denied due to request throttling.
+ * + * @throws {@link ValidationException} (client fault) + *The input does not satisfy the constraints specified by an AWS service.
+ * + * @throws {@link ConflictException} (client fault) + *Updating or deleting a resource can cause an inconsistent state.
+ * + * @throws {@link ServiceQuotaExceededException} (client fault) + *Request would cause a service quota to be exceeded.
+ * + * @throws {@link SupplyChainServiceException} + *Base exception class for all service exceptions from SupplyChain service.
+ * + * + * @example Update description of an existing AWS Supply Chain namespace + * ```javascript + * // + * const input = { + * description: "This is an updated AWS Supply Chain namespace", + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * name: "my_namespace" + * }; + * const command = new UpdateDataLakeNamespaceCommand(input); + * const response = await client.send(command); + * /* response is + * { + * namespace: { + * arn: "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + * createdTime: 1.736892560751E9, + * description: "This is an updated AWS Supply Chain namespace", + * instanceId: "1877dd20-dee9-4639-8e99-cb67acf21fe5", + * lastModifiedTime: 1.736892586156E9, + * name: "my_namespace" + * } + * } + * *\/ + * ``` + * + * @public + */ +export class UpdateDataLakeNamespaceCommand extends $Command + .classBuilder< + UpdateDataLakeNamespaceCommandInput, + UpdateDataLakeNamespaceCommandOutput, + SupplyChainClientResolvedConfig, + ServiceInputTypes, + ServiceOutputTypes + >() + .ep(commonParams) + .m(function (this: any, Command: any, cs: any, config: SupplyChainClientResolvedConfig, o: any) { + return [ + getSerdePlugin(config, this.serialize, this.deserialize), + getEndpointPlugin(config, Command.getEndpointParameterInstructions()), + ]; + }) + .s("GalaxyPublicAPIGateway", "UpdateDataLakeNamespace", {}) + .n("SupplyChainClient", "UpdateDataLakeNamespaceCommand") + .f(void 0, void 0) + .ser(se_UpdateDataLakeNamespaceCommand) + .de(de_UpdateDataLakeNamespaceCommand) + .build() { + /** @internal type navigation helper, not in runtime. */ + protected declare static __types: { + api: { + input: UpdateDataLakeNamespaceRequest; + output: UpdateDataLakeNamespaceResponse; + }; + sdk: { + input: UpdateDataLakeNamespaceCommandInput; + output: UpdateDataLakeNamespaceCommandOutput; + }; + }; +} diff --git a/clients/client-supplychain/src/commands/index.ts b/clients/client-supplychain/src/commands/index.ts index c000e1ee4464..0b8bc18d7c38 100644 --- a/clients/client-supplychain/src/commands/index.ts +++ b/clients/client-supplychain/src/commands/index.ts @@ -2,16 +2,24 @@ export * from "./CreateBillOfMaterialsImportJobCommand"; export * from "./CreateDataIntegrationFlowCommand"; export * from "./CreateDataLakeDatasetCommand"; +export * from "./CreateDataLakeNamespaceCommand"; export * from "./CreateInstanceCommand"; export * from "./DeleteDataIntegrationFlowCommand"; export * from "./DeleteDataLakeDatasetCommand"; +export * from "./DeleteDataLakeNamespaceCommand"; export * from "./DeleteInstanceCommand"; export * from "./GetBillOfMaterialsImportJobCommand"; +export * from "./GetDataIntegrationEventCommand"; export * from "./GetDataIntegrationFlowCommand"; +export * from "./GetDataIntegrationFlowExecutionCommand"; export * from "./GetDataLakeDatasetCommand"; +export * from "./GetDataLakeNamespaceCommand"; export * from "./GetInstanceCommand"; +export * from "./ListDataIntegrationEventsCommand"; +export * from "./ListDataIntegrationFlowExecutionsCommand"; export * from "./ListDataIntegrationFlowsCommand"; export * from "./ListDataLakeDatasetsCommand"; +export * from "./ListDataLakeNamespacesCommand"; export * from "./ListInstancesCommand"; export * from "./ListTagsForResourceCommand"; export * from "./SendDataIntegrationEventCommand"; @@ -19,4 +27,5 @@ export * from "./TagResourceCommand"; export * from "./UntagResourceCommand"; export * from "./UpdateDataIntegrationFlowCommand"; export * from "./UpdateDataLakeDatasetCommand"; +export * from "./UpdateDataLakeNamespaceCommand"; export * from "./UpdateInstanceCommand"; diff --git a/clients/client-supplychain/src/models/models_0.ts b/clients/client-supplychain/src/models/models_0.ts index 98c18021a73b..b8e3cef0c51b 100644 --- a/clients/client-supplychain/src/models/models_0.ts +++ b/clients/client-supplychain/src/models/models_0.ts @@ -266,6 +266,89 @@ export interface GetBillOfMaterialsImportJobResponse { job: BillOfMaterialsImportJob | undefined; } +/** + * @public + * @enum + */ +export const DataIntegrationFlowFieldPriorityDedupeSortOrder = { + ASC: "ASC", + DESC: "DESC", +} as const; + +/** + * @public + */ +export type DataIntegrationFlowFieldPriorityDedupeSortOrder = + (typeof DataIntegrationFlowFieldPriorityDedupeSortOrder)[keyof typeof DataIntegrationFlowFieldPriorityDedupeSortOrder]; + +/** + *The field used in the field priority deduplication strategy.
+ * @public + */ +export interface DataIntegrationFlowFieldPriorityDedupeField { + /** + *The name of the deduplication field. Must exist in the dataset and not be a primary key.
+ * @public + */ + name: string | undefined; + + /** + *The sort order for the deduplication field.
+ * @public + */ + sortOrder: DataIntegrationFlowFieldPriorityDedupeSortOrder | undefined; +} + +/** + *The field priority deduplication strategy details.
+ * @public + */ +export interface DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration { + /** + *The list of field names and their sort order for deduplication, arranged in descending priority from highest to lowest.
+ * @public + */ + fields: DataIntegrationFlowFieldPriorityDedupeField[] | undefined; +} + +/** + * @public + * @enum + */ +export const DataIntegrationFlowDedupeStrategyType = { + FIELD_PRIORITY: "FIELD_PRIORITY", +} as const; + +/** + * @public + */ +export type DataIntegrationFlowDedupeStrategyType = + (typeof DataIntegrationFlowDedupeStrategyType)[keyof typeof DataIntegrationFlowDedupeStrategyType]; + +/** + *The deduplication strategy details.
+ * @public + */ +export interface DataIntegrationFlowDedupeStrategy { + /** + *The type of the deduplication strategy.
+ *+ * FIELD_PRIORITY - Field priority configuration for the deduplication strategy specifies an ordered list of fields used to tie-break the data records sharing the same primary key values. Fields earlier in the list have higher priority for evaluation. For each field, the sort order determines whether to retain data record with larger or smaller field value.
+ *The field priority deduplication strategy.
+ * @public + */ + fieldPriority?: DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration | undefined; +} + /** * @public * @enum @@ -287,16 +370,33 @@ export type DataIntegrationFlowLoadType = */ export interface DataIntegrationFlowDatasetOptions { /** - *The dataset data load type in dataset options.
+ *The target dataset's data load type. This only affects how source S3 files are selected in the S3-to-dataset flow.
+ *+ * REPLACE - Target dataset will get replaced with the new file added under the source s3 prefix.
+ *+ * INCREMENTAL - Target dataset will get updated with the up-to-date content under S3 prefix incorporating any file additions or removals there.
+ *The dataset load option to remove duplicates.
+ *The option to perform deduplication on data records sharing same primary key values. If disabled, transformed data with duplicate primary key values will ingest into dataset, for datasets within asc namespace, such duplicates will cause ingestion fail. If enabled without dedupeStrategy, deduplication is done by retaining a random data record among those sharing the same primary key values. If enabled with dedupeStragtegy, the deduplication is done following the strategy.
+ *Note that target dataset may have partition configured, when dedupe is enabled, it only dedupe against primary keys and retain only one record out of those duplicates regardless of its partition status.
* @public */ dedupeRecords?: boolean | undefined; + + /** + *The deduplication strategy to dedupe the data records sharing same primary key values of the target dataset. This strategy only applies to target dataset with primary keys and with dedupeRecords option enabled. If transformed data still got duplicates after the dedupeStrategy evaluation, a random data record is chosen to be retained.
+ * @public + */ + dedupeStrategy?: DataIntegrationFlowDedupeStrategy | undefined; } /** @@ -357,7 +457,7 @@ export interface DataIntegrationFlowS3SourceConfiguration { bucketName: string | undefined; /** - *The prefix of the S3 source objects.
+ *The prefix of the S3 source objects. To trigger data ingestion, S3 files need to be put under s3://bucketName/prefix/.
The dataset DataIntegrationFlow target.
+ *The dataset DataIntegrationFlow target. Note that for AWS Supply Chain dataset under asc namespace, it has a connection_id internal field that is not allowed to be provided by client directly, they will be auto populated.
* @public */ datasetTarget?: DataIntegrationFlowDatasetTargetConfiguration | undefined; @@ -600,6 +700,88 @@ export interface CreateDataIntegrationFlowResponse { name: string | undefined; } +/** + * @public + * @enum + */ +export const DataLakeDatasetPartitionTransformType = { + DAY: "DAY", + HOUR: "HOUR", + IDENTITY: "IDENTITY", + MONTH: "MONTH", + YEAR: "YEAR", +} as const; + +/** + * @public + */ +export type DataLakeDatasetPartitionTransformType = + (typeof DataLakeDatasetPartitionTransformType)[keyof typeof DataLakeDatasetPartitionTransformType]; + +/** + *The detail of the partition field transformation.
+ * @public + */ +export interface DataLakeDatasetPartitionFieldTransform { + /** + *The type of partitioning transformation for this field. The available options are:
+ *+ * IDENTITY - Partitions data on a given field by its exact values.
+ *+ * YEAR - Partitions data on a timestamp field using year granularity.
+ *+ * MONTH - Partitions data on a timestamp field using month granularity.
+ *+ * DAY - Partitions data on a timestamp field using day granularity.
+ *+ * HOUR - Partitions data on a timestamp field using hour granularity.
+ *The detail of the partition field.
+ * @public + */ +export interface DataLakeDatasetPartitionField { + /** + *The name of the partition field.
+ * @public + */ + name: string | undefined; + + /** + *The transformation of the partition field. A transformation specifies how to partition on a given field. For example, with timestamp you can specify that you'd like to partition fields by day, e.g. data record with value 2025-01-03T00:00:00Z in partition field is in 2025-01-03 partition. Also noted that data record without any value in optional partition field is in NULL partition.
+ * @public + */ + transform: DataLakeDatasetPartitionFieldTransform | undefined; +} + +/** + *The partition specification for a dataset.
+ * @public + */ +export interface DataLakeDatasetPartitionSpec { + /** + *The fields on which to partition a dataset. The partitions will be applied hierarchically based on the order of this list.
+ * @public + */ + fields: DataLakeDatasetPartitionField[] | undefined; +} + /** * @public * @enum @@ -607,6 +789,7 @@ export interface CreateDataIntegrationFlowResponse { export const DataLakeDatasetSchemaFieldType = { DOUBLE: "DOUBLE", INT: "INT", + LONG: "LONG", STRING: "STRING", TIMESTAMP: "TIMESTAMP", } as const; @@ -642,7 +825,19 @@ export interface DataLakeDatasetSchemaField { } /** - *The schema details of the dataset.
+ *The detail of the primary key field.
+ * @public + */ +export interface DataLakeDatasetPrimaryKeyField { + /** + *The name of the primary key field.
+ * @public + */ + name: string | undefined; +} + +/** + *The schema details of the dataset. Note that for AWS Supply Chain dataset under asc namespace, it may have internal fields like connection_id that will be auto populated by data ingestion methods.
* @public */ export interface DataLakeDatasetSchema { @@ -657,6 +852,13 @@ export interface DataLakeDatasetSchema { * @public */ fields: DataLakeDatasetSchemaField[] | undefined; + + /** + *The list of primary key fields for the dataset. Primary keys defined can help data ingestion methods to ensure data uniqueness: CreateDataIntegrationFlow's dedupe strategy will leverage primary keys to perform records deduplication before write to dataset; SendDataIntegrationEvent's UPSERT and DELETE can only work with dataset with primary keys. For more details, refer to those data ingestion documentations.
+ *Note that defining primary keys does not necessarily mean the dataset cannot have duplicate records, duplicate records can still be ingested if CreateDataIntegrationFlow's dedupe disabled or through SendDataIntegrationEvent's APPEND operation.
+ * @public + */ + primaryKeys?: DataLakeDatasetPrimaryKeyField[] | undefined; } /** @@ -671,7 +873,7 @@ export interface CreateDataLakeDatasetRequest { instanceId: string | undefined; /** - *The name space of the dataset.
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -693,7 +895,7 @@ export interface CreateDataLakeDatasetRequest { name: string | undefined; /** - *
The custom schema of the data lake dataset and is only required when the name space is default.
+ *The custom schema of the data lake dataset and required for dataset in default and custom namespaces.
* @public */ schema?: DataLakeDatasetSchema | undefined; @@ -704,6 +906,12 @@ export interface CreateDataLakeDatasetRequest { */ description?: string | undefined; + /** + *The partition specification of the dataset. Partitioning can effectively improve the dataset query performance by reducing the amount of data scanned during query execution. But partitioning or not will affect how data get ingested by data ingestion methods, such as SendDataIntegrationEvent's dataset UPSERT will upsert records within partition (instead of within whole dataset). For more details, refer to those data ingestion documentations.
+ * @public + */ + partitionSpec?: DataLakeDatasetPartitionSpec | undefined; + /** *The tags of the dataset.
* @public @@ -723,7 +931,7 @@ export interface DataLakeDataset { instanceId: string | undefined; /** - *The name space of the dataset. The available values are:
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -739,7 +947,7 @@ export interface DataLakeDataset { namespace: string | undefined; /** - *
The name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
+ *The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
* @public */ name: string | undefined; @@ -762,6 +970,12 @@ export interface DataLakeDataset { */ description?: string | undefined; + /** + *The partition specification for a dataset.
+ * @public + */ + partitionSpec?: DataLakeDatasetPartitionSpec | undefined; + /** *The creation time of the dataset.
* @public @@ -787,6 +1001,91 @@ export interface CreateDataLakeDatasetResponse { dataset: DataLakeDataset | undefined; } +/** + *The request parameters for CreateDataLakeNamespace.
+ * @public + */ +export interface CreateDataLakeNamespaceRequest { + /** + *The Amazon Web Services Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The name of the namespace. Noted you cannot create namespace with name starting with asc, default, scn, aws, amazon, amzn + *
+ * @public + */ + name: string | undefined; + + /** + *The description of the namespace.
+ * @public + */ + description?: string | undefined; + + /** + *The tags of the namespace.
+ * @public + */ + tags?: RecordThe data lake namespace details.
+ * @public + */ +export interface DataLakeNamespace { + /** + *The Amazon Web Services Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The name of the namespace.
+ * @public + */ + name: string | undefined; + + /** + *The arn of the namespace.
+ * @public + */ + arn: string | undefined; + + /** + *The description of the namespace.
+ * @public + */ + description?: string | undefined; + + /** + *The creation time of the namespace.
+ * @public + */ + createdTime: Date | undefined; + + /** + *The last modified time of the namespace.
+ * @public + */ + lastModifiedTime: Date | undefined; +} + +/** + *The response parameters of CreateDataLakeNamespace.
+ * @public + */ +export interface CreateDataLakeNamespaceResponse { + /** + *The detail of created namespace.
+ * @public + */ + namespace: DataLakeNamespace | undefined; +} + /** *The request parameters for CreateInstance.
* @public @@ -935,54 +1234,143 @@ export interface CreateInstanceResponse { * @public * @enum */ -export const DataIntegrationEventType = { - FORECAST: "scn.data.forecast", - INBOUND_ORDER: "scn.data.inboundorder", - INBOUND_ORDER_LINE: "scn.data.inboundorderline", - INBOUND_ORDER_LINE_SCHEDULE: "scn.data.inboundorderlineschedule", - INVENTORY_LEVEL: "scn.data.inventorylevel", - OUTBOUND_ORDER_LINE: "scn.data.outboundorderline", - OUTBOUND_SHIPMENT: "scn.data.outboundshipment", - PROCESS_HEADER: "scn.data.processheader", - PROCESS_OPERATION: "scn.data.processoperation", - PROCESS_PRODUCT: "scn.data.processproduct", - RESERVATION: "scn.data.reservation", - SHIPMENT: "scn.data.shipment", - SHIPMENT_STOP: "scn.data.shipmentstop", - SHIPMENT_STOP_ORDER: "scn.data.shipmentstoporder", - SUPPLY_PLAN: "scn.data.supplyplan", +export const DataIntegrationEventDatasetLoadStatus = { + FAILED: "FAILED", + IN_PROGRESS: "IN_PROGRESS", + SUCCEEDED: "SUCCEEDED", } as const; /** * @public */ -export type DataIntegrationEventType = (typeof DataIntegrationEventType)[keyof typeof DataIntegrationEventType]; +export type DataIntegrationEventDatasetLoadStatus = + (typeof DataIntegrationEventDatasetLoadStatus)[keyof typeof DataIntegrationEventDatasetLoadStatus]; /** - *The request parameters for SendDataIntegrationEvent.
+ *The target dataset load execution details.
* @public */ -export interface SendDataIntegrationEventRequest { +export interface DataIntegrationEventDatasetLoadExecutionDetails { /** - *The AWS Supply Chain instance identifier.
+ *The event load execution status to target dataset.
* @public */ - instanceId: string | undefined; + status: DataIntegrationEventDatasetLoadStatus | undefined; /** - *The data event type.
+ *The failure message (if any) of failed event load execution to dataset.
* @public */ - eventType: DataIntegrationEventType | undefined; + message?: string | undefined; +} + +/** + * @public + * @enum + */ +export const DataIntegrationEventDatasetOperationType = { + APPEND: "APPEND", + DELETE: "DELETE", + UPSERT: "UPSERT", +} as const; + +/** + * @public + */ +export type DataIntegrationEventDatasetOperationType = + (typeof DataIntegrationEventDatasetOperationType)[keyof typeof DataIntegrationEventDatasetOperationType]; +/** + *The target dataset details for a DATASET event type.
+ * @public + */ +export interface DataIntegrationEventDatasetTargetDetails { /** - *The data payload of the event. For more information on the data schema to use, see Data entities supported in AWS Supply Chain.
+ *The datalake dataset ARN identifier.
* @public */ - data: string | undefined; + datasetIdentifier: string | undefined; + + /** + *The target dataset load operation type. The available options are:
+ *+ * APPEND - Add new records to the dataset. Noted that this operation type will just try to append records as-is without any primary key or partition constraints.
+ *+ * UPSERT - Modify existing records in the dataset with primary key configured, events for datasets without primary keys are not allowed. If event data contains primary keys that match records in the dataset within same partition, then those existing records (in that partition) will be updated. If primary keys do not match, new records will be added. Note that if dataset contain records with duplicate primary key values in the same partition, those duplicate records will be deduped into one updated record.
+ *+ * DELETE - Remove existing records in the dataset with primary key configured, events for datasets without primary keys are not allowed. If event data contains primary keys that match records in the dataset within same partition, then those existing records (in that partition) will be deleted. If primary keys do not match, no actions will be done. Note that if dataset contain records with duplicate primary key values in the same partition, all those duplicates will be removed.
+ *The target dataset load execution.
+ * @public + */ + datasetLoadExecution: DataIntegrationEventDatasetLoadExecutionDetails | undefined; +} + +/** + * @public + * @enum + */ +export const DataIntegrationEventType = { + DATASET: "scn.data.dataset", + FORECAST: "scn.data.forecast", + INBOUND_ORDER: "scn.data.inboundorder", + INBOUND_ORDER_LINE: "scn.data.inboundorderline", + INBOUND_ORDER_LINE_SCHEDULE: "scn.data.inboundorderlineschedule", + INVENTORY_LEVEL: "scn.data.inventorylevel", + OUTBOUND_ORDER_LINE: "scn.data.outboundorderline", + OUTBOUND_SHIPMENT: "scn.data.outboundshipment", + PROCESS_HEADER: "scn.data.processheader", + PROCESS_OPERATION: "scn.data.processoperation", + PROCESS_PRODUCT: "scn.data.processproduct", + RESERVATION: "scn.data.reservation", + SHIPMENT: "scn.data.shipment", + SHIPMENT_STOP: "scn.data.shipmentstop", + SHIPMENT_STOP_ORDER: "scn.data.shipmentstoporder", + SUPPLY_PLAN: "scn.data.supplyplan", +} as const; + +/** + * @public + */ +export type DataIntegrationEventType = (typeof DataIntegrationEventType)[keyof typeof DataIntegrationEventType]; + +/** + *The data integration event details.
+ * @public + */ +export interface DataIntegrationEvent { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The unique event identifier.
+ * @public + */ + eventId: string | undefined; /** - *Event identifier (for example, orderId for InboundOrder) used for data sharing or partitioning.
+ *The data event type.
+ * @public + */ + eventType: DataIntegrationEventType | undefined; + + /** + *Event identifier (for example, orderId for InboundOrder) used for data sharding or partitioning.
* @public */ eventGroupId: string | undefined; @@ -991,25 +1379,31 @@ export interface SendDataIntegrationEventRequest { *The event timestamp (in epoch seconds).
* @public */ - eventTimestamp?: Date | undefined; + eventTimestamp: Date | undefined; /** - *The idempotent client token.
+ *The target dataset details for a DATASET event type.
* @public */ - clientToken?: string | undefined; + datasetTargetDetails?: DataIntegrationEventDatasetTargetDetails | undefined; } /** - *The response parameters for SendDataIntegrationEvent.
+ *The target dataset configuration for a DATASET event type.
* @public */ -export interface SendDataIntegrationEventResponse { +export interface DataIntegrationEventDatasetTargetConfiguration { /** - *The unique event identifier.
+ *The datalake dataset ARN identifier.
* @public */ - eventId: string | undefined; + datasetIdentifier: string | undefined; + + /** + *The target dataset load operation type.
+ * @public + */ + operationType: DataIntegrationEventDatasetOperationType | undefined; } /** @@ -1060,6 +1454,148 @@ export interface DataIntegrationFlow { lastModifiedTime: Date | undefined; } +/** + *The details of a flow execution with dataset source.
+ * @public + */ +export interface DataIntegrationFlowDatasetSource { + /** + *The ARN of the dataset source.
+ * @public + */ + datasetIdentifier: string | undefined; +} + +/** + *The output metadata of the flow execution.
+ * @public + */ +export interface DataIntegrationFlowExecutionOutputMetadata { + /** + *The S3 URI under which all diagnostic files (such as deduped records if any) are stored.
+ * @public + */ + diagnosticReportsRootS3URI?: string | undefined; +} + +/** + *The details of a flow execution with S3 source.
+ * @public + */ +export interface DataIntegrationFlowS3Source { + /** + *The S3 bucket name of the S3 source.
+ * @public + */ + bucketName: string | undefined; + + /** + *The S3 object key of the S3 source.
+ * @public + */ + key: string | undefined; +} + +/** + *The source information of a flow execution.
+ * @public + */ +export interface DataIntegrationFlowExecutionSourceInfo { + /** + *The data integration flow execution source type.
+ * @public + */ + sourceType: DataIntegrationFlowSourceType | undefined; + + /** + *The source details of a flow execution with S3 source.
+ * @public + */ + s3Source?: DataIntegrationFlowS3Source | undefined; + + /** + *The source details of a flow execution with dataset source.
+ * @public + */ + datasetSource?: DataIntegrationFlowDatasetSource | undefined; +} + +/** + * @public + * @enum + */ +export const DataIntegrationFlowExecutionStatus = { + FAILED: "FAILED", + IN_PROGRESS: "IN_PROGRESS", + SUCCEEDED: "SUCCEEDED", +} as const; + +/** + * @public + */ +export type DataIntegrationFlowExecutionStatus = + (typeof DataIntegrationFlowExecutionStatus)[keyof typeof DataIntegrationFlowExecutionStatus]; + +/** + *The flow execution details.
+ * @public + */ +export interface DataIntegrationFlowExecution { + /** + *The flow execution's instanceId.
+ * @public + */ + instanceId: string | undefined; + + /** + *The flow execution's flowName.
+ * @public + */ + flowName: string | undefined; + + /** + *The flow executionId.
+ * @public + */ + executionId: string | undefined; + + /** + *The status of flow execution.
+ * @public + */ + status?: DataIntegrationFlowExecutionStatus | undefined; + + /** + *The source information for a flow execution.
+ * @public + */ + sourceInfo?: DataIntegrationFlowExecutionSourceInfo | undefined; + + /** + *The failure message (if any) of failed flow execution.
+ * @public + */ + message?: string | undefined; + + /** + *The flow execution start timestamp.
+ * @public + */ + startTime?: Date | undefined; + + /** + *The flow execution end timestamp.
+ * @public + */ + endTime?: Date | undefined; + + /** + *The flow execution output metadata.
+ * @public + */ + outputMetadata?: DataIntegrationFlowExecutionOutputMetadata | undefined; +} + /** *The request parameters for DeleteDataIntegrationFlow.
* @public @@ -1228,7 +1764,7 @@ export interface DeleteDataLakeDatasetRequest { instanceId: string | undefined; /** - *The name space of the dataset. The available values are:
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -1244,7 +1780,7 @@ export interface DeleteDataLakeDatasetRequest { namespace: string | undefined; /** - *
The name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
+ *The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
* @public */ name: string | undefined; @@ -1262,7 +1798,7 @@ export interface DeleteDataLakeDatasetResponse { instanceId: string | undefined; /** - *The name space of deleted dataset.
+ *The namespace of deleted dataset.
* @public */ namespace: string | undefined; @@ -1286,7 +1822,7 @@ export interface GetDataLakeDatasetRequest { instanceId: string | undefined; /** - *The name space of the dataset. The available values are:
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -1302,14 +1838,14 @@ export interface GetDataLakeDatasetRequest { namespace: string | undefined; /** - *
The name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
+ *The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
* @public */ name: string | undefined; } /** - *The response parameters for UpdateDataLakeDataset.
+ *The response parameters for GetDataLakeDataset.
* @public */ export interface GetDataLakeDatasetResponse { @@ -1332,7 +1868,7 @@ export interface ListDataLakeDatasetsRequest { instanceId: string | undefined; /** - *The name space of the dataset. The available values are:
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -1390,7 +1926,7 @@ export interface UpdateDataLakeDatasetRequest { instanceId: string | undefined; /** - *
The name space of the dataset. The available values are:
+ *The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
*@@ -1406,7 +1942,7 @@ export interface UpdateDataLakeDatasetRequest { namespace: string | undefined; /** - *
The name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
+ *The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
* @public */ name: string | undefined; @@ -1431,123 +1967,344 @@ export interface UpdateDataLakeDatasetResponse { } /** - *The request parameters for DeleteInstance.
+ *The request parameters of DeleteDataLakeNamespace.
* @public */ -export interface DeleteInstanceRequest { +export interface DeleteDataLakeNamespaceRequest { /** *The AWS Supply Chain instance identifier.
* @public */ instanceId: string | undefined; -} -/** - *The response parameters for DeleteInstance.
- * @public - */ -export interface DeleteInstanceResponse { /** - *The AWS Supply Chain instance resource data details.
+ *The name of the namespace. Noted you cannot delete pre-defined namespace like asc, default which are only deleted through instance deletion.
* @public */ - instance: Instance | undefined; + name: string | undefined; } /** - *The request parameters for GetInstance.
+ *The response parameters of DeleteDataLakeNamespace.
* @public */ -export interface GetInstanceRequest { +export interface DeleteDataLakeNamespaceResponse { /** - *The AWS Supply Chain instance identifier
+ *The AWS Supply Chain instance identifier.
* @public */ instanceId: string | undefined; + + /** + *The name of deleted namespace.
+ * @public + */ + name: string | undefined; } /** - *The response parameters for GetInstance.
+ *The request parameters for GetDataLakeNamespace.
* @public */ -export interface GetInstanceResponse { +export interface GetDataLakeNamespaceRequest { /** - *The instance resource data details.
+ *The Amazon Web Services Supply Chain instance identifier.
* @public */ - instance: Instance | undefined; + instanceId: string | undefined; + + /** + *The name of the namespace. Besides the namespaces user created, you can also specify the pre-defined namespaces:
+ *+ * asc - Pre-defined namespace containing Amazon Web Services Supply Chain supported datasets, see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
+ *+ * default - Pre-defined namespace containing datasets with custom user-defined schemas.
+ *The request parameters for ListInstances.
+ *The response parameters for GetDataLakeNamespace.
* @public */ -export interface ListInstancesRequest { +export interface GetDataLakeNamespaceResponse { /** - *The pagination token to fetch the next page of instances.
+ *The fetched namespace details.
* @public */ - nextToken?: string | undefined; + namespace: DataLakeNamespace | undefined; +} +/** + *The request parameters of ListDataLakeNamespaces.
+ * @public + */ +export interface ListDataLakeNamespacesRequest { /** - *Specify the maximum number of instances to fetch in this paginated request.
+ *The Amazon Web Services Supply Chain instance identifier.
* @public */ - maxResults?: number | undefined; + instanceId: string | undefined; /** - *The filter to ListInstances based on their names.
+ *The pagination token to fetch next page of namespaces.
* @public */ - instanceNameFilter?: string[] | undefined; + nextToken?: string | undefined; /** - *The filter to ListInstances based on their state.
+ *The max number of namespaces to fetch in this paginated request.
* @public */ - instanceStateFilter?: InstanceState[] | undefined; + maxResults?: number | undefined; } /** - *The response parameters for ListInstances.
+ *The response parameters of ListDataLakeNamespaces.
* @public */ -export interface ListInstancesResponse { +export interface ListDataLakeNamespacesResponse { /** - *The list of instances resource data details.
+ *The list of fetched namespace details. Noted it only contains custom namespaces, pre-defined namespaces are not included.
* @public */ - instances: Instance[] | undefined; + namespaces: DataLakeNamespace[] | undefined; /** - *The pagination token to fetch the next page of instances.
+ *The pagination token to fetch next page of namespaces.
* @public */ nextToken?: string | undefined; } /** - *The request parameters for UpdateInstance.
+ *The request parameters of UpdateDataLakeNamespace.
* @public */ -export interface UpdateInstanceRequest { +export interface UpdateDataLakeNamespaceRequest { /** - *The AWS Supply Chain instance identifier.
+ *The Amazon Web Services Chain instance identifier.
* @public */ instanceId: string | undefined; /** - *The AWS Supply Chain instance name.
+ *The name of the namespace. Noted you cannot update namespace with name starting with asc, default, scn, aws, amazon, amzn + *
* @public */ - instanceName?: string | undefined; + name: string | undefined; /** - *The AWS Supply Chain instance description.
+ *The updated description of the data lake namespace.
* @public */ - instanceDescription?: string | undefined; + description?: string | undefined; +} + +/** + *The response parameters of UpdateDataLakeNamespace.
+ * @public + */ +export interface UpdateDataLakeNamespaceResponse { + /** + *The updated namespace details.
+ * @public + */ + namespace: DataLakeNamespace | undefined; +} + +/** + *The request parameters for DeleteInstance.
+ * @public + */ +export interface DeleteInstanceRequest { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; +} + +/** + *The response parameters for DeleteInstance.
+ * @public + */ +export interface DeleteInstanceResponse { + /** + *The AWS Supply Chain instance resource data details.
+ * @public + */ + instance: Instance | undefined; +} + +/** + *The request parameters for GetDataIntegrationEvent.
+ * @public + */ +export interface GetDataIntegrationEventRequest { + /** + *The Amazon Web Services Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The unique event identifier.
+ * @public + */ + eventId: string | undefined; +} + +/** + *The response parameters for GetDataIntegrationEvent.
+ * @public + */ +export interface GetDataIntegrationEventResponse { + /** + *The details of the DataIntegrationEvent returned.
+ * @public + */ + event: DataIntegrationEvent | undefined; +} + +/** + *The request parameters of GetFlowExecution.
+ * @public + */ +export interface GetDataIntegrationFlowExecutionRequest { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The flow name.
+ * @public + */ + flowName: string | undefined; + + /** + *The flow execution identifier.
+ * @public + */ + executionId: string | undefined; +} + +/** + *The response parameters of GetFlowExecution.
+ * @public + */ +export interface GetDataIntegrationFlowExecutionResponse { + /** + *The flow execution details.
+ * @public + */ + flowExecution: DataIntegrationFlowExecution | undefined; +} + +/** + *The request parameters for GetInstance.
+ * @public + */ +export interface GetInstanceRequest { + /** + *The AWS Supply Chain instance identifier
+ * @public + */ + instanceId: string | undefined; +} + +/** + *The response parameters for GetInstance.
+ * @public + */ +export interface GetInstanceResponse { + /** + *The instance resource data details.
+ * @public + */ + instance: Instance | undefined; +} + +/** + *The request parameters for ListInstances.
+ * @public + */ +export interface ListInstancesRequest { + /** + *The pagination token to fetch the next page of instances.
+ * @public + */ + nextToken?: string | undefined; + + /** + *Specify the maximum number of instances to fetch in this paginated request.
+ * @public + */ + maxResults?: number | undefined; + + /** + *The filter to ListInstances based on their names.
+ * @public + */ + instanceNameFilter?: string[] | undefined; + + /** + *The filter to ListInstances based on their state.
+ * @public + */ + instanceStateFilter?: InstanceState[] | undefined; +} + +/** + *The response parameters for ListInstances.
+ * @public + */ +export interface ListInstancesResponse { + /** + *The list of instances resource data details.
+ * @public + */ + instances: Instance[] | undefined; + + /** + *The pagination token to fetch the next page of instances.
+ * @public + */ + nextToken?: string | undefined; +} + +/** + *The request parameters for UpdateInstance.
+ * @public + */ +export interface UpdateInstanceRequest { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The AWS Supply Chain instance name.
+ * @public + */ + instanceName?: string | undefined; + + /** + *The AWS Supply Chain instance description.
+ * @public + */ + instanceDescription?: string | undefined; } /** @@ -1562,6 +2319,102 @@ export interface UpdateInstanceResponse { instance: Instance | undefined; } +/** + *The request parameters for ListDataIntegrationEvents.
+ * @public + */ +export interface ListDataIntegrationEventsRequest { + /** + *The Amazon Web Services Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *List data integration events for the specified eventType.
+ * @public + */ + eventType?: DataIntegrationEventType | undefined; + + /** + *The pagination token to fetch the next page of the data integration events.
+ * @public + */ + nextToken?: string | undefined; + + /** + *Specify the maximum number of data integration events to fetch in one paginated request.
+ * @public + */ + maxResults?: number | undefined; +} + +/** + *The response parameters for ListDataIntegrationEvents.
+ * @public + */ +export interface ListDataIntegrationEventsResponse { + /** + *The list of data integration events.
+ * @public + */ + events: DataIntegrationEvent[] | undefined; + + /** + *The pagination token to fetch the next page of the ListDataIntegrationEvents.
+ * @public + */ + nextToken?: string | undefined; +} + +/** + *The request parameters of ListFlowExecutions.
+ * @public + */ +export interface ListDataIntegrationFlowExecutionsRequest { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The flow name.
+ * @public + */ + flowName: string | undefined; + + /** + *The pagination token to fetch next page of flow executions.
+ * @public + */ + nextToken?: string | undefined; + + /** + *The number to specify the max number of flow executions to fetch in this paginated request.
+ * @public + */ + maxResults?: number | undefined; +} + +/** + *The response parameters of ListFlowExecutions.
+ * @public + */ +export interface ListDataIntegrationFlowExecutionsResponse { + /** + *The list of flow executions.
+ * @public + */ + flowExecutions: DataIntegrationFlowExecution[] | undefined; + + /** + *The pagination token to fetch next page of flow executions.
+ * @public + */ + nextToken?: string | undefined; +} + /** *The request parameters of ListTagsForResource.
* @public @@ -1586,6 +2439,133 @@ export interface ListTagsForResourceResponse { tags: RecordThe request parameters for SendDataIntegrationEvent.
+ * @public + */ +export interface SendDataIntegrationEventRequest { + /** + *The AWS Supply Chain instance identifier.
+ * @public + */ + instanceId: string | undefined; + + /** + *The data event type.
+ *+ * scn.data.dataset - Send data directly to any specified dataset.
+ *+ * scn.data.supplyplan - Send data to supply_plan dataset.
+ *+ * scn.data.shipmentstoporder - Send data to shipment_stop_order dataset.
+ *+ * scn.data.shipmentstop - Send data to shipment_stop dataset.
+ *+ * scn.data.shipment - Send data to shipment dataset.
+ *+ * scn.data.reservation - Send data to reservation dataset.
+ *+ * scn.data.processproduct - Send data to process_product dataset.
+ *+ * scn.data.processoperation - Send data to process_operation dataset.
+ *+ * scn.data.processheader - Send data to process_header dataset.
+ *+ * scn.data.forecast - Send data to forecast dataset.
+ *+ * scn.data.inventorylevel - Send data to inv_level dataset.
+ *+ * scn.data.inboundorder - Send data to inbound_order dataset.
+ *+ * scn.data.inboundorderline - Send data to inbound_order_line dataset.
+ *+ * scn.data.inboundorderlineschedule - Send data to inbound_order_line_schedule dataset.
+ *+ * scn.data.outboundorderline - Send data to outbound_order_line dataset.
+ *+ * scn.data.outboundshipment - Send data to outbound_shipment dataset.
+ *The data payload of the event, should follow the data schema of the target dataset, or see Data entities supported in AWS Supply Chain. To send single data record, use JsonObject format; to send multiple data records, use JsonArray format.
+ *Note that for AWS Supply Chain dataset under asc namespace, it has a connection_id internal field that is not allowed to be provided by client directly, they will be auto populated.
+ * @public + */ + data: string | undefined; + + /** + *Event identifier (for example, orderId for InboundOrder) used for data sharding or partitioning. Noted under one eventGroupId of same eventType and instanceId, events are processed sequentially in the order they are received by the server.
+ * @public + */ + eventGroupId: string | undefined; + + /** + *The timestamp (in epoch seconds) associated with the event. If not provided, it will be assigned with current timestamp.
+ * @public + */ + eventTimestamp?: Date | undefined; + + /** + *The idempotent client token. The token is active for 8 hours, and within its lifetime, it ensures the request completes only once upon retry with same client token. If omitted, the AWS SDK generates a unique value so that AWS SDK can safely retry the request upon network errors.
+ * @public + */ + clientToken?: string | undefined; + + /** + *The target dataset configuration for scn.data.dataset event type.
+ * @public + */ + datasetTarget?: DataIntegrationEventDatasetTargetConfiguration | undefined; +} + +/** + *The response parameters for SendDataIntegrationEvent.
+ * @public + */ +export interface SendDataIntegrationEventResponse { + /** + *The unique event identifier.
+ * @public + */ + eventId: string | undefined; +} + /** *The request parameters of TagResource.
* @public @@ -1634,6 +2614,80 @@ export interface UntagResourceRequest { */ export interface UntagResourceResponse {} +/** + * @internal + */ +export const DataIntegrationFlowSQLTransformationConfigurationFilterSensitiveLog = ( + obj: DataIntegrationFlowSQLTransformationConfiguration +): any => ({ + ...obj, + ...(obj.query && { query: SENSITIVE_STRING }), +}); + +/** + * @internal + */ +export const DataIntegrationFlowTransformationFilterSensitiveLog = (obj: DataIntegrationFlowTransformation): any => ({ + ...obj, + ...(obj.sqlTransformation && { + sqlTransformation: DataIntegrationFlowSQLTransformationConfigurationFilterSensitiveLog(obj.sqlTransformation), + }), +}); + +/** + * @internal + */ +export const CreateDataIntegrationFlowRequestFilterSensitiveLog = (obj: CreateDataIntegrationFlowRequest): any => ({ + ...obj, + ...(obj.transformation && { + transformation: DataIntegrationFlowTransformationFilterSensitiveLog(obj.transformation), + }), +}); + +/** + * @internal + */ +export const DataIntegrationFlowFilterSensitiveLog = (obj: DataIntegrationFlow): any => ({ + ...obj, + ...(obj.transformation && { + transformation: DataIntegrationFlowTransformationFilterSensitiveLog(obj.transformation), + }), +}); + +/** + * @internal + */ +export const GetDataIntegrationFlowResponseFilterSensitiveLog = (obj: GetDataIntegrationFlowResponse): any => ({ + ...obj, + ...(obj.flow && { flow: DataIntegrationFlowFilterSensitiveLog(obj.flow) }), +}); + +/** + * @internal + */ +export const ListDataIntegrationFlowsResponseFilterSensitiveLog = (obj: ListDataIntegrationFlowsResponse): any => ({ + ...obj, + ...(obj.flows && { flows: obj.flows.map((item) => DataIntegrationFlowFilterSensitiveLog(item)) }), +}); + +/** + * @internal + */ +export const UpdateDataIntegrationFlowRequestFilterSensitiveLog = (obj: UpdateDataIntegrationFlowRequest): any => ({ + ...obj, + ...(obj.transformation && { + transformation: DataIntegrationFlowTransformationFilterSensitiveLog(obj.transformation), + }), +}); + +/** + * @internal + */ +export const UpdateDataIntegrationFlowResponseFilterSensitiveLog = (obj: UpdateDataIntegrationFlowResponse): any => ({ + ...obj, + ...(obj.flow && { flow: DataIntegrationFlowFilterSensitiveLog(obj.flow) }), +}); + /** * @internal */ diff --git a/clients/client-supplychain/src/pagination/ListDataIntegrationEventsPaginator.ts b/clients/client-supplychain/src/pagination/ListDataIntegrationEventsPaginator.ts new file mode 100644 index 000000000000..aa2dedcc6559 --- /dev/null +++ b/clients/client-supplychain/src/pagination/ListDataIntegrationEventsPaginator.ts @@ -0,0 +1,24 @@ +// smithy-typescript generated code +import { createPaginator } from "@smithy/core"; +import { Paginator } from "@smithy/types"; + +import { + ListDataIntegrationEventsCommand, + ListDataIntegrationEventsCommandInput, + ListDataIntegrationEventsCommandOutput, +} from "../commands/ListDataIntegrationEventsCommand"; +import { SupplyChainClient } from "../SupplyChainClient"; +import { SupplyChainPaginationConfiguration } from "./Interfaces"; + +/** + * @public + */ +export const paginateListDataIntegrationEvents: ( + config: SupplyChainPaginationConfiguration, + input: ListDataIntegrationEventsCommandInput, + ...rest: any[] +) => PaginatorA list of accelerator capabilities requested for this fleet. Only Amazon Elastic Compute Cloud instances\n that provide these capabilities will be used. For example, if you specify both L4 and T4\n chips, Deadline Cloud will use Amazon EC2 instances that have either the L4 or the T4 chip\n installed.
", + "smithy.api#documentation": "A list of accelerator capabilities requested for this fleet. Only Amazon Elastic Compute Cloud instances that provide these capabilities will be used. For example, if you specify both L4 and T4 chips, Deadline Cloud will use Amazon EC2 instances that have either the L4 or the T4 chip installed.
", "smithy.api#required": {} } }, @@ -34,7 +34,7 @@ } }, "traits": { - "smithy.api#documentation": "Provides information about the GPU accelerators used for jobs processed by a\n fleet.
" + "smithy.api#documentation": "Provides information about the GPU accelerators used for jobs processed by a fleet.
" } }, "com.amazonaws.deadline#AcceleratorCountRange": { @@ -55,7 +55,7 @@ } }, "traits": { - "smithy.api#documentation": "Defines the maximum and minimum number of GPU accelerators required for a worker\n instance..
" + "smithy.api#documentation": "Defines the maximum and minimum number of GPU accelerators required for a worker instance..
" } }, "com.amazonaws.deadline#AcceleratorName": { @@ -102,7 +102,7 @@ "name": { "target": "com.amazonaws.deadline#AcceleratorName", "traits": { - "smithy.api#documentation": "The name of the chip used by the GPU accelerator.
\nIf you specify l4 as the name of the accelerator, you must specify\n latest or grid:r550 as the runtime.
The available GPU accelerators are:
\n\n t4 - NVIDIA T4 Tensor Core GPU
\n a10g - NVIDIA A10G Tensor Core GPU
\n l4 - NVIDIA L4 Tensor Core GPU
\n l40s - NVIDIA L40S Tensor Core GPU
The name of the chip used by the GPU accelerator.
If you specify l4 as the name of the accelerator, you must specify latest or grid:r550 as the runtime.
The available GPU accelerators are:
t4 - NVIDIA T4 Tensor Core GPU
a10g - NVIDIA A10G Tensor Core GPU
l4 - NVIDIA L4 Tensor Core GPU
l40s - NVIDIA L40S Tensor Core GPU
Specifies the runtime driver to use for the GPU accelerator. You must use the same\n runtime for all GPUs.
\nYou can choose from the following runtimes:
\n\n latest - Use the latest runtime available for the chip. If you\n specify latest and a new version of the runtime is released, the new\n version of the runtime is used.
\n grid:r550 - NVIDIA vGPU software 17\n
\n grid:r535 - NVIDIA vGPU software 16\n
If you don't specify a runtime, Deadline Cloud uses latest as the default. However,\n if you have multiple accelerators and specify latest for some and leave others\n blank, Deadline Cloud raises an exception.
Specifies the runtime driver to use for the GPU accelerator. You must use the same runtime for all GPUs.
You can choose from the following runtimes:
latest - Use the latest runtime available for the chip. If you specify latest and a new version of the runtime is released, the new version of the runtime is used.
grid:r550 - NVIDIA vGPU software 17
grid:r535 - NVIDIA vGPU software 16
If you don't specify a runtime, Deadline Cloud uses latest as the default. However, if you have multiple accelerators and specify latest for some and leave others blank, Deadline Cloud raises an exception.
Defines the maximum and minimum amount of memory, in MiB, to use for the\n accelerator.
" + "smithy.api#documentation": "Defines the maximum and minimum amount of memory, in MiB, to use for the accelerator.
" } }, "com.amazonaws.deadline#AcceleratorType": { @@ -915,7 +915,7 @@ "documentation": "Grants permission to assume a fleet role for read-only access", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Get Amazon Web Services credentials from the fleet role. The IAM permissions of the credentials are\n scoped down to have read-only access.
", + "smithy.api#documentation": "Get Amazon Web Services credentials from the fleet role. The IAM permissions of the credentials are scoped down to have read-only access.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -1089,7 +1089,7 @@ "documentation": "Grants permission to assume a queue role for read-only access", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Gets Amazon Web Services credentials from the queue role. The IAM permissions of the credentials are\n scoped down to have read-only access.
", + "smithy.api#documentation": "Gets Amazon Web Services credentials from the queue role. The IAM permissions of the credentials are scoped down to have read-only access.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -1525,7 +1525,7 @@ "farmId": { "target": "com.amazonaws.deadline#FarmId", "traits": { - "smithy.api#documentation": "The farm ID of the worker that's fetching job details. The worker must have an\n assignment on a job to fetch job details.
", + "smithy.api#documentation": "The farm ID of the worker that's fetching job details. The worker must have an assignment on a job to fetch job details.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -1533,7 +1533,7 @@ "fleetId": { "target": "com.amazonaws.deadline#FleetId", "traits": { - "smithy.api#documentation": "The fleet ID of the worker that's fetching job details. The worker must have an\n assignment on a job to fetch job details.
", + "smithy.api#documentation": "The fleet ID of the worker that's fetching job details. The worker must have an assignment on a job to fetch job details.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -1609,7 +1609,7 @@ "description": { "target": "com.amazonaws.deadline#Description", "traits": { - "smithy.api#documentation": "A description for the budget action to add.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nA description for the budget action to add.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the budget.
\n\n ACTIVE–The budget is being evaluated.
\n INACTIVE–The budget is inactive. This can include Expired,\n Canceled, or deleted Deleted statuses.
The status of the budget.
ACTIVE–The budget is being evaluated.
INACTIVE–The budget is inactive. This can include Expired, Canceled, or deleted Deleted statuses.
The display name of the budget summary to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the budget summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget summary.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the budget summary.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Your request has conflicting operations. This can occur if you're trying to perform more\n than one operation on the same resource at the same time.
", + "smithy.api#documentation": "Your request has conflicting operations. This can occur if you're trying to perform more than one operation on the same resource at the same time.
", "smithy.api#error": "client", "smithy.api#httpError": 409 } @@ -2122,7 +2122,7 @@ "targetS3Location": { "target": "com.amazonaws.deadline#S3Location", "traits": { - "smithy.api#documentation": "The Amazon S3 bucket name and key where you would like to add a copy of the job\n template.
", + "smithy.api#documentation": "The Amazon S3 bucket name and key where you would like to add a copy of the job template.
", "smithy.api#required": {} } } @@ -2238,7 +2238,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the budget.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Creates a farm to allow space for queues and fleets. Farms are the space where the\n components of your renders gather and are pieced together in the cloud. Farms contain\n budgets and allow you to enforce permissions. Deadline Cloud farms are a useful container for\n large projects.
", + "smithy.api#documentation": "Creates a farm to allow space for queues and fleets. Farms are the space where the components of your renders gather and are pieced together in the cloud. Farms contain budgets and allow you to enforce permissions. Deadline Cloud farms are a useful container for large projects.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -2351,7 +2351,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the farm.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Creates a fleet. Fleets gather information relating to compute, or capacity, for renders\n within your farms. You can choose to manage your own capacity or opt to have fleets fully\n managed by Deadline Cloud.
", + "smithy.api#documentation": "Creates a fleet. Fleets gather information relating to compute, or capacity, for renders within your farms. You can choose to manage your own capacity or opt to have fleets fully managed by Deadline Cloud.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -2468,7 +2468,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the fleet.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of workers for the fleet.
", + "smithy.api#documentation": "The maximum number of workers for the fleet.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
The configuration settings for the fleet. Customer managed fleets are self-managed.\n Service managed Amazon EC2 fleets are managed by Deadline Cloud.
", + "smithy.api#documentation": "The configuration settings for the fleet. Customer managed fleets are self-managed. Service managed Amazon EC2 fleets are managed by Deadline Cloud.
", "smithy.api#required": {} } }, @@ -2512,6 +2512,12 @@ "traits": { "smithy.api#documentation": "Each tag consists of a tag key and a tag value. Tag keys and values are both required, but tag values can be empty strings.
" } + }, + "hostConfiguration": { + "target": "com.amazonaws.deadline#HostConfiguration", + "traits": { + "smithy.api#documentation": "Provides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
" + } } }, "traits": { @@ -2567,7 +2573,7 @@ "documentation": "Grants permission to create a job", "requiredActions": ["deadline:GetJobTemplate", "identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Creates a job. A job is a set of instructions that Deadline Cloud uses to schedule\n and run work on available workers. For more information, see Deadline Cloud\n jobs.
", + "smithy.api#documentation": "Creates a job. A job is a set of instructions that Deadline Cloud uses to schedule and run work on available workers. For more information, see Deadline Cloud jobs.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -2621,7 +2627,7 @@ "priority": { "target": "com.amazonaws.deadline#JobPriority", "traits": { - "smithy.api#documentation": "The priority of the job. The highest priority (first scheduled) is 100. When two jobs\n have the same priority, the oldest job is scheduled first.
", + "smithy.api#documentation": "The priority of the job. The highest priority (first scheduled) is 100. When two jobs have the same priority, the oldest job is scheduled first.
", "smithy.api#required": {} } }, @@ -2634,7 +2640,7 @@ "attachments": { "target": "com.amazonaws.deadline#Attachments", "traits": { - "smithy.api#documentation": "The attachments for the job. Attach files required for the job to run to a render\n job.
" + "smithy.api#documentation": "The attachments for the job. Attach files required for the job to run to a render job.
" } }, "storageProfileId": { @@ -2647,7 +2653,7 @@ "target": "com.amazonaws.deadline#CreateJobTargetTaskRunStatus", "traits": { "smithy.api#default": "READY", - "smithy.api#documentation": "The initial job status when it is created. Jobs that are created with a\n SUSPENDED status will not run until manually requeued.
The initial job status when it is created. Jobs that are created with a SUSPENDED status will not run until manually requeued.
The maximum number of worker hosts that can concurrently process a job. When the\n maxWorkerCount is reached, no more workers will be assigned to process the\n job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no\n maximum number of workers.
If you don't specify the maxWorkerCount, Deadline Cloud won't throttle\n the number of workers used to process the job.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, Deadline Cloud won't throttle the number of workers used to process the job.
Creates a license endpoint to integrate your various licensed software used for\n rendering on Deadline Cloud.
", + "smithy.api#documentation": "Creates a license endpoint to integrate your various licensed software used for rendering on Deadline Cloud.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -2865,7 +2871,7 @@ "documentation": "Grants permission to create a limit for a farm", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Creates a limit that manages the distribution of shared resources, such as floating\n licenses. A limit can throttle work assignments, help manage workloads, and track current\n usage. Before you use a limit, you must associate the limit with one or more queues.
\nYou must add the amountRequirementName to a step in a job template to\n declare the limit requirement.
Creates a limit that manages the distribution of shared resources, such as floating licenses. A limit can throttle work assignments, help manage workloads, and track current usage. Before you use a limit, you must associate the limit with one or more queues.
You must add the amountRequirementName to a step in a job template to declare the limit requirement.
The display name of the limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of\n the hostRequirements in a step of a job template to declare the limit\n requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are\n in use, steps that require the limit won't be scheduled until the resource is\n available.
\nThe maxCount must not be 0. If the value is -1, there is no restriction on\n the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxCount must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
A description of the limit. A description helps you identify the purpose of the\n limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nA description of the limit. A description helps you identify the purpose of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
A unique identifier for the limit. Use this identifier in other operations, such as\n CreateQueueLimitAssociation and DeleteLimit.
A unique identifier for the limit. Use this identifier in other operations, such as CreateQueueLimitAssociation and DeleteLimit.
Creates an Amazon Web Services Deadline Cloud monitor that you can use to view your farms, queues, and\n fleets. After you submit a job, you can track the progress of the tasks and steps that make\n up the job, and then download the job's results.
", + "smithy.api#documentation": "Creates an Amazon Web Services Deadline Cloud monitor that you can use to view your farms, queues, and fleets. After you submit a job, you can track the progress of the tasks and steps that make up the job, and then download the job's results.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -3009,7 +3015,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The name that you give the monitor that is displayed in the Deadline Cloud console.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe name that you give the monitor that is displayed in the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain to use when creating the monitor URL. The full URL of the monitor is\n subdomain.Region.deadlinecloud.amazonaws.com.
", + "smithy.api#documentation": "The subdomain to use when creating the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
", "smithy.api#required": {} } }, "roleArn": { "target": "com.amazonaws.deadline#IamRoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that the monitor uses to connect to Deadline Cloud. Every user\n that signs in to the monitor using IAM Identity Center uses this role to access Deadline Cloud\n resources.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that the monitor uses to connect to Deadline Cloud. Every user that signs in to the monitor using IAM Identity Center uses this role to access Deadline Cloud resources.
", "smithy.api#required": {} } } @@ -3102,7 +3108,7 @@ "s3:ListBucket" ] }, - "smithy.api#documentation": "Creates a queue to coordinate the order in which jobs run on a farm. A queue can also\n specify where to pull resources and indicate where to output completed jobs.
", + "smithy.api#documentation": "Creates a queue to coordinate the order in which jobs run on a farm. A queue can also specify where to pull resources and indicate where to output completed jobs.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -3190,7 +3196,7 @@ "priority": { "target": "com.amazonaws.deadline#Priority", "traits": { - "smithy.api#documentation": "Sets the priority of the environments in the queue from 0 to 10,000, where 0 is the\n highest priority (activated first and deactivated last). If two environments share the same\n priority value, the environment created first takes higher priority.
", + "smithy.api#documentation": "Sets the priority of the environments in the queue from 0 to 10,000, where 0 is the highest priority (activated first and deactivated last). If two environments share the same priority value, the environment created first takes higher priority.
", "smithy.api#required": {} } }, @@ -3347,7 +3353,7 @@ "documentation": "Grants permission to create a queue-limit association", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Associates a limit with a particular queue. After the limit is associated, all workers\n for jobs that specify the limit associated with the queue are subject to the limit. You\n can't associate two limits with the same amountRequirementName to the same\n queue.
Associates a limit with a particular queue. After the limit is associated, all workers for jobs that specify the limit associated with the queue are subject to the limit. You can't associate two limits with the same amountRequirementName to the same queue.
The display name of the queue.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The job attachment settings for the queue. These are the Amazon S3 bucket name and the Amazon S3\n prefix.
" + "smithy.api#documentation": "The job attachment settings for the queue. These are the Amazon S3 bucket name and the Amazon S3 prefix.
" } }, "roleArn": { @@ -3534,7 +3540,7 @@ "documentation": "Grants permission to create a storage profile for a farm", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Creates a storage profile that specifies the operating system, file type, and file\n location of resources used on a farm.
", + "smithy.api#documentation": "Creates a storage profile that specifies the operating system, file type, and file location of resources used on a farm.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -3568,7 +3574,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the storage profile.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the storage profile.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Creates a worker. A worker tells your instance how much processing power (vCPU), and\n memory (GiB) you’ll need to assemble the digital assets held within a particular instance.\n You can specify certain instance types to use, or let the worker know which instances types\n to exclude.
", + "smithy.api#documentation": "Creates a worker. A worker tells your instance how much processing power (vCPU), and memory (GiB) you’ll need to assemble the digital assets held within a particular instance. You can specify certain instance types to use, or let the worker know which instances types to exclude.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
Specifies whether tags associated with a fleet are attached to workers when the worker\n is launched.
\nWhen the tagPropagationMode is set to\n PROPAGATE_TAGS_TO_WORKERS_AT_LAUNCH any tag associated with a fleet is\n attached to workers when they launch. If the tags for a fleet change, the tags associated\n with running workers do not change.
If you don't specify tagPropagationMode, the default is\n NO_PROPAGATION.
Specifies whether tags associated with a fleet are attached to workers when the worker is launched.
When the tagPropagationMode is set to PROPAGATE_TAGS_TO_WORKERS_AT_LAUNCH any tag associated with a fleet is attached to workers when they launch. If the tags for a fleet change, the tags associated with running workers do not change.
If you don't specify tagPropagationMode, the default is NO_PROPAGATION.
The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your\n projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions\n specific to their job function.
\nWith Deadline Cloud, content production teams can deploy resources for their workforce\n securely in the cloud, reducing the costs of added physical infrastructure. Keep your\n content production operations secure, while allowing your contributors to access the tools\n they need, such as scalable high-speed storage, licenses, and cost management\n services.
", + "smithy.api#documentation": "The Amazon Web Services Deadline Cloud API provides infrastructure and centralized management for your projects. Use the Deadline Cloud API to onboard users, assign projects, and attach permissions specific to their job function.
With Deadline Cloud, content production teams can deploy resources for their workforce securely in the cloud, reducing the costs of added physical infrastructure. Keep your content production operations secure, while allowing your contributors to access the tools they need, such as scalable high-speed storage, licenses, and cost management services.
", "smithy.api#title": "AWSDeadlineCloud", "smithy.rules#endpointRuleSet": { "version": "1.0", @@ -5090,7 +5096,7 @@ "documentation": "Grants permission to delete a limit", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Removes a limit from the specified farm. Before you delete a limit you must use the\n DeleteQueueLimitAssociation operation to remove the association with any\n queues.
Removes a limit from the specified farm. Before you delete a limit you must use the DeleteQueueLimitAssociation operation to remove the association with any queues.
Removes a Deadline Cloud monitor. After you delete a monitor, you can create a new one and\n attach farms to the monitor.
", + "smithy.api#documentation": "Removes a Deadline Cloud monitor. After you delete a monitor, you can create a new one and attach farms to the monitor.
", "smithy.api#endpoint": { "hostPrefix": "management." }, @@ -5257,7 +5263,7 @@ "monitorId": { "target": "com.amazonaws.deadline#MonitorId", "traits": { - "smithy.api#documentation": "The unique identifier of the monitor to delete. This ID is returned by the\n CreateMonitor operation, and is included in the response to the\n GetMonitor operation.
The unique identifier of the monitor to delete. This ID is returned by the CreateMonitor operation, and is included in the response to the GetMonitor operation.
Deletes a queue.
\nYou can't recover the jobs in a queue if you delete the queue. Deleting the queue\n also deletes the jobs in that queue.
\nDeletes a queue.
You can't recover the jobs in a queue if you delete the queue. Deleting the queue also deletes the jobs in that queue.
Removes the association between a queue and a limit. You must use the\n UpdateQueueLimitAssociation operation to set the status to\n STOP_LIMIT_USAGE_AND_COMPLETE_TASKS or\n STOP_LIMIT_USAGE_AND_CANCEL_TASKS. The status does not change immediately.\n Use the GetQueueLimitAssociation operation to see if the status changed to\n STOPPED before deleting the association.
Removes the association between a queue and a limit. You must use the UpdateQueueLimitAssociation operation to set the status to STOP_LIMIT_USAGE_AND_COMPLETE_TASKS or STOP_LIMIT_USAGE_AND_CANCEL_TASKS. The status does not change immediately. Use the GetQueueLimitAssociation operation to see if the status changed to STOPPED before deleting the association.
The unique identifier of the farm that contains the queue and limit to\n disassociate.
", + "smithy.api#documentation": "The unique identifier of the farm that contains the queue and limit to disassociate.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -6644,7 +6650,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the farm.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the fleet summary to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the fleet summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the budget.
\n\n ACTIVE–Get a budget being evaluated.
\n INACTIVE–Get an inactive budget. This can include expired,\n canceled, or deleted statuses.
The status of the budget.
ACTIVE–Get a budget being evaluated.
INACTIVE–Get an inactive budget. This can include expired, canceled, or deleted statuses.
The display name of the budget.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the budget.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the farm.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the farm.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the fleet.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the fleet.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The Auto Scaling status of the fleet. Either GROWING, STEADY, or\n SHRINKING.
The Auto Scaling status of the fleet. Either GROWING, STEADY, or SHRINKING.
The script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
" + } + }, "capabilities": { "target": "com.amazonaws.deadline#FleetCapabilities", "traits": { - "smithy.api#documentation": "Outlines what the fleet is capable of for minimums, maximums, and naming, in addition to\n attribute names and values.
" + "smithy.api#documentation": "Outlines what the fleet is capable of for minimums, maximums, and naming, in addition to attribute names and values.
" } }, "roleArn": { @@ -8017,13 +8029,13 @@ "description": { "target": "com.amazonaws.deadline#JobDescription", "traits": { - "smithy.api#documentation": "The description of the job.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the job.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of worker hosts that can concurrently process a job. When the\n maxWorkerCount is reached, no more workers will be assigned to process the\n job, even if the fleets assigned to the job's queue has available workers.
If you don't set the maxWorkerCount when you create a job, this value is\n not returned in the response.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
If you don't set the maxWorkerCount when you create a job, this value is not returned in the response.
The display name of the limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of\n the hostRequirements in a step of a job template to declare the limit\n requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are\n in use, steps that require the limit won't be scheduled until the resource is\n available.
\nThe maxValue must not be 0. If the value is -1, there is no restriction on\n the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxValue must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
The number of resources from the limit that are being used by jobs. The result is\n delayed and may not be the count at the time that you called the operation.
", + "smithy.api#documentation": "The number of resources from the limit that are being used by jobs. The result is delayed and may not be the count at the time that you called the operation.
", "smithy.api#required": {} } }, "description": { "target": "com.amazonaws.deadline#Description", "traits": { - "smithy.api#documentation": "The description of the limit that helps identify what the limit is used for.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the limit that helps identify what the limit is used for.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The unique identifier for the monitor. This ID is returned by the\n CreateMonitor operation.
The unique identifier for the monitor. This ID is returned by the CreateMonitor operation.
The name used to identify the monitor on the Deadline Cloud console.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe name used to identify the monitor on the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain used for the monitor URL. The full URL of the monitor is\n subdomain.Region.deadlinecloud.amazonaws.com.
", + "smithy.api#documentation": "The subdomain used for the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
", "smithy.api#required": {} } }, "url": { "target": "com.amazonaws.deadline#Url", "traits": { - "smithy.api#documentation": "The complete URL of the monitor. The full URL of the monitor is\n subdomain.Region.deadlinecloud.amazonaws.com.
", + "smithy.api#documentation": "The complete URL of the monitor. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
", "smithy.api#required": {} } }, "roleArn": { "target": "com.amazonaws.deadline#IamRoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to\n access Deadline Cloud resources.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to access Deadline Cloud resources.
", "smithy.api#required": {} } }, @@ -9072,14 +9084,14 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the queue.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The status of the queue.
\n\n ACTIVE–The queue is active.
\n SCHEDULING–The queue is scheduling.
\n SCHEDULING_BLOCKED–The queue scheduling is blocked. See the\n provided reason.
The status of the queue.
ACTIVE–The queue is active.
SCHEDULING–The queue is scheduling.
SCHEDULING_BLOCKED–The queue scheduling is blocked. See the provided reason.
The process exit code. The default Deadline Cloud worker agent converts unsigned\n 32-bit exit codes to signed 32-bit exit codes.
" + "smithy.api#documentation": "The process exit code. The default Deadline Cloud worker agent converts unsigned 32-bit exit codes to signed 32-bit exit codes.
" } }, "progressMessage": { @@ -9366,7 +9378,7 @@ "acquiredLimits": { "target": "com.amazonaws.deadline#AcquiredLimits", "traits": { - "smithy.api#documentation": "The limits and their amounts acquired during a session action. If no limits were\n acquired during the session, this field isn't returned.
" + "smithy.api#documentation": "The limits and their amounts acquired during a session action. If no limits were acquired during the session, this field isn't returned.
" } } }, @@ -9531,7 +9543,7 @@ "documentation": "Grants permission to get all collected statistics for sessions", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Gets a set of statistics for queues or farms. Before you can call the\n GetSessionStatisticsAggregation operation, you must first call the\n StartSessionsStatisticsAggregation operation. Statistics are available for\n 1 hour after you call the StartSessionsStatisticsAggregation operation.
Gets a set of statistics for queues or farms. Before you can call the GetSessionStatisticsAggregation operation, you must first call the StartSessionsStatisticsAggregation operation. Statistics are available for 1 hour after you call the StartSessionsStatisticsAggregation operation.
The identifier of the farm to include in the statistics. This should be the same as the\n farm ID used in the call to the StartSessionsStatisticsAggregation\n operation.
The identifier of the farm to include in the statistics. This should be the same as the farm ID used in the call to the StartSessionsStatisticsAggregation operation.
The identifier returned by the StartSessionsStatisticsAggregation operation\n that identifies the aggregated statistics.
The identifier returned by the StartSessionsStatisticsAggregation operation that identifies the aggregated statistics.
The status of the aggregated results. An aggregation may fail or time out if the results\n are too large. If this happens, you can call the\n StartSessionsStatisticsAggregation operation after you reduce the\n aggregation time frame, reduce the number of queues or fleets in the aggregation, or\n increase the period length.
If you call the StartSessionsStatisticsAggregation operation when the\n status is IN_PROGRESS, you will receive a\n ThrottlingException.
The status of the aggregated results. An aggregation may fail or time out if the results are too large. If this happens, you can call the StartSessionsStatisticsAggregation operation after you reduce the aggregation time frame, reduce the number of queues or fleets in the aggregation, or increase the period length.
If you call the StartSessionsStatisticsAggregation operation when the status is IN_PROGRESS, you will receive a ThrottlingException.
The description of the step.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the step.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the storage profile connected to a queue.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the storage profile connected to a queue.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the storage profile.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the storage profile.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The text of the script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet. The script runs after a worker enters the STARTING state and before the worker processes tasks.
For more information about using the script, see Run scripts as an administrator to configure workers in the Deadline Cloud Developer Guide.
The script runs as an administrative user (sudo root on Linux, as an Administrator on Windows).
The maximum time that the host configuration can run. If the timeout expires, the worker enters the NOT RESPONDING state and shuts down. You are charged for the time that the worker is running the host configuration script.
You should configure your fleet for a maximum of one worker while testing your host configuration script to avoid starting additional workers.
The default is 300 seconds (5 minutes).
" + } + } + }, + "traits": { + "smithy.api#documentation": "Provides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
To remove a script from a fleet, use the UpdateFleet operation with the hostConfiguration scriptBody parameter set to an empty string (\"\").
Specifies whether the job should run using the queue's system user or if the job should\n run using the worker agent system user.
", + "smithy.api#documentation": "Specifies whether the job should run using the queue's system user or if the job should run using the worker agent system user.
", "smithy.api#required": {} } } @@ -11282,7 +11335,7 @@ "taskRunStatus": { "target": "com.amazonaws.deadline#TaskRunStatus", "traits": { - "smithy.api#documentation": "The task run status for the job.
\n\n PENDING–pending and waiting for resources.
\n READY–ready to be processed.
\n ASSIGNED–assigned and will run next on a worker.
\n SCHEDULED–scheduled to be run on a worker.
\n INTERRUPTING–being interrupted.
\n RUNNING–running on a worker.
\n SUSPENDED–the task is suspended.
\n CANCELED–the task has been canceled.
\n FAILED–the task has failed.
\n SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The maximum number of worker hosts that can concurrently process a job. When the\n maxWorkerCount is reached, no more workers will be assigned to process the\n job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no\n maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The task run status for the job.
\n\n PENDING–pending and waiting for resources.
\n READY–ready to be processed.
\n ASSIGNED–assigned and will run next on a worker.
\n SCHEDULED–scheduled to be run on a worker.
\n INTERRUPTING–being interrupted.
\n RUNNING–running on a worker.
\n SUSPENDED–the task is suspended.
\n CANCELED–the task has been canceled.
\n FAILED–the task has failed.
\n SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The maximum number of worker hosts that can concurrently process a job. When the\n maxWorkerCount is reached, no more workers will be assigned to process the\n job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no\n maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The name of the limit used in lists to identify the limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe name of the limit used in lists to identify the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The value that you specify as the name in the amounts field of\n the hostRequirements in a step of a job template to declare the limit\n requirement.
The value that you specify as the name in the amounts field of the hostRequirements in a step of a job template to declare the limit requirement.
The maximum number of resources constrained by this limit. When all of the resources are\n in use, steps that require the limit won't be scheduled until the resource is\n available.
\nThe maxValue must not be 0. If the value is -1, there is no restriction on\n the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
The maxValue must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
The number of resources from the limit that are being used by jobs. The result is\n delayed and may not be the count at the time that you called the operation.
", + "smithy.api#documentation": "The number of resources from the limit that are being used by jobs. The result is delayed and may not be the count at the time that you called the operation.
", "smithy.api#required": {} } } @@ -12351,7 +12404,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display names of a list of fleets.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display names of a list of fleets.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
A list of MonitorSummary objects that describe your monitors in the\n Deadline Cloud.
A list of MonitorSummary objects that describe your monitors in the Deadline Cloud.
Specifies that the operation should return only the queue limit associations for the\n specified queue. If you specify both the queueId and the limitId,\n only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the specified queue. If you specify both the queueId and the limitId, only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the\n specified limit. If you specify both the queueId and the limitId,\n only the specified limit is returned if it exists.
Specifies that the operation should return only the queue limit associations for the specified limit. If you specify both the queueId and the limitId, only the specified limit is returned if it exists.
A list of associations between limits and queues in the farm specified in the\n request.
", + "smithy.api#documentation": "A list of associations between limits and queues in the farm specified in the request.
", "smithy.api#required": {} } }, @@ -13678,7 +13731,7 @@ "status": { "target": "com.amazonaws.deadline#QueueStatus", "traits": { - "smithy.api#documentation": "The status of the queues listed.
\n\n ACTIVE–The queues are active.
\n SCHEDULING–The queues are scheduling.
\n SCHEDULING_BLOCKED–The queue scheduling is blocked for these\n queues.
The status of the queues listed.
ACTIVE–The queues are active.
SCHEDULING–The queues are scheduling.
SCHEDULING_BLOCKED–The queue scheduling is blocked for these queues.
The name of the monitor that displays on the Deadline Cloud console.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe name of the monitor that displays on the Deadline Cloud console.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The subdomain used for the monitor URL. The full URL of the monitor is\n subdomain.Region.deadlinecloud.amazonaws.com.
", + "smithy.api#documentation": "The subdomain used for the monitor URL. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
", "smithy.api#required": {} } }, "url": { "target": "com.amazonaws.deadline#Url", "traits": { - "smithy.api#documentation": "The complete URL of the monitor. The full URL of the monitor is\n subdomain.Region.deadlinecloud.amazonaws.com.
", + "smithy.api#documentation": "The complete URL of the monitor. The full URL of the monitor is subdomain.Region.deadlinecloud.amazonaws.com.
", "smithy.api#required": {} } }, "roleArn": { "target": "com.amazonaws.deadline#IamRoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to\n access Deadline Cloud resources.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role for the monitor. Users of the monitor use this role to access Deadline Cloud resources.
", "smithy.api#required": {} } }, @@ -15973,7 +16026,7 @@ "status": { "target": "com.amazonaws.deadline#QueueFleetAssociationStatus", "traits": { - "smithy.api#documentation": "The status of task scheduling in the queue-fleet association.
\n\n ACTIVE–Association is active.
\n STOP_SCHEDULING_AND_COMPLETE_TASKS–Association has stopped\n scheduling new tasks and is completing current tasks.
\n STOP_SCHEDULING_AND_CANCEL_TASKS–Association has stopped\n scheduling new tasks and is canceling current tasks.
\n STOPPED–Association has been stopped.
The status of task scheduling in the queue-fleet association.
ACTIVE–Association is active.
STOP_SCHEDULING_AND_COMPLETE_TASKS–Association has stopped scheduling new tasks and is completing current tasks.
STOP_SCHEDULING_AND_CANCEL_TASKS–Association has stopped scheduling new tasks and is canceling current tasks.
STOPPED–Association has been stopped.
The status of task scheduling in the queue-limit association.
\n\n ACTIVE - Association is active.
\n STOP_LIMIT_USAGE_AND_COMPLETE_TASKS - Association has stopped\n scheduling new tasks and is completing current tasks.
\n STOP_LIMIT_USAGE_AND_CANCEL_TASKS - Association has stopped\n scheduling new tasks and is canceling current tasks.
\n STOPPED - Association has been stopped.
The status of task scheduling in the queue-limit association.
ACTIVE - Association is active.
STOP_LIMIT_USAGE_AND_COMPLETE_TASKS - Association has stopped scheduling new tasks and is completing current tasks.
STOP_LIMIT_USAGE_AND_CANCEL_TASKS - Association has stopped scheduling new tasks and is canceling current tasks.
STOPPED - Association has been stopped.
The display name of the queue summary to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the queue summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The budget action description.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe budget action description.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The filter expression, AND or OR, to use\nwhen searching among a group of search strings in a resource.\n\nYou can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use\nwhen searching among a group of search strings in a resource.\n\nYou can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use\nwhen searching among a group of search strings in a resource.\n\nYou can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use\nwhen searching among a group of search strings in a resource.\n\nYou can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
Specifies how Deadline Cloud matches your search term in the results. If you don't\n specify a matchType the default is FUZZY_MATCH.
\n FUZZY_MATCH - Matches if a portion of the search term is found in the\n result.
\n CONTAINS - Matches if the exact search term is contained in the\n result.
Specifies how Deadline Cloud matches your search term in the results. If you don't specify a matchType the default is FUZZY_MATCH.
FUZZY_MATCH - Matches if a portion of the search term is found in the result.
CONTAINS - Matches if the exact search term is contained in the result.
The filter expression, AND or OR, to use\nwhen searching among a group of search strings in a resource.\n\nYou can use two groupings per search each within parenthesis ().
The filter expression, AND or OR, to use when searching among a group of search strings in a resource. You can use two groupings per search each within parenthesis ().
Describes the GPU accelerator capabilities required for worker host instances in this\n fleet.
" + "smithy.api#documentation": "Describes the GPU accelerator capabilities required for worker host instances in this fleet.
" } }, "allowedInstanceTypes": { @@ -17428,7 +17481,7 @@ } }, "traits": { - "smithy.api#documentation": "You exceeded your service quota. Service quotas, also referred to as limits, are the\n maximum number of service resources or operations for your Amazon Web Services account.
", + "smithy.api#documentation": "You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your Amazon Web Services account.
", "smithy.api#error": "client", "smithy.api#httpError": 402 } @@ -17447,6 +17500,12 @@ "traits": { "smithy.api#enumValue": "KMS_KEY_LIMIT_EXCEEDED" } + }, + "DEPENDENCY_LIMIT_EXCEEDED": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "DEPENDENCY_LIMIT_EXCEEDED" + } } } }, @@ -17660,7 +17719,7 @@ "workerUpdatedAt": { "target": "com.amazonaws.deadline#Timestamp", "traits": { - "smithy.api#documentation": "The Linux timestamp of the last date and time that the session action was\n updated.
" + "smithy.api#documentation": "The Linux timestamp of the last date and time that the session action was updated.
" } }, "progressPercent": { @@ -17847,7 +17906,7 @@ "queueIds": { "target": "com.amazonaws.deadline#QueueIds", "traits": { - "smithy.api#documentation": "One to 10 queue IDs that specify the queues to return statistics for. If you specify the\n queueIds field, you can't specify the fleetIds field.
One to 10 queue IDs that specify the queues to return statistics for. If you specify the queueIds field, you can't specify the fleetIds field.
One to 10 fleet IDs that specify the fleets to return statistics for. If you specify the\n fleetIds field, you can't specify the queueIds field.
One to 10 fleet IDs that specify the fleets to return statistics for. If you specify the fleetIds field, you can't specify the queueIds field.
Specifies the fleet IDs or queue IDs to return statistics. You can specify only fleet\n IDs or queue IDS, not both.
" + "smithy.api#documentation": "Specifies the fleet IDs or queue IDs to return statistics. You can specify only fleet IDs or queue IDS, not both.
" } }, "com.amazonaws.deadline#SortOrder": { @@ -17917,7 +17976,7 @@ "documentation": "Grants permission to get all collected statistics for sessions", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Starts an asynchronous request for getting aggregated statistics about queues and farms.\n Get the statistics using the GetSessionsStatisticsAggregation operation. You\n can only have one running aggregation for your Deadline Cloud farm. Call the\n GetSessionsStatisticsAggregation operation and check the\n status field to see if an aggregation is running. Statistics are available\n for 1 hour after you call the StartSessionsStatisticsAggregation\n operation.
Starts an asynchronous request for getting aggregated statistics about queues and farms. Get the statistics using the GetSessionsStatisticsAggregation operation. You can only have one running aggregation for your Deadline Cloud farm. Call the GetSessionsStatisticsAggregation operation and check the status field to see if an aggregation is running. Statistics are available for 1 hour after you call the StartSessionsStatisticsAggregation operation.
The identifier of the farm that contains queues or fleets to return statistics\n for.
", + "smithy.api#documentation": "The identifier of the farm that contains queues or fleets to return statistics for.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -18000,7 +18059,7 @@ "aggregationId": { "target": "com.amazonaws.deadline#AggregationId", "traits": { - "smithy.api#documentation": "A unique identifier for the aggregated statistics. Use this identifier with the\n GetAggregatedStatisticsForSessions operation to return the\n statistics.
A unique identifier for the aggregated statistics. Use this identifier with the GetAggregatedStatisticsForSessions operation to return the statistics.
How the statistics should appear in USD. Options include: minimum, maximum, average or\n sum.
", + "smithy.api#documentation": "How the statistics should appear in USD. Options include: minimum, maximum, average or sum.
", "smithy.api#required": {} } }, @@ -18590,7 +18649,7 @@ "taskRunStatus": { "target": "com.amazonaws.deadline#TaskRunStatus", "traits": { - "smithy.api#documentation": "The task run status for the job.
\n\n PENDING–pending and waiting for resources.
\n READY–ready to be processed.
\n ASSIGNED–assigned and will run next on a worker.
\n SCHEDULED–scheduled to be run on a worker.
\n INTERRUPTING–being interrupted.
\n RUNNING–running on a worker.
\n SUSPENDED–the task is suspended.
\n CANCELED–the task has been canceled.
\n FAILED–the task has failed.
\n SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to be processed.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to be run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The task run status for the job.
\n\n PENDING–pending and waiting for resources.
\n READY–ready to process.
\n ASSIGNED–assigned and will run next on a worker.
\n SCHEDULED–scheduled to run on a worker.
\n INTERRUPTING–being interrupted.
\n RUNNING–running on a worker.
\n SUSPENDED–the task is suspended.
\n CANCELED–the task has been canceled.
\n FAILED–the task has failed.
\n SUCCEEDED–the task has succeeded.
The task run status for the job.
PENDING–pending and waiting for resources.
READY–ready to process.
ASSIGNED–assigned and will run next on a worker.
SCHEDULED–scheduled to run on a worker.
INTERRUPTING–being interrupted.
RUNNING–running on a worker.
SUSPENDED–the task is suspended.
CANCELED–the task has been canceled.
FAILED–the task has failed.
SUCCEEDED–the task has succeeded.
The display name of the storage profile summary to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the storage profile summary to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the budget to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the budget to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the budget to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the budget to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Updates the status of the budget.
\n\n ACTIVE–The budget is being evaluated.
\n INACTIVE–The budget is inactive. This can include Expired,\n Canceled, or deleted Deleted statuses.
Updates the status of the budget.
ACTIVE–The budget is being evaluated.
INACTIVE–The budget is inactive. This can include Expired, Canceled, or deleted Deleted statuses.
The budget actions to add. Budget actions specify what happens when the budget runs\n out.
" + "smithy.api#documentation": "The budget actions to add. Budget actions specify what happens when the budget runs out.
" } }, "actionsToRemove": { @@ -19857,13 +19916,13 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the farm to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the farm to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the farm to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the farm to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The display name of the fleet to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the fleet to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the fleet to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the fleet to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of workers in the fleet.
" + "smithy.api#documentation": "The maximum number of workers in the fleet.
Deadline Cloud limits the number of workers to less than or equal to the fleet's maximum worker count. The service maintains eventual consistency for the worker count. If you make multiple rapid calls to CreateWorker before the field updates, you might exceed your fleet's maximum worker count. For example, if your maxWorkerCount is 10 and you currently have 9 workers, making two quick CreateWorker calls might successfully create 2 workers instead of 1, resulting in 11 total workers.
The fleet configuration to update.
" } + }, + "hostConfiguration": { + "target": "com.amazonaws.deadline#HostConfiguration", + "traits": { + "smithy.api#documentation": "Provides a script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
" + } } }, "traits": { @@ -20033,7 +20098,7 @@ "documentation": "Grants permission to update a job", "requiredActions": ["identitystore:ListGroupMembershipsForMember"] }, - "smithy.api#documentation": "Updates a job.
\nWhen you change the status of the job to ARCHIVED, the job can't be\n scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be\n recovered.
\nUpdates a job.
When you change the status of the job to ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be recovered.
The status of a job in its lifecycle. When you change the status of the job to\n ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be\n recovered.
\nThe status of a job in its lifecycle. When you change the status of the job to ARCHIVED, the job can't be scheduled or archived.
An archived jobs and its steps and tasks are deleted after 120 days. The job can't be recovered.
The maximum number of worker hosts that can concurrently process a job. When the\n maxWorkerCount is reached, no more workers will be assigned to process the\n job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no\n maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of workers that can process tasks in the job.
" + "smithy.api#documentation": "The maximum number of worker hosts that can concurrently process a job. When the maxWorkerCount is reached, no more workers will be assigned to process the job, even if the fleets assigned to the job's queue has available workers.
You can't set the maxWorkerCount to 0. If you set it to -1, there is no maximum number of workers.
If you don't specify the maxWorkerCount, the default is -1.
The maximum number of workers that can process tasks in the job.
" } }, "farmId": { @@ -20204,19 +20269,19 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The new display name of the limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe new display name of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The new description of the limit.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe new description of the limit.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The maximum number of resources constrained by this limit. When all of the resources are\n in use, steps that require the limit won't be scheduled until the resource is\n available.
\nIf more than the new maximum number is currently in use, running jobs finish but no new\n jobs are started until the number of resources in use is below the new maximum\n number.
\nThe maxCount must not be 0. If the value is -1, there is no restriction on\n the number of resources that can be acquired for this limit.
The maximum number of resources constrained by this limit. When all of the resources are in use, steps that require the limit won't be scheduled until the resource is available.
If more than the new maximum number is currently in use, running jobs finish but no new jobs are started until the number of resources in use is below the new maximum number.
The maxCount must not be 0. If the value is -1, there is no restriction on the number of resources that can be acquired for this limit.
Modifies the settings for a Deadline Cloud monitor. You can modify one or all of the settings\n when you call UpdateMonitor.
Modifies the settings for a Deadline Cloud monitor. You can modify one or all of the settings when you call UpdateMonitor.
The new value to use for the monitor's display name.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe new value to use for the monitor's display name.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
Updates the status of the queue. If you set the status to one of the\n STOP_LIMIT_USAGE* values, there will be a delay before the status\n transitions to the STOPPED state.
Updates the status of the queue. If you set the status to one of the STOP_LIMIT_USAGE* values, there will be a delay before the status transitions to the STOPPED state.
Sets the status of the limit. You can mark the limit active, or you can stop usage of\n the limit and either complete existing tasks or cancel any existing tasks immediately.\n
", + "smithy.api#documentation": "Sets the status of the limit. You can mark the limit active, or you can stop usage of the limit and either complete existing tasks or cancel any existing tasks immediately.
", "smithy.api#required": {} } } @@ -20736,13 +20801,13 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the queue to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the queue to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The description of the queue to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe description of the queue to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The job attachment settings to update for the\n queue.
" + "smithy.api#documentation": "The job attachment settings to update for the queue.
" } }, "roleArn": { @@ -21093,7 +21158,7 @@ "displayName": { "target": "com.amazonaws.deadline#ResourceName", "traits": { - "smithy.api#documentation": "The display name of the storage profile to update.
\nThis field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
\nThe display name of the storage profile to update.
This field can store any content. Escape or encode this content before displaying it on a webpage or any other system that might interpret the content of this field.
The worker log to update.
" } + }, + "hostConfiguration": { + "target": "com.amazonaws.deadline#HostConfiguration", + "traits": { + "smithy.api#documentation": "The script that runs as a worker is starting up that you can use to provide additional configuration for workers in your fleet.
" + } } }, "traits": { @@ -21500,7 +21571,7 @@ "processExitCode": { "target": "com.amazonaws.deadline#ProcessExitCode", "traits": { - "smithy.api#documentation": "The process exit code. The default Deadline Cloud worker agent converts unsigned\n 32-bit exit codes to signed 32-bit exit codes.
" + "smithy.api#documentation": "The process exit code. The default Deadline Cloud worker agent converts unsigned 32-bit exit codes to signed 32-bit exit codes.
" } }, "progressMessage": { @@ -21538,7 +21609,7 @@ } }, "traits": { - "smithy.api#documentation": "The updated session action information as it relates to completion and progress of the\n session.
" + "smithy.api#documentation": "The updated session action information as it relates to completion and progress of the session.
" } }, "com.amazonaws.deadline#UpdatedSessionActions": { @@ -21778,7 +21849,7 @@ } }, "traits": { - "smithy.api#documentation": "The request isn't valid. This can occur if your request contains malformed JSON or\n unsupported characters.
", + "smithy.api#documentation": "The request isn't valid. This can occur if your request contains malformed JSON or unsupported characters.
", "smithy.api#error": "client", "smithy.api#httpError": 400 } diff --git a/codegen/sdk-codegen/aws-models/ec2.json b/codegen/sdk-codegen/aws-models/ec2.json index 65e6c5b0e65c..a487d5f716ef 100644 --- a/codegen/sdk-codegen/aws-models/ec2.json +++ b/codegen/sdk-codegen/aws-models/ec2.json @@ -1832,6 +1832,12 @@ "smithy.api#xmlName": "AssetId" } }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#AvailabilityZoneId", + "traits": { + "smithy.api#documentation": "The ID of the Availability Zone.
" + } + }, "AutoPlacement": { "target": "com.amazonaws.ec2#AutoPlacement", "traits": { @@ -1868,9 +1874,7 @@ "target": "com.amazonaws.ec2#String", "traits": { "aws.protocols#ec2QueryName": "AvailabilityZone", - "smithy.api#clientOptional": {}, "smithy.api#documentation": "The Availability Zone in which to allocate the Dedicated Host.
", - "smithy.api#required": {}, "smithy.api#xmlName": "availabilityZone" } } @@ -5571,6 +5575,14 @@ "smithy.api#xmlName": "availabilityZone" } }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#String", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } + }, "Instance": { "target": "com.amazonaws.ec2#AnalysisComponent", "traits": { @@ -12313,6 +12325,14 @@ "smithy.api#documentation": "The tenancy of the Capacity Reservation.
", "smithy.api#xmlName": "tenancy" } + }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#AvailabilityZoneId", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } } }, "traits": { @@ -34917,7 +34937,7 @@ "target": "com.amazonaws.ec2#DescribeInstanceStatusResult" }, "traits": { - "smithy.api#documentation": "Describes the status of the specified instances or all of your instances. By default,\n only running instances are described, unless you specifically indicate to return the\n status of all instances.
\nInstance status includes the following components:
\n\n Status checks - Amazon EC2 performs status\n checks on running EC2 instances to identify hardware and software issues. For\n more information, see Status checks for your instances and Troubleshoot\n instances with failed status checks in the Amazon EC2 User\n Guide.
\n\n Scheduled events - Amazon EC2 can schedule\n events (such as reboot, stop, or terminate) for your instances related to\n hardware issues, software updates, or system maintenance. For more information,\n see Scheduled events for your instances in the Amazon EC2 User\n Guide.
\n\n Instance state - You can manage your instances\n from the moment you launch them through their termination. For more information,\n see Instance\n lifecycle in the Amazon EC2 User Guide.
\nThe order of the elements in the response, including those within nested\n structures, might vary. Applications should not assume the elements appear in a\n particular order.
\nDescribes the status of the specified instances or all of your instances. By default,\n only running instances are described, unless you specifically indicate to return the\n status of all instances.
\nInstance status includes the following components:
\n\n Status checks - Amazon EC2 performs status\n checks on running EC2 instances to identify hardware and software issues. For\n more information, see Status checks for your instances and Troubleshoot\n instances with failed status checks in the Amazon EC2 User\n Guide.
\n\n Scheduled events - Amazon EC2 can schedule\n events (such as reboot, stop, or terminate) for your instances related to\n hardware issues, software updates, or system maintenance. For more information,\n see Scheduled events for your instances in the Amazon EC2 User\n Guide.
\n\n Instance state - You can manage your instances\n from the moment you launch them through their termination. For more information,\n see Instance\n lifecycle in the Amazon EC2 User Guide.
\nThe Amazon EC2 API follows an eventual consistency model. This means that the result of an\n API command you run that creates or modifies resources might not be immediately\n available to all subsequent commands you run. For guidance on how to manage eventual\n consistency, see Eventual consistency in the\n Amazon EC2 API in the Amazon EC2 Developer\n Guide.
\nThe order of the elements in the response, including those within nested\n structures, might vary. Applications should not assume the elements appear in a\n particular order.
\nDescribes the specified instances or all instances.
\nIf you specify instance IDs, the output includes information for only the specified\n instances. If you specify filters, the output includes information for only those\n instances that meet the filter criteria. If you do not specify instance IDs or filters,\n the output includes information for all instances, which can affect performance. We\n recommend that you use pagination to ensure that the operation returns quickly and\n successfully.
\nIf you specify an instance ID that is not valid, an error is returned. If you specify\n an instance that you do not own, it is not included in the output.
\nRecently terminated instances might appear in the returned results. This interval is\n usually less than one hour.
\nIf you describe instances in the rare case where an Availability Zone is experiencing\n a service disruption and you specify instance IDs that are in the affected zone, or do\n not specify any instance IDs at all, the call fails. If you describe instances and\n specify only instance IDs that are in an unaffected zone, the call works\n normally.
\nWe strongly recommend using only paginated requests. Unpaginated requests are\n susceptible to throttling and timeouts.
\nThe order of the elements in the response, including those within nested\n structures, might vary. Applications should not assume the elements appear in a\n particular order.
\nDescribes the specified instances or all instances.
\nIf you specify instance IDs, the output includes information for only the specified\n instances. If you specify filters, the output includes information for only those\n instances that meet the filter criteria. If you do not specify instance IDs or filters,\n the output includes information for all instances, which can affect performance. We\n recommend that you use pagination to ensure that the operation returns quickly and\n successfully.
\nIf you specify an instance ID that is not valid, an error is returned. If you specify\n an instance that you do not own, it is not included in the output.
\nRecently terminated instances might appear in the returned results. This interval is\n usually less than one hour.
\nIf you describe instances in the rare case where an Availability Zone is experiencing\n a service disruption and you specify instance IDs that are in the affected zone, or do\n not specify any instance IDs at all, the call fails. If you describe instances and\n specify only instance IDs that are in an unaffected zone, the call works\n normally.
\nThe Amazon EC2 API follows an eventual consistency model. This means that the result of an\n API command you run that creates or modifies resources might not be immediately\n available to all subsequent commands you run. For guidance on how to manage eventual\n consistency, see Eventual consistency in the\n Amazon EC2 API in the Amazon EC2 Developer\n Guide.
\nWe strongly recommend using only paginated requests. Unpaginated requests are\n susceptible to throttling and timeouts.
\nThe order of the elements in the response, including those within nested\n structures, might vary. Applications should not assume the elements appear in a\n particular order.
\nOne or more filters.
\n\n client-token - The idempotency token for the modification request.
\n create-date - The time when the modification request was created.
\n effective-date - The time when the modification becomes effective.
\n modification-result.reserved-instances-id - The ID for the Reserved Instances\n created as part of the modification request. This ID is only available when the status of\n the modification is fulfilled.
\n modification-result.target-configuration.availability-zone - The Availability\n Zone for the new Reserved Instances.
\n modification-result.target-configuration.instance-count - The number of new\n Reserved Instances.
\n modification-result.target-configuration.instance-type - The instance type of\n the new Reserved Instances.
\n reserved-instances-id - The ID of the Reserved Instances modified.
\n reserved-instances-modification-id - The ID of the modification\n request.
\n status - The status of the Reserved Instances modification request\n (processing | fulfilled | failed).
\n status-message - The reason for the status.
\n update-date - The time when the modification request was last updated.
One or more filters.
\n\n client-token - The idempotency token for the modification request.
\n create-date - The time when the modification request was created.
\n effective-date - The time when the modification becomes effective.
\n modification-result.reserved-instances-id - The ID for the Reserved Instances\n created as part of the modification request. This ID is only available when the status of\n the modification is fulfilled.
\n modification-result.target-configuration.availability-zone - The Availability\n Zone for the new Reserved Instances.
\n modification-result.target-configuration.availability-zone-id - The ID of the\n Availability Zone for the new Reserved Instances.
\n modification-result.target-configuration.instance-count - The number of new\n Reserved Instances.
\n modification-result.target-configuration.instance-type - The instance type of\n the new Reserved Instances.
\n reserved-instances-id - The ID of the Reserved Instances modified.
\n reserved-instances-modification-id - The ID of the modification\n request.
\n status - The status of the Reserved Instances modification request\n (processing | fulfilled | failed).
\n status-message - The reason for the status.
\n update-date - The time when the modification request was last updated.
The Availability Zone in which the Reserved Instance can be used.
" + "smithy.api#documentation": "The Availability Zone in which the Reserved Instance can be used.
\nEither AvailabilityZone or AvailabilityZoneId can be specified,\n but not both.
The ID of the Availability Zone.
\nEither AvailabilityZone or AvailabilityZoneId can be specified,\n but not both.
One or more filters.
\n\n availability-zone - The Availability Zone where the Reserved Instance can be\n used.
\n duration - The duration of the Reserved Instance (for example, one year or\n three years), in seconds (31536000 | 94608000).
\n fixed-price - The purchase price of the Reserved Instance (for example,\n 9800.0).
\n instance-type - The instance type that is covered by the reservation.
\n marketplace - Set to true to show only Reserved Instance\n Marketplace offerings. When this filter is not used, which is the default behavior, all\n offerings from both Amazon Web Services and the Reserved Instance Marketplace are listed.
\n product-description - The Reserved Instance product platform description\n (Linux/UNIX | Linux with SQL Server Standard | Linux\n with SQL Server Web | Linux with SQL Server Enterprise | SUSE\n Linux | Red Hat Enterprise Linux | Red Hat Enterprise Linux\n with HA | Windows | Windows with SQL Server Standard |\n Windows with SQL Server Web | Windows with SQL Server\n Enterprise).
\n reserved-instances-offering-id - The Reserved Instances offering ID.
\n scope - The scope of the Reserved Instance (Availability Zone or\n Region).
\n usage-price - The usage price of the Reserved Instance, per hour (for\n example, 0.84).
One or more filters.
\n\n availability-zone - The Availability Zone where the Reserved Instance can be\n used.
\n availability-zone-id - The ID of the Availability Zone where the Reserved\n Instance can be used.
\n duration - The duration of the Reserved Instance (for example, one year or\n three years), in seconds (31536000 | 94608000).
\n fixed-price - The purchase price of the Reserved Instance (for example,\n 9800.0).
\n instance-type - The instance type that is covered by the reservation.
\n marketplace - Set to true to show only Reserved Instance\n Marketplace offerings. When this filter is not used, which is the default behavior, all\n offerings from both Amazon Web Services and the Reserved Instance Marketplace are listed.
\n product-description - The Reserved Instance product platform description\n (Linux/UNIX | Linux with SQL Server Standard | Linux\n with SQL Server Web | Linux with SQL Server Enterprise | SUSE\n Linux | Red Hat Enterprise Linux | Red Hat Enterprise Linux\n with HA | Windows | Windows with SQL Server Standard |\n Windows with SQL Server Web | Windows with SQL Server\n Enterprise).
\n reserved-instances-offering-id - The Reserved Instances offering ID.
\n scope - The scope of the Reserved Instance (Availability Zone or\n Region).
\n usage-price - The usage price of the Reserved Instance, per hour (for\n example, 0.84).
One or more filters.
\n\n availability-zone - The Availability Zone where the Reserved Instance can\n be used.
\n duration - The duration of the Reserved Instance (one year or three\n years), in seconds (31536000 | 94608000).
\n end - The time when the Reserved Instance expires (for example,\n 2015-08-07T11:54:42.000Z).
\n fixed-price - The purchase price of the Reserved Instance (for example,\n 9800.0).
\n instance-type - The instance type that is covered by the\n reservation.
\n scope - The scope of the Reserved Instance (Region or\n Availability Zone).
\n product-description - The Reserved Instance product platform description\n (Linux/UNIX | Linux with SQL Server Standard | Linux\n with SQL Server Web | Linux with SQL Server Enterprise | SUSE\n Linux | Red Hat Enterprise Linux | Red Hat Enterprise Linux\n with HA | Windows | Windows with SQL Server Standard |\n Windows with SQL Server Web | Windows with SQL Server\n Enterprise).
\n reserved-instances-id - The ID of the Reserved Instance.
\n start - The time at which the Reserved Instance purchase request was\n placed (for example, 2014-08-07T11:54:42.000Z).
\n state - The state of the Reserved Instance (payment-pending\n | active | payment-failed | retired).
\n tag: - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value.\n For example, to find all resources that have a tag with the key Owner and the value TeamA, specify tag:Owner for the filter name and TeamA for the filter value.
\n tag-key - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value.
\n usage-price - The usage price of the Reserved Instance, per hour (for\n example, 0.84).
One or more filters.
\n\n availability-zone - The Availability Zone where the Reserved Instance can\n be used.
\n availability-zone-id - The ID of the Availability Zone where the Reserved\n Instance can be used.
\n duration - The duration of the Reserved Instance (one year or three\n years), in seconds (31536000 | 94608000).
\n end - The time when the Reserved Instance expires (for example,\n 2015-08-07T11:54:42.000Z).
\n fixed-price - The purchase price of the Reserved Instance (for example,\n 9800.0).
\n instance-type - The instance type that is covered by the\n reservation.
\n scope - The scope of the Reserved Instance (Region or\n Availability Zone).
\n product-description - The Reserved Instance product platform description\n (Linux/UNIX | Linux with SQL Server Standard | Linux\n with SQL Server Web | Linux with SQL Server Enterprise | SUSE\n Linux | Red Hat Enterprise Linux | Red Hat Enterprise Linux\n with HA | Windows | Windows with SQL Server Standard |\n Windows with SQL Server Web | Windows with SQL Server\n Enterprise).
\n reserved-instances-id - The ID of the Reserved Instance.
\n start - The time at which the Reserved Instance purchase request was\n placed (for example, 2014-08-07T11:54:42.000Z).
\n state - The state of the Reserved Instance (payment-pending\n | active | payment-failed | retired).
\n tag: - The key/value combination of a tag assigned to the resource. Use the tag key in the filter name and the tag value as the filter value.\n For example, to find all resources that have a tag with the key Owner and the value TeamA, specify tag:Owner for the filter name and TeamA for the filter value.
\n tag-key - The key of a tag assigned to the resource. Use this filter to find all resources assigned a tag with a specific key, regardless of the tag value.
\n usage-price - The usage price of the Reserved Instance, per hour (for\n example, 0.84).
The IDs of the Availability Zones.
", + "smithy.api#xmlName": "availabilityZoneIdSet" + } + }, "Cidrs": { "target": "com.amazonaws.ec2#ValueStringList", "traits": { @@ -97007,6 +97041,14 @@ "smithy.api#xmlName": "tagSet" } }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#String", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } + }, "ReservedInstancesId": { "target": "com.amazonaws.ec2#String", "traits": { @@ -97142,6 +97184,14 @@ "smithy.api#documentation": "Whether the Reserved Instance is applied to instances in a Region or instances in a\n specific Availability Zone.
", "smithy.api#xmlName": "scope" } + }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#String", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } } }, "traits": { @@ -97492,6 +97542,14 @@ "smithy.api#xmlName": "scope" } }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#AvailabilityZoneId", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } + }, "ReservedInstancesOfferingId": { "target": "com.amazonaws.ec2#String", "traits": { @@ -116199,6 +116257,14 @@ "smithy.api#documentation": "Information about the instances to which the volume is attached.
", "smithy.api#xmlName": "attachmentStatuses" } + }, + "AvailabilityZoneId": { + "target": "com.amazonaws.ec2#String", + "traits": { + "aws.protocols#ec2QueryName": "AvailabilityZoneId", + "smithy.api#documentation": "The ID of the Availability Zone.
", + "smithy.api#xmlName": "availabilityZoneId" + } } }, "traits": { diff --git a/codegen/sdk-codegen/aws-models/iam.json b/codegen/sdk-codegen/aws-models/iam.json index 3670d86e5a25..9e2ece80c6e4 100644 --- a/codegen/sdk-codegen/aws-models/iam.json +++ b/codegen/sdk-codegen/aws-models/iam.json @@ -1364,6 +1364,56 @@ }, "type": "endpoint" }, + { + "conditions": [ + { + "fn": "stringEquals", + "argv": [ + { + "fn": "getAttr", + "argv": [ + { + "ref": "PartitionResult" + }, + "name" + ] + }, + "aws-eusc" + ] + }, + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseFIPS" + }, + false + ] + }, + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + false + ] + } + ], + "endpoint": { + "url": "https://iam.eusc-de-east-1.amazonaws.eu", + "properties": { + "authSchemes": [ + { + "name": "sigv4", + "signingRegion": "eusc-de-east-1" + } + ] + }, + "headers": {} + }, + "type": "endpoint" + }, { "conditions": [ { diff --git a/codegen/sdk-codegen/aws-models/medialive.json b/codegen/sdk-codegen/aws-models/medialive.json index 5eb831e76d8c..f8efd47e62c0 100644 --- a/codegen/sdk-codegen/aws-models/medialive.json +++ b/codegen/sdk-codegen/aws-models/medialive.json @@ -1718,6 +1718,26 @@ "smithy.api#documentation": "Av1 Look Ahead Rate Control" } }, + "com.amazonaws.medialive#Av1RateControlMode": { + "type": "enum", + "members": { + "CBR": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "CBR" + } + }, + "QVBR": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "QVBR" + } + } + }, + "traits": { + "smithy.api#documentation": "Av1 Rate Control Mode" + } + }, "com.amazonaws.medialive#Av1SceneChangeDetect": { "type": "enum", "members": { @@ -1863,6 +1883,20 @@ "smithy.api#documentation": "Configures the timecode burn-in feature. If you enable this feature, the timecode will become part of the video.", "smithy.api#jsonName": "timecodeBurninSettings" } + }, + "Bitrate": { + "target": "com.amazonaws.medialive#__integerMin50000Max8000000", + "traits": { + "smithy.api#documentation": "Average bitrate in bits/second. Required when the rate control mode is CBR. Not used for QVBR.", + "smithy.api#jsonName": "bitrate" + } + }, + "RateControlMode": { + "target": "com.amazonaws.medialive#Av1RateControlMode", + "traits": { + "smithy.api#documentation": "Rate control mode.\n\nQVBR: Quality will match the specified quality level except when it is constrained by the\nmaximum bitrate. Recommended if you or your viewers pay for bandwidth.\n\nCBR: Quality varies, depending on the video complexity. Recommended only if you distribute\nyour assets to devices that cannot handle variable bitrates.", + "smithy.api#jsonName": "rateControlMode" + } } }, "traits": { @@ -28520,6 +28554,13 @@ "smithy.api#documentation": "SRT settings for an SRT output; one destination for each redundant encoder.", "smithy.api#jsonName": "srtSettings" } + }, + "LogicalInterfaceNames": { + "target": "com.amazonaws.medialive#__listOf__string", + "traits": { + "smithy.api#documentation": "Optional assignment of an output to a logical interface on the Node. Only applies to on premises channels.", + "smithy.api#jsonName": "logicalInterfaceNames" + } } }, "traits": { diff --git a/codegen/sdk-codegen/aws-models/mediatailor.json b/codegen/sdk-codegen/aws-models/mediatailor.json index 72eb7e43c4d8..767d697c173b 100644 --- a/codegen/sdk-codegen/aws-models/mediatailor.json +++ b/codegen/sdk-codegen/aws-models/mediatailor.json @@ -7,7 +7,7 @@ "AccessType": { "target": "com.amazonaws.mediatailor#AccessType", "traits": { - "smithy.api#documentation": "The type of authentication used to access content from HttpConfiguration::BaseUrl on your source location.
\n S3_SIGV4 - AWS Signature Version 4 authentication for Amazon S3 hosted virtual-style access. If your source location base URL is an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the bucket where your source content is stored. Your MediaTailor source location baseURL must follow the S3 virtual hosted-style request URL format. For example, https://bucket-name.s3.Region.amazonaws.com/key-name.
Before you can use S3_SIGV4, you must meet these requirements:
• You must allow MediaTailor to access your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For information about configuring access in IAM, see Access management in the IAM User Guide.
\n• The mediatailor.amazonaws.com service principal must have permissions to read all top level manifests referenced by the VodSource packaging configurations.
\n• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
\n\n AUTODETECT_SIGV4 - AWS Signature Version 4 authentication for a set of supported services: MediaPackage Version 2 and Amazon S3 hosted virtual-style access. If your source location base URL is a MediaPackage Version 2 endpoint or an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the resource where your source content is stored.
Before you can use AUTODETECT_SIGV4 with a MediaPackage Version 2 endpoint, you must meet these requirements:
• You must grant MediaTailor access to your MediaPackage endpoint by granting mediatailor.amazonaws.com principal access in an Origin Access policy on the endpoint.
• Your MediaTailor source location base URL must be a MediaPackage V2 endpoint.
\n• The caller of the API must have mediapackagev2:GetObject IAM permissions to read all top level manifests referenced by the MediaTailor source packaging configurations.
Before you can use AUTODETECT_SIGV4 with an Amazon S3 bucket, you must meet these requirements:
• You must grant MediaTailor access to your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For more information about configuring access in IAM, see Access management in the IAM User Guide..
• The mediatailor.amazonaws.com service principal must have permissions to read all top-level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
The type of authentication used to access content from HttpConfiguration::BaseUrl on your source location.
S3_SIGV4 - AWS Signature Version 4 authentication for Amazon S3 hosted virtual-style access. If your source location base URL is an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the bucket where your source content is stored. Your MediaTailor source location baseURL must follow the S3 virtual hosted-style request URL format. For example, https://bucket-name.s3.Region.amazonaws.com/key-name.
Before you can use S3_SIGV4, you must meet these requirements:
• You must allow MediaTailor to access your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For information about configuring access in IAM, see Access management in the IAM User Guide.
• The mediatailor.amazonaws.com service principal must have permissions to read all top level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
AUTODETECT_SIGV4 - AWS Signature Version 4 authentication for a set of supported services: MediaPackage Version 2 and Amazon S3 hosted virtual-style access. If your source location base URL is a MediaPackage Version 2 endpoint or an Amazon S3 bucket, MediaTailor can use AWS Signature Version 4 (SigV4) authentication to access the resource where your source content is stored.
Before you can use AUTODETECT_SIGV4 with a MediaPackage Version 2 endpoint, you must meet these requirements:
• You must grant MediaTailor access to your MediaPackage endpoint by granting mediatailor.amazonaws.com principal access in an Origin Access policy on the endpoint.
• Your MediaTailor source location base URL must be a MediaPackage V2 endpoint.
• The caller of the API must have mediapackagev2:GetObject IAM permissions to read all top level manifests referenced by the MediaTailor source packaging configurations.
Before you can use AUTODETECT_SIGV4 with an Amazon S3 bucket, you must meet these requirements:
• You must grant MediaTailor access to your S3 bucket by granting mediatailor.amazonaws.com principal access in IAM. For more information about configuring access in IAM, see Access management in the IAM User Guide..
• The mediatailor.amazonaws.com service principal must have permissions to read all top-level manifests referenced by the VodSource packaging configurations.
• The caller of the API must have s3:GetObject IAM permissions to read all top level manifests referenced by your MediaTailor VodSource packaging configurations.
Defines the SCTE-35 time_signal message inserted around the ad.
Programs on a channel's schedule can be configured with one or more ad breaks. You can attach a splice_insert SCTE-35 message to the ad break. This message provides basic metadata about the ad break.
See section 9.7.4 of the 2022 SCTE-35 specification for more information.
" + "smithy.api#documentation": "Defines the SCTE-35 time_signal message inserted around the ad.
Programs on a channel's schedule can be configured with one or more ad breaks. You can attach a splice_insert SCTE-35 message to the ad break. This message provides basic metadata about the ad break.
See section 9.7.4 of the 2022 SCTE-35 specification for more information.
" } }, "AdBreakMetadata": { @@ -127,7 +127,7 @@ "StreamingMediaFileConditioning": { "target": "com.amazonaws.mediatailor#StreamingMediaFileConditioning", "traits": { - "smithy.api#documentation": "For ads that have media files with streaming delivery and supported file extensions, indicates what transcoding action MediaTailor takes when it first receives these ads from the ADS. \n TRANSCODE indicates that MediaTailor must transcode the ads. \n NONE indicates that you have already transcoded the ads outside of MediaTailor and don't need them transcoded as part of the ad insertion workflow. \n For more information about ad conditioning see Using preconditioned ads in the Elemental MediaTailor user guide.
For ads that have media files with streaming delivery and supported file extensions, indicates what transcoding action MediaTailor takes when it first receives these ads from the ADS. TRANSCODE indicates that MediaTailor must transcode the ads. NONE indicates that you have already transcoded the ads outside of MediaTailor and don't need them transcoded as part of the ad insertion workflow. For more information about ad conditioning see Using preconditioned ads in the Elemental MediaTailor user guide.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
Settings for customizing what events are included in logs for interactions with the ad decision server (ADS).
\nFor more information about ADS logs, inlcuding descriptions of the event types, see MediaTailor ADS logs description and event types\n in Elemental MediaTailor User Guide.
" + "smithy.api#documentation": "Settings for customizing what events are included in logs for interactions with the ad decision server (ADS).
For more information about ADS logs, inlcuding descriptions of the event types, see MediaTailor ADS logs description and event types in Elemental MediaTailor User Guide.
" } }, "com.amazonaws.mediatailor#AdsInteractionPublishOptInEventType": { @@ -601,7 +601,7 @@ "DynamicVariable": { "target": "com.amazonaws.mediatailor#__string", "traits": { - "smithy.api#documentation": "The dynamic variable(s) that MediaTailor should use as avail matching criteria. MediaTailor only places the prefetched ads into the avail if the avail matches the criteria defined by the dynamic variable. For information about dynamic variables, see Using dynamic ad variables in the MediaTailor User Guide.
\nYou can include up to 100 dynamic variables.
", + "smithy.api#documentation": "The dynamic variable(s) that MediaTailor should use as avail matching criteria. MediaTailor only places the prefetched ads into the avail if the avail matches the criteria defined by the dynamic variable. For information about dynamic variables, see Using dynamic ad variables in the MediaTailor User Guide.
You can include up to 100 dynamic variables.
", "smithy.api#required": {} } }, @@ -614,7 +614,7 @@ } }, "traits": { - "smithy.api#documentation": "MediaTailor only places (consumes) prefetched ads if the ad break meets the criteria defined by the dynamic variables. This gives you granular control over which ad break to place the prefetched ads into.
\nAs an example, let's say that you set DynamicVariable to scte.event_id and Operator to EQUALS, and your playback configuration has an ADS URL of https://my.ads.server.com/path?&podId=[scte.avail_num]&event=[scte.event_id]&duration=[session.avail_duration_secs]. And the prefetch request to the ADS contains these values https://my.ads.server.com/path?&podId=3&event=my-awesome-event&duration=30. MediaTailor will only insert the prefetched ads into the ad break if has a SCTE marker with an event id of my-awesome-event, since it must match the event id that MediaTailor uses to query the ADS.
You can specify up to five AvailMatchingCriteria. If you specify multiple AvailMatchingCriteria, MediaTailor combines them to match using a logical AND. You can model logical OR combinations by creating multiple prefetch schedules.
MediaTailor only places (consumes) prefetched ads if the ad break meets the criteria defined by the dynamic variables. This gives you granular control over which ad break to place the prefetched ads into.
As an example, let's say that you set DynamicVariable to scte.event_id and Operator to EQUALS, and your playback configuration has an ADS URL of https://my.ads.server.com/path?&podId=[scte.avail_num]&event=[scte.event_id]&duration=[session.avail_duration_secs]. And the prefetch request to the ADS contains these values https://my.ads.server.com/path?&podId=3&event=my-awesome-event&duration=30. MediaTailor will only insert the prefetched ads into the ad break if has a SCTE marker with an event id of my-awesome-event, since it must match the event id that MediaTailor uses to query the ADS.
You can specify up to five AvailMatchingCriteria. If you specify multiple AvailMatchingCriteria, MediaTailor combines them to match using a logical AND. You can model logical OR combinations by creating multiple prefetch schedules.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR\n PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP\n PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode for this channel.
\n\n LINEAR - Programs play back-to-back only once.
\n LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
The type of playback mode for this channel.
LINEAR - Programs play back-to-back only once.
LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
The percentage of session logs that MediaTailor sends to your CloudWatch Logs account. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100\n
The percentage of session logs that MediaTailor sends to your CloudWatch Logs account. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
The method used for collecting logs from AWS Elemental MediaTailor. To configure MediaTailor to send logs directly to Amazon CloudWatch Logs, choose LEGACY_CLOUDWATCH. To configure MediaTailor to \n send logs to CloudWatch, which then vends the logs to your destination of choice, choose VENDED_LOGS. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
To use vended logs, you must configure the delivery destination in Amazon CloudWatch, as described in Enable logging from AWS services, Logging that requires additional permissions [V2].
" + "smithy.api#documentation": "The method used for collecting logs from AWS Elemental MediaTailor. To configure MediaTailor to send logs directly to Amazon CloudWatch Logs, choose LEGACY_CLOUDWATCH. To configure MediaTailor to send logs to CloudWatch, which then vends the logs to your destination of choice, choose VENDED_LOGS. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
To use vended logs, you must configure the delivery destination in Amazon CloudWatch, as described in Enable logging from AWS services, Logging that requires additional permissions [V2].
" } }, "AdsInteractionLog": { @@ -1129,7 +1129,7 @@ "FillerSlate": { "target": "com.amazonaws.mediatailor#SlateSource", "traits": { - "smithy.api#documentation": "The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR\n PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP\n PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode to use for this channel.
\n\n LINEAR - The programs in the schedule play once back-to-back in the schedule.
\n LOOP - The programs in the schedule play back-to-back in an endless loop. When the last program in the schedule stops playing, playback loops back to the first program in the schedule.
The type of playback mode to use for this channel.
LINEAR - The programs in the schedule play once back-to-back in the schedule.
LOOP - The programs in the schedule play back-to-back in an endless loop. When the last program in the schedule stops playing, playback loops back to the first program in the schedule.
\n The time-shifted viewing configuration you want to associate to the channel.\n
" + "smithy.api#documentation": "The time-shifted viewing configuration you want to associate to the channel.
" } }, "Audiences": { @@ -1246,7 +1246,7 @@ "TimeShiftConfiguration": { "target": "com.amazonaws.mediatailor#TimeShiftConfiguration", "traits": { - "smithy.api#documentation": "\n The time-shifted viewing configuration assigned to the channel.\n
" + "smithy.api#documentation": "The time-shifted viewing configuration assigned to the channel.
" } }, "Audiences": { @@ -1416,7 +1416,7 @@ "ScheduleType": { "target": "com.amazonaws.mediatailor#PrefetchScheduleType", "traits": { - "smithy.api#documentation": "The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.\n
" + "smithy.api#documentation": "The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.
" } }, "StreamId": { @@ -2373,7 +2373,7 @@ "TimeShiftConfiguration": { "target": "com.amazonaws.mediatailor#TimeShiftConfiguration", "traits": { - "smithy.api#documentation": "\n The time-shifted viewing configuration for the channel.\n
" + "smithy.api#documentation": "The time-shifted viewing configuration for the channel.
" } }, "Audiences": { @@ -2882,7 +2882,7 @@ "NextToken": { "target": "com.amazonaws.mediatailor#__string", "traits": { - "smithy.api#documentation": "(Optional) If the playback configuration has more than MaxResults channel schedules, use NextToken to get the second and subsequent pages of results.
For the first GetChannelScheduleRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more channel schedules to get.
(Optional) If the playback configuration has more than MaxResults channel schedules, use NextToken to get the second and subsequent pages of results.
For the first GetChannelScheduleRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more channel schedules to get.
(Optional) If the playback configuration has more than MaxResults prefetch schedules, use NextToken to get the second and subsequent pages of results.
For the first ListPrefetchSchedulesRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more prefetch schedules to get.
(Optional) If the playback configuration has more than MaxResults prefetch schedules, use NextToken to get the second and subsequent pages of results.
For the first ListPrefetchSchedulesRequest request, omit this value.
For the second and subsequent requests, get the value of NextToken from the previous response and specify that value for NextToken in the request.
If the previous response didn't include a NextToken element, there are no more prefetch schedules to get.
The type of prefetch schedules that you want to list. SINGLE indicates that you want to list the configured single prefetch schedules. RECURRING \n indicates that you want to list the configured recurring prefetch schedules. ALL indicates that you want to list all configured prefetch schedules.
The type of prefetch schedules that you want to list. SINGLE indicates that you want to list the configured single prefetch schedules. RECURRING indicates that you want to list the configured recurring prefetch schedules. ALL indicates that you want to list all configured prefetch schedules.
The percentage of session logs that MediaTailor sends to your configured log destination. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100\n
The percentage of session logs that MediaTailor sends to your configured log destination. For example, if your playback configuration has 1000 sessions and percentEnabled is set to 60, MediaTailor sends logs for 600 of the sessions to CloudWatch Logs. MediaTailor decides at random which of the playback configuration sessions to send logs for. If you want to view logs for a specific session, you can use the debug log mode.
Valid values: 0 - 100
The method used for collecting logs from AWS Elemental MediaTailor. LEGACY_CLOUDWATCH indicates that MediaTailor is sending logs directly to Amazon CloudWatch Logs. VENDED_LOGS indicates that MediaTailor is sending logs to CloudWatch, which then vends the logs to your destination of choice. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
The method used for collecting logs from AWS Elemental MediaTailor. LEGACY_CLOUDWATCH indicates that MediaTailor is sending logs directly to Amazon CloudWatch Logs. VENDED_LOGS indicates that MediaTailor is sending logs to CloudWatch, which then vends the logs to your destination of choice. Supported destinations are CloudWatch Logs log group, Amazon S3 bucket, and Amazon Data Firehose stream.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
For HLS, when set to true, MediaTailor passes through EXT-X-CUE-IN, EXT-X-CUE-OUT, and EXT-X-SPLICEPOINT-SCTE35 ad markers from the origin manifest to the MediaTailor personalized manifest.
No logic is applied to these ad markers. For example, if EXT-X-CUE-OUT has a value of 60, but no ads are filled for that ad break, MediaTailor will not set the value to 0.
Settings for customizing what events are included in logs for interactions with the origin server.
\nFor more information about manifest service logs, including descriptions of the event types, see MediaTailor manifest logs description and event types\n in Elemental MediaTailor User Guide.
" + "smithy.api#documentation": "Settings for customizing what events are included in logs for interactions with the origin server.
For more information about manifest service logs, including descriptions of the event types, see MediaTailor manifest logs description and event types in Elemental MediaTailor User Guide.
" } }, "com.amazonaws.mediatailor#MaxResults": { @@ -4338,7 +4340,7 @@ ], "maxAge": 86400 }, - "smithy.api#documentation": "Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
\nThrough the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
", + "smithy.api#documentation": "Use the AWS Elemental MediaTailor SDKs and CLI to configure scalable ad insertion and linear channels. With MediaTailor, you can assemble existing content into a linear stream and serve targeted ads to viewers while maintaining broadcast quality in over-the-top (OTT) video applications. For information about using the service, including detailed information about the settings covered in this guide, see the AWS Elemental MediaTailor User Guide.
Through the SDKs and the CLI you manage AWS Elemental MediaTailor configurations and channels the same as you do through the console. For example, you specify ad insertion behavior and mapping information for the origin server and the ad decision server (ADS).
", "smithy.api#title": "AWS MediaTailor", "smithy.rules#endpointRuleSet": { "version": "1.0", @@ -5332,7 +5334,7 @@ "DynamicVariables": { "target": "com.amazonaws.mediatailor#__mapOf__string", "traits": { - "smithy.api#documentation": "The dynamic variables to use for substitution during prefetch requests to the ad decision server (ADS).
\nYou initially configure dynamic variables for the ADS URL when you set up your playback configuration. When you specify DynamicVariables for prefetch retrieval, MediaTailor includes the dynamic variables in the request to the ADS.
The dynamic variables to use for substitution during prefetch requests to the ad decision server (ADS).
You initially configure dynamic variables for the ADS URL when you set up your playback configuration. When you specify DynamicVariables for prefetch retrieval, MediaTailor includes the dynamic variables in the request to the ADS.
The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.\n
" + "smithy.api#documentation": "The frequency that MediaTailor creates prefetch schedules. SINGLE indicates that this schedule applies to one ad break. RECURRING indicates that MediaTailor automatically creates a schedule for each ad avail in a live event.
For more information about the prefetch types and when you might use each, see Prefetching ads in Elemental MediaTailor.
" } }, "RecurringPrefetchConfiguration": { @@ -5885,7 +5887,7 @@ } }, "traits": { - "smithy.api#documentation": "With recurring prefetch, MediaTailor automatically prefetches ads for every avail that occurs during the retrieval window. The following\n configurations describe the MediaTailor behavior when prefetching ads for a live event.
" + "smithy.api#documentation": "With recurring prefetch, MediaTailor automatically prefetches ads for every avail that occurs during the retrieval window. The following configurations describe the MediaTailor behavior when prefetching ads for a live event.
" } }, "com.amazonaws.mediatailor#RelativePosition": { @@ -6248,7 +6250,7 @@ } }, "traits": { - "smithy.api#documentation": "The segmentation_descriptor message can contain advanced metadata fields, like content identifiers, to convey a wide range of information about the ad break. MediaTailor writes the ad metadata in the egress manifest as part of the EXT-X-DATERANGE or EventStream ad marker's SCTE-35 data.
\n segmentation_descriptor messages must be sent with the time_signal message type.
See the segmentation_descriptor() table of the 2022 SCTE-35 specification for more information.
The segmentation_descriptor message can contain advanced metadata fields, like content identifiers, to convey a wide range of information about the ad break. MediaTailor writes the ad metadata in the egress manifest as part of the EXT-X-DATERANGE or EventStream ad marker's SCTE-35 data.
segmentation_descriptor messages must be sent with the time_signal message type.
See the segmentation_descriptor() table of the 2022 SCTE-35 specification for more information.
\n The maximum time delay for time-shifted viewing. The minimum allowed maximum time delay is 0 seconds, \n and the maximum allowed maximum time delay is 21600 seconds (6 hours).\n
", + "smithy.api#documentation": "The maximum time delay for time-shifted viewing. The minimum allowed maximum time delay is 0 seconds, and the maximum allowed maximum time delay is 21600 seconds (6 hours).
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "\n The configuration for time-shifted viewing.\n
" + "smithy.api#documentation": "The configuration for time-shifted viewing.
" } }, "com.amazonaws.mediatailor#TimeSignalMessage": { @@ -6586,7 +6588,7 @@ } }, "traits": { - "smithy.api#documentation": "The SCTE-35 time_signal message can be sent with one or more segmentation_descriptor messages. A time_signal message can be sent only if a single segmentation_descriptor message is sent.
The time_signal message contains only the splice_time field which is constructed using a given presentation timestamp. When sending a time_signal message, the splice_command_type field in the splice_info_section message is set to 6 (0x06).
See the time_signal() table of the 2022 SCTE-35 specification for more information.
The SCTE-35 time_signal message can be sent with one or more segmentation_descriptor messages. A time_signal message can be sent only if a single segmentation_descriptor message is sent.
The time_signal message contains only the splice_time field which is constructed using a given presentation timestamp. When sending a time_signal message, the splice_command_type field in the splice_info_section message is set to 6 (0x06).
See the time_signal() table of the 2022 SCTE-35 specification for more information.
Defines when the program plays in the schedule. You can set the value to ABSOLUTE or RELATIVE.
\n ABSOLUTE - The program plays at a specific wall clock time. This setting can only be used for channels using the LINEAR\n PlaybackMode.
Note the following considerations when using ABSOLUTE transitions:
If the preceding program in the schedule has a duration that extends past the wall clock time, MediaTailor truncates the preceding program on a common segment boundary.
\nIf there are gaps in playback, MediaTailor plays the FillerSlate you configured for your linear channel.
\n RELATIVE - The program is inserted into the schedule either before or after a program that you specify via RelativePosition.
Defines when the program plays in the schedule. You can set the value to ABSOLUTE or RELATIVE.
ABSOLUTE - The program plays at a specific wall clock time. This setting can only be used for channels using the LINEAR PlaybackMode.
Note the following considerations when using ABSOLUTE transitions:
If the preceding program in the schedule has a duration that extends past the wall clock time, MediaTailor truncates the preceding program on a common segment boundary.
If there are gaps in playback, MediaTailor plays the FillerSlate you configured for your linear channel.
RELATIVE - The program is inserted into the schedule either before or after a program that you specify via RelativePosition.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR\n PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP\n PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
\n The time-shifted viewing configuration you want to associate to the channel.\n
" + "smithy.api#documentation": "The time-shifted viewing configuration you want to associate to the channel.
" } }, "Audiences": { @@ -6801,7 +6803,7 @@ "FillerSlate": { "target": "com.amazonaws.mediatailor#SlateSource", "traits": { - "smithy.api#documentation": "The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR\n PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP\n PlaybackMode.
The slate used to fill gaps between programs in the schedule. You must configure filler slate if your channel uses the LINEAR PlaybackMode. MediaTailor doesn't support filler slate for channels using the LOOP PlaybackMode.
The type of playback mode for this channel.
\n\n LINEAR - Programs play back-to-back only once.
\n LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
The type of playback mode for this channel.
LINEAR - Programs play back-to-back only once.
LOOP - Programs play back-to-back in an endless loop. When the last program in the schedule plays, playback loops back to the first program in the schedule.
\n The time-shifted viewing configuration for the channel.\n
" + "smithy.api#documentation": "The time-shifted viewing configuration for the channel.
" } }, "Audiences": { diff --git a/codegen/sdk-codegen/aws-models/s3-control.json b/codegen/sdk-codegen/aws-models/s3-control.json index a6f1830c8c3e..24735dd7d1af 100644 --- a/codegen/sdk-codegen/aws-models/s3-control.json +++ b/codegen/sdk-codegen/aws-models/s3-control.json @@ -819,6 +819,29 @@ } ], "rules": [ + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "Endpoint" + } + ] + }, + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + true + ] + } + ], + "error": "Invalid Configuration: DualStack and custom endpoint are not supported", + "type": "error" + }, { "conditions": [ { @@ -834,6 +857,42 @@ "error": "S3Express does not support Dual-stack.", "type": "error" }, + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "Endpoint" + } + ] + }, + { + "fn": "parseURL", + "argv": [ + { + "ref": "Endpoint" + } + ], + "assign": "url" + } + ], + "endpoint": { + "url": "{url#scheme}://{url#authority}", + "properties": { + "authSchemes": [ + { + "disableDoubleEncoding": true, + "name": "sigv4", + "signingName": "s3express", + "signingRegion": "{Region}" + } + ] + }, + "headers": {} + }, + "type": "endpoint" + }, { "conditions": [ { @@ -1309,6 +1368,80 @@ } ], "rules": [ + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "Endpoint" + } + ] + }, + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + true + ] + } + ], + "error": "Invalid Configuration: DualStack and custom endpoint are not supported", + "type": "error" + }, + { + "conditions": [ + { + "fn": "booleanEquals", + "argv": [ + { + "ref": "UseDualStack" + }, + true + ] + } + ], + "error": "S3Express does not support Dual-stack.", + "type": "error" + }, + { + "conditions": [ + { + "fn": "isSet", + "argv": [ + { + "ref": "Endpoint" + } + ] + }, + { + "fn": "parseURL", + "argv": [ + { + "ref": "Endpoint" + } + ], + "assign": "url" + } + ], + "endpoint": { + "url": "{url#scheme}://{url#authority}", + "properties": { + "authSchemes": [ + { + "disableDoubleEncoding": true, + "name": "sigv4", + "signingName": "s3express", + "signingRegion": "{Region}" + } + ] + }, + "headers": {} + }, + "type": "endpoint" + }, { "conditions": [ { @@ -7670,6 +7803,420 @@ "UseDualStack": false, "UseFIPS": false } + }, + { + "documentation": "Access Point APIs on express bucket routed to custom endpoint if provided", + "expect": { + "endpoint": { + "properties": { + "authSchemes": [ + { + "name": "sigv4", + "signingName": "s3express", + "signingRegion": "us-east-1", + "disableDoubleEncoding": true + } + ] + }, + "url": "https://my-endpoint.express-control.s3.aws.dev" + } + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "CreateAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "Bucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157", + "Scope": { + "Prefixes": [], + "Permissions": [] + } + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "GetAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "DeleteAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "PutAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157", + "Policy": "my-policy" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "GetAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "DeleteAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "GetAccessPointPolicyStatus", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "AccessPointName": "myaccesspoint--abcd-ab1--xa-s3", + "Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "Region": "us-east-1", + "RequiresAccountId": true, + "UseDualStack": false, + "UseFIPS": false + } + }, + { + "documentation": "Access Point APIs on express bucket routed to custom endpoint if provided for List", + "expect": { + "endpoint": { + "properties": { + "authSchemes": [ + { + "name": "sigv4", + "signingName": "s3express", + "signingRegion": "us-east-1", + "disableDoubleEncoding": true + } + ] + }, + "url": "https://my-endpoint.express-control.s3.aws.dev" + } + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev" + }, + "operationName": "ListAccessPointsForDirectoryBuckets", + "operationParams": { + "DirectoryBucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "Region": "us-east-1", + "UseS3ExpressControlEndpoint": true, + "Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "RequiresAccountId": true, + "UseDualStack": false, + "UseFIPS": false + } + }, + { + "documentation": "Error on Access Point APIs on express bucket for dual stack", + "expect": { + "error": "S3Express does not support Dual-stack." + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "CreateAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "Bucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157", + "Scope": { + "Prefixes": [], + "Permissions": [] + } + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "DeleteAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "PutAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157", + "Policy": "my-policy" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "DeleteAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPointPolicyStatus", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "AccessPointName": "myaccesspoint--abcd-ab1--xa-s3", + "Region": "us-east-1", + "RequiresAccountId": true, + "UseDualStack": true, + "UseFIPS": false + } + }, + { + "documentation": "Error Access Point APIs on express bucket for dual stack for List", + "expect": { + "error": "S3Express does not support Dual-stack." + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "AWS::UseDualStack": true + }, + "operationName": "ListAccessPointsForDirectoryBuckets", + "operationParams": { + "DirectoryBucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "Region": "us-east-1", + "UseS3ExpressControlEndpoint": true, + "RequiresAccountId": true, + "UseDualStack": true, + "UseFIPS": false + } + }, + { + "documentation": "Error on Access Point APIs on express bucket for custom endpoint and dual stack", + "expect": { + "error": "Invalid Configuration: DualStack and custom endpoint are not supported" + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "CreateAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "Bucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157", + "Scope": { + "Prefixes": [], + "Permissions": [] + } + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "DeleteAccessPoint", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "PutAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157", + "Policy": "my-policy" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "DeleteAccessPointPolicy", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + }, + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "GetAccessPointPolicyStatus", + "operationParams": { + "Name": "myaccesspoint--abcd-ab1--xa-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "AccessPointName": "myaccesspoint--abcd-ab1--xa-s3", + "Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "Region": "us-east-1", + "RequiresAccountId": true, + "UseDualStack": true, + "UseFIPS": false + } + }, + { + "documentation": "Error Access Point APIs on express bucket for custom endpoint and dual stack for List", + "expect": { + "error": "Invalid Configuration: DualStack and custom endpoint are not supported" + }, + "operationInputs": [ + { + "builtInParams": { + "AWS::Region": "us-east-1", + "SDK::Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "AWS::UseDualStack": true + }, + "operationName": "ListAccessPointsForDirectoryBuckets", + "operationParams": { + "DirectoryBucket": "mybucket--abcd-ab1--x-s3", + "AccountId": "871317572157" + } + } + ], + "params": { + "AccountId": "871317572157", + "Region": "us-east-1", + "UseS3ExpressControlEndpoint": true, + "Endpoint": "https://my-endpoint.express-control.s3.aws.dev", + "RequiresAccountId": true, + "UseDualStack": true, + "UseFIPS": false + } } ], "version": "1.0" diff --git a/codegen/sdk-codegen/aws-models/sagemaker.json b/codegen/sdk-codegen/aws-models/sagemaker.json index f57d93179e79..8d0439f1de86 100644 --- a/codegen/sdk-codegen/aws-models/sagemaker.json +++ b/codegen/sdk-codegen/aws-models/sagemaker.json @@ -1,33 +1,5 @@ { "smithy": "2.0", - "metadata": { - "suppressions": [ - { - "id": "HttpMethodSemantics", - "namespace": "*" - }, - { - "id": "HttpResponseCodeSemantics", - "namespace": "*" - }, - { - "id": "PaginatedTrait", - "namespace": "*" - }, - { - "id": "HttpHeaderTrait", - "namespace": "*" - }, - { - "id": "HttpUriConflict", - "namespace": "*" - }, - { - "id": "Service", - "namespace": "*" - } - ] - }, "shapes": { "com.amazonaws.sagemaker#Accept": { "type": "string", @@ -184,7 +156,7 @@ } }, "traits": { - "smithy.api#documentation": "Lists the properties of an action. An action represents an action\n or activity. Some examples are a workflow step and a model deployment. Generally, an\n action involves at least one input artifact or output artifact.
" + "smithy.api#documentation": "Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
" } }, "com.amazonaws.sagemaker#ActivationState": { @@ -221,7 +193,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an association between the source and the destination. A\n source can be associated with multiple destinations, and a destination can be associated\n with multiple sources. An association is a lineage tracking entity. For more information, see\n Amazon SageMaker\n ML Lineage Tracking.
" + "smithy.api#documentation": "Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
" } }, "com.amazonaws.sagemaker#AddAssociationRequest": { @@ -246,7 +218,7 @@ "AssociationType": { "target": "com.amazonaws.sagemaker#AssociationEdgeType", "traits": { - "smithy.api#documentation": "The type of association. The following are suggested uses for each type. Amazon SageMaker\n places no restrictions on their use.
\nContributedTo - The source contributed to the destination or had a part in\n enabling the destination. For example, the training data contributed to the training\n job.
\nAssociatedWith - The source is connected to the destination. For example, an\n approval workflow is associated with a model deployment.
\nDerivedFrom - The destination is a modification of the source. For example, a digest\n output of a channel input for a processing job is derived from the original inputs.
\nProduced - The source generated the destination. For example, a training job\n produced a model artifact.
\nThe type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use.
ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job.
AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment.
DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs.
Produced - The source generated the destination. For example, a training job produced a model artifact.
Adds or overwrites one or more tags for the specified SageMaker resource. You can add\n tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform\n jobs, models, labeling jobs, work teams, endpoint configurations, and\n endpoints.
\nEach tag consists of a key and an optional value. Tag keys must be unique per\n resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
\nTags that you add to a hyperparameter tuning job by calling this API are also\n added to any training jobs that the hyperparameter tuning job launches after you\n call this API, but not to training jobs that the hyperparameter tuning job launched\n before you called this API. To make sure that the tags associated with a\n hyperparameter tuning job are also added to all training jobs that the\n hyperparameter tuning job launches, add the tags when you first create the tuning\n job by specifying them in the Tags parameter of CreateHyperParameterTuningJob\n
Tags that you add to a SageMaker Domain or User Profile by calling this API are\n also added to any Apps that the Domain or User Profile launches after you call this\n API, but not to Apps that the Domain or User Profile launched before you called this\n API. To make sure that the tags associated with a Domain or User Profile are also\n added to all Apps that the Domain or User Profile launches, add the tags when you\n first create the Domain or User Profile by specifying them in the Tags\n parameter of CreateDomain\n or CreateUserProfile.
Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
Tags that you add to a SageMaker Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
", + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
", "smithy.api#required": {} } } @@ -343,7 +315,7 @@ "target": "com.amazonaws.sagemaker#EntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A unique name to identify the additional inference specification. The name must \n be unique within the list of your additional inference specifications for a \n particular model package.
", + "smithy.api#documentation": "A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
", "smithy.api#required": {} } }, @@ -364,7 +336,7 @@ "SupportedTransformInstanceTypes": { "target": "com.amazonaws.sagemaker#TransformInstanceTypes", "traits": { - "smithy.api#documentation": "A list of the instance types on which a transformation job can be run \n or on which an endpoint can be deployed.
" + "smithy.api#documentation": "A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
" } }, "SupportedRealtimeInferenceInstanceTypes": { @@ -387,7 +359,7 @@ } }, "traits": { - "smithy.api#documentation": "A structure of additional Inference Specification. Additional Inference Specification \n specifies details about inference jobs that can be run with models based on\n this model package
" + "smithy.api#documentation": "A structure of additional Inference Specification. Additional Inference Specification specifies details about inference jobs that can be run with models based on this model package
" } }, "com.amazonaws.sagemaker#AdditionalInferenceSpecifications": { @@ -454,7 +426,7 @@ "target": "com.amazonaws.sagemaker#AdditionalS3DataSourceDataType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The data type of the additional data source that you specify for use in inference or\n training.
", + "smithy.api#documentation": "The data type of the additional data source that you specify for use in inference or training.
", "smithy.api#required": {} } }, @@ -462,14 +434,14 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The uniform resource identifier (URI) used to identify an additional data source used\n in inference or training.
", + "smithy.api#documentation": "The uniform resource identifier (URI) used to identify an additional data source used in inference or training.
", "smithy.api#required": {} } }, "CompressionType": { "target": "com.amazonaws.sagemaker#CompressionType", "traits": { - "smithy.api#documentation": "The type of compression used for an additional data source used in inference or\n training. Specify None if your additional data source is not\n compressed.
The type of compression used for an additional data source used in inference or training. Specify None if your additional data source is not compressed.
A data source used for training or inference that is in addition to the input dataset\n or model data.
" + "smithy.api#documentation": "A data source used for training or inference that is in addition to the input dataset or model data.
" } }, "com.amazonaws.sagemaker#AdditionalS3DataSourceDataType": { @@ -675,13 +647,13 @@ "TrainingImage": { "target": "com.amazonaws.sagemaker#AlgorithmImage", "traits": { - "smithy.api#documentation": "The registry path of the Docker image\n that contains the training algorithm.\n For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry\n Paths and Example Code in the Amazon SageMaker developer guide.\n SageMaker supports both registry/repository[:tag] and\n registry/repository[@digest] image path formats. For more information\n about using your custom training container, see Using Your Own Algorithms with\n Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName\n parameter or the image URI of the algorithm container to the\n TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter\n description.
The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
For more information, see the note in the AlgorithmName parameter description.
The name of the algorithm resource to use for the training job. This must be an\n algorithm resource that you created or subscribe to on Amazon Web Services\n Marketplace.
\nYou must specify either the algorithm name to the AlgorithmName\n parameter or the image URI of the algorithm container to the\n TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the\n TrainingImage parameter. If you specify a value for the\n AlgorithmName parameter, you can't specify a value for\n TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you\n don't specify any value for both parameters, the training job might raise a\n null error.
The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace.
You must specify either the algorithm name to the AlgorithmName parameter or the image URI of the algorithm container to the TrainingImage parameter.
Note that the AlgorithmName parameter is mutually exclusive with the TrainingImage parameter. If you specify a value for the AlgorithmName parameter, you can't specify a value for TrainingImage, and vice versa.
If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a null error.
A list of metric definition objects. Each object specifies the metric name and regular\n expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
" + "smithy.api#documentation": "A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
" } }, "EnableSageMakerMetricsTimeSeries": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "To generate and save time-series metrics during training, set to true.\n The default is false and time-series metrics aren't generated except in the\n following cases:
You use one of the SageMaker built-in algorithms
\nYou use one of the following Prebuilt SageMaker Docker Images:
\nTensorflow (version >= 1.15)
\nMXNet (version >= 1.6)
\nPyTorch (version >= 1.3)
\nYou specify at least one MetricDefinition\n
\nTo generate and save time-series metrics during training, set to true. The default is false and time-series metrics aren't generated except in the following cases:
You use one of the SageMaker built-in algorithms
You use one of the following Prebuilt SageMaker Docker Images:
Tensorflow (version >= 1.15)
MXNet (version >= 1.6)
PyTorch (version >= 1.3)
You specify at least one MetricDefinition
The entrypoint script\n for a Docker container used to run a training job. This script takes\n precedence over the default train processing instructions. See How Amazon SageMaker\n Runs Your Training Image for more information.
" + "smithy.api#documentation": "The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
" } }, "ContainerArguments": { "target": "com.amazonaws.sagemaker#TrainingContainerArguments", "traits": { - "smithy.api#documentation": "The arguments for a container used to run a training job. See How Amazon SageMaker\n Runs Your Training Image for additional information.
" + "smithy.api#documentation": "The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
" } }, "TrainingImageConfig": { "target": "com.amazonaws.sagemaker#TrainingImageConfig", "traits": { - "smithy.api#documentation": "The configuration to use an image from a private Docker registry for a training\n job.
" + "smithy.api#documentation": "The configuration to use an image from a private Docker registry for a training job.
" } } }, "traits": { - "smithy.api#documentation": "Specifies the training algorithm to use in a CreateTrainingJob request.
\nSageMaker uses its own SageMaker account credentials to pull and access built-in algorithms\n so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard,\n unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use\n custom algorithms if you require specific access controls.
\nFor more information about algorithms provided by SageMaker, see Algorithms. For\n information about using your own algorithms, see Using Your Own Algorithms with\n Amazon SageMaker.
" + "smithy.api#documentation": "Specifies the training algorithm to use in a CreateTrainingJob request.
SageMaker uses its own SageMaker account credentials to pull and access built-in algorithms so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard, unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use custom algorithms if you require specific access controls.
For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
" } }, "com.amazonaws.sagemaker#AlgorithmStatus": { @@ -876,7 +848,7 @@ "target": "com.amazonaws.sagemaker#EntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the profile for the algorithm. The name must have 1 to 63 characters.\n Valid characters are a-z, A-Z, 0-9, and - (hyphen).
", + "smithy.api#documentation": "The name of the profile for the algorithm. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
", "smithy.api#required": {} } }, @@ -884,19 +856,19 @@ "target": "com.amazonaws.sagemaker#TrainingJobDefinition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The TrainingJobDefinition object that describes the training job that\n SageMaker runs to validate your algorithm.
The TrainingJobDefinition object that describes the training job that SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job that\n SageMaker runs to validate your algorithm.
The TransformJobDefinition object that describes the transform job that SageMaker runs to validate your algorithm.
Defines a training job and a batch transform job that SageMaker runs to validate your\n algorithm.
\nThe data provided in the validation profile is made available to your buyers on\n Amazon Web Services Marketplace.
" + "smithy.api#documentation": "Defines a training job and a batch transform job that SageMaker runs to validate your algorithm.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
" } }, "com.amazonaws.sagemaker#AlgorithmValidationProfiles": { @@ -926,13 +898,13 @@ "target": "com.amazonaws.sagemaker#AlgorithmValidationProfiles", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of AlgorithmValidationProfile objects, each of which specifies a\n training job and batch transform job that SageMaker runs to validate your algorithm.
An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that SageMaker runs to validate your algorithm.
Specifies configurations for one or more training jobs that SageMaker runs to test the\n algorithm.
" + "smithy.api#documentation": "Specifies configurations for one or more training jobs that SageMaker runs to test the algorithm.
" } }, "com.amazonaws.sagemaker#AmazonQSettings": { @@ -962,7 +934,7 @@ "target": "com.amazonaws.sagemaker#LambdaFunctionArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
\nFor built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
\n Bounding box - Finds the most similar boxes from\n different workers based on the Jaccard index of the boxes.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox\n
\n Image classification - Uses a variant of the\n Expectation Maximization approach to estimate the true class of an image based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass\n
\n Multi-label image classification - Uses a variant of\n the Expectation Maximization approach to estimate the true classes of an image based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel\n
\n Semantic segmentation - Treats each pixel in an image\n as a multi-class classification and treats pixel annotations from workers as \"votes\" for\n the correct label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation\n
\n Text classification - Uses a variant of the\n Expectation Maximization approach to estimate the true class of text based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass\n
\n Multi-label text classification - Uses a variant of\n the Expectation Maximization approach to estimate the true classes of text based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel\n
\n Named entity recognition - Groups similar selections\n and calculates aggregate boundaries, resolving to most-assigned label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition\n
\n Video Classification - Use this task type when you need workers to classify videos using\n predefined labels that you specify. Workers are shown videos and are asked to choose one\n label for each video.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass\n
\n Video Frame Object Detection - Use this task type to\n have workers identify and locate objects in a sequence of video frames (images extracted\n from a video) using bounding boxes. For example, you can use this task to ask workers to\n identify and localize various objects in a series of video frames, such as cars, bikes,\n and pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection\n
\n Video Frame Object Tracking - Use this task type to\n have workers track the movement of objects in a sequence of video frames (images\n extracted from a video) using bounding boxes. For example, you can use this task to ask\n workers to track the movement of objects, such as cars, bikes, and pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking\n
\n 3D Point Cloud Object Detection - Use this task type\n when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids\n around objects. For example, you can use this task type to ask workers to identify\n different types of objects in a point cloud, such as cars, bikes, and\n pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection\n
\n 3D Point Cloud Object Tracking - Use this task type\n when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D\n point cloud frames. For example, you can use this task type to ask workers to track the\n movement of vehicles across multiple point cloud frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking\n
\n 3D Point Cloud Semantic Segmentation - Use this task\n type when you want workers to create a point-level semantic segmentation masks by\n painting objects in a 3D point cloud using different colors where each color is assigned\n to one of the classes you specify.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation\n
\n Use the following ARNs for Label Verification and Adjustment Jobs\n
\nUse label verification and adjustment jobs to review and adjust labels. To learn more,\n see Verify and Adjust Labels .
\n\n Semantic Segmentation Adjustment - Treats each pixel\n in an image as a multi-class classification and treats pixel adjusted annotations from\n workers as \"votes\" for the correct label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation\n
\n Semantic Segmentation Verification - Uses a variant\n of the Expectation Maximization approach to estimate the true class of verification\n judgment for semantic segmentation labels based on annotations from individual\n workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation\n
\n Bounding Box Adjustment - Finds the most similar\n boxes from different workers based on the Jaccard index of the adjusted\n annotations.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox\n
\n Bounding Box Verification - Uses a variant of the\n Expectation Maximization approach to estimate the true class of verification judgement\n for bounding box labels based on annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox\n
\n Video Frame Object Detection Adjustment - \n Use this task type when you want workers to adjust bounding boxes that workers have added \n to video frames to classify and localize objects in a sequence of video frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection\n
\n Video Frame Object Tracking Adjustment - \n Use this task type when you want workers to adjust bounding boxes that workers have added \n to video frames to track object movement across a sequence of video frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking\n
\n 3D Point Cloud Object Detection Adjustment - Use this\n task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection\n
\n 3D Point Cloud Object Tracking Adjustment - Use this\n task type when you want workers to adjust 3D cuboids around objects that appear in a\n sequence of 3D point cloud frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking\n
\n 3D Point Cloud Semantic Segmentation Adjustment - Use this task\n type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
\n\n arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation\n
The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn. For custom labeling workflows, see Post-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Semantic Segmentation Adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
Semantic Segmentation Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
Bounding Box Adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
Bounding Box Verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
3D Point Cloud Object Detection Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
3D Point Cloud Object Tracking Adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation Adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.
arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
The configuration for the file system and the runtime, \n such as the environment variables and entry point.
" + "smithy.api#documentation": "The configuration for the file system and the runtime, such as the environment variables and entry point.
" } } }, @@ -2121,7 +2093,7 @@ } }, "traits": { - "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio\n applications.
" + "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio applications.
" } }, "com.amazonaws.sagemaker#AppList": { @@ -2499,7 +2471,7 @@ } }, "traits": { - "smithy.api#documentation": "Lists a summary of the properties of an artifact. An artifact represents a URI\n addressable object or data. Some examples are a dataset and a model.
" + "smithy.api#documentation": "Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
" } }, "com.amazonaws.sagemaker#AssemblyType": { @@ -2536,7 +2508,7 @@ } ], "traits": { - "smithy.api#documentation": "Associates a trial component with a trial. A trial component can be associated with\n multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
" + "smithy.api#documentation": "Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
" } }, "com.amazonaws.sagemaker#AssociateTrialComponentRequest": { @@ -2690,7 +2662,7 @@ } }, "traits": { - "smithy.api#documentation": "Lists a summary of the properties of an association. An association is an entity that\n links other lineage or experiment entities. An example would be an association between a\n training job and a model.
" + "smithy.api#documentation": "Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
" } }, "com.amazonaws.sagemaker#AssumableRoleArns": { @@ -2711,12 +2683,12 @@ "MaxConcurrentInvocationsPerInstance": { "target": "com.amazonaws.sagemaker#MaxConcurrentInvocationsPerInstance", "traits": { - "smithy.api#documentation": "The maximum number of concurrent requests sent by the SageMaker client to the model\n container. If no value is provided, SageMaker chooses an optimal value.
" + "smithy.api#documentation": "The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
" } } }, "traits": { - "smithy.api#documentation": "Configures the behavior of the client used by SageMaker to interact with the model\n container during asynchronous inference.
" + "smithy.api#documentation": "Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
" } }, "com.amazonaws.sagemaker#AsyncInferenceConfig": { @@ -2725,7 +2697,7 @@ "ClientConfig": { "target": "com.amazonaws.sagemaker#AsyncInferenceClientConfig", "traits": { - "smithy.api#documentation": "Configures the behavior of the client used by SageMaker to interact with the model\n container during asynchronous inference.
" + "smithy.api#documentation": "Configures the behavior of the client used by SageMaker to interact with the model container during asynchronous inference.
" } }, "OutputConfig": { @@ -2747,24 +2719,24 @@ "SuccessTopic": { "target": "com.amazonaws.sagemaker#SnsTopicArn", "traits": { - "smithy.api#documentation": "Amazon SNS topic to post a notification to when inference completes successfully. If no\n topic is provided, no notification is sent on success.
" + "smithy.api#documentation": "Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.
" } }, "ErrorTopic": { "target": "com.amazonaws.sagemaker#SnsTopicArn", "traits": { - "smithy.api#documentation": "Amazon SNS topic to post a notification to when inference fails. If no topic is provided,\n no notification is sent on failure.
" + "smithy.api#documentation": "Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
" } }, "IncludeInferenceResponseIn": { "target": "com.amazonaws.sagemaker#AsyncNotificationTopicTypeList", "traits": { - "smithy.api#documentation": "The Amazon SNS topics where you want the inference response to be included.
\nThe inference response is included only if the response size is less than or equal\n to 128 KB.
\nThe Amazon SNS topics where you want the inference response to be included.
The inference response is included only if the response size is less than or equal to 128 KB.
Specifies the configuration for notifications of inference results for asynchronous\n inference.
" + "smithy.api#documentation": "Specifies the configuration for notifications of inference results for asynchronous inference.
" } }, "com.amazonaws.sagemaker#AsyncInferenceOutputConfig": { @@ -2773,7 +2745,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker\n uses to encrypt the asynchronous inference output in Amazon S3.
\n " + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
" } }, "S3OutputPath": { @@ -2785,7 +2757,7 @@ "NotificationConfig": { "target": "com.amazonaws.sagemaker#AsyncInferenceNotificationConfig", "traits": { - "smithy.api#documentation": "Specifies the configuration for notifications of inference results for asynchronous\n inference.
" + "smithy.api#documentation": "Specifies the configuration for notifications of inference results for asynchronous inference.
" } }, "S3FailurePath": { @@ -2888,7 +2860,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker\n uses to encrypt data generated from an Athena query execution.
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
" } }, "OutputFormat": { @@ -3171,13 +3143,13 @@ "target": "com.amazonaws.sagemaker#AutoMLAlgorithms", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The selection of algorithms trained on your dataset to generate the model candidates for\n an Autopilot job.
\n\n For the tabular problem type\n TabularJobConfig:\n
Selected algorithms must belong to the list corresponding to the training mode\n set in AutoMLJobConfig.Mode (ENSEMBLING or\n HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
\"catboost\"
\n\"extra-trees\"
\n\"fastai\"
\n\"lightgbm\"
\n\"linear-learner\"
\n\"nn-torch\"
\n\"randomforest\"
\n\"xgboost\"
\nIn HYPERPARAMETER_TUNING mode:
\"linear-learner\"
\n\"mlp\"
\n\"xgboost\"
\n\n For the time-series forecasting problem type\n TimeSeriesForecastingJobConfig:\n
Choose your algorithms from this list.
\n\"cnn-qr\"
\n\"deepar\"
\n\"prophet\"
\n\"arima\"
\n\"npts\"
\n\"ets\"
\nThe selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
For the tabular problem type TabularJobConfig:
Selected algorithms must belong to the list corresponding to the training mode set in AutoMLJobConfig.Mode (ENSEMBLING or HYPERPARAMETER_TUNING). Choose a minimum of 1 algorithm.
In ENSEMBLING mode:
\"catboost\"
\"extra-trees\"
\"fastai\"
\"lightgbm\"
\"linear-learner\"
\"nn-torch\"
\"randomforest\"
\"xgboost\"
In HYPERPARAMETER_TUNING mode:
\"linear-learner\"
\"mlp\"
\"xgboost\"
For the time-series forecasting problem type TimeSeriesForecastingJobConfig:
Choose your algorithms from this list.
\"cnn-qr\"
\"deepar\"
\"prophet\"
\"arima\"
\"npts\"
\"ets\"
The selection of algorithms trained on your dataset to generate the model candidates for\n an Autopilot job.
" + "smithy.api#documentation": "The selection of algorithms trained on your dataset to generate the model candidates for an Autopilot job.
" } }, "com.amazonaws.sagemaker#AutoMLAlgorithms": { @@ -3285,12 +3257,12 @@ "InferenceContainerDefinitions": { "target": "com.amazonaws.sagemaker#AutoMLInferenceContainerDefinitions", "traits": { - "smithy.api#documentation": "The mapping of all supported processing unit (CPU, GPU, etc...) to inference container\n definitions for the candidate. This field is populated for the AutoML jobs V2 (for example,\n for jobs created by calling CreateAutoMLJobV2) related to image or text\n classification problem types only.
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the AutoML jobs V2 (for example, for jobs created by calling CreateAutoMLJobV2) related to image or text classification problem types only.
Information about a candidate produced by an AutoML training job, including its status,\n steps, and other properties.
" + "smithy.api#documentation": "Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.
" } }, "com.amazonaws.sagemaker#AutoMLCandidateGenerationConfig": { @@ -3299,13 +3271,13 @@ "FeatureSpecificationS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "A URL to the Amazon S3 data source containing selected features from the input\n data source to run an Autopilot job. You can input FeatureAttributeNames\n (optional) in JSON format as shown below:
\n { \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown\n below:
\n\n { \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }\n
These column keys may not include the target column.
\nIn ensembling mode, Autopilot only supports the following data types: numeric,\n categorical, text, and datetime. In HPO mode,\n Autopilot can support numeric, categorical, text,\n datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1,\n col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are\n provided, then the column keys should be a subset of the column names provided in\n FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in\n [\"col1\", \"col2\", ...] are case sensitive and should be a list of strings\n containing unique values that are a subset of the column names in the input data. The list\n of columns provided must not include the target column.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in [\"col1\", \"col2\", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
Stores the configuration information for the selection of algorithms trained on tabular\n data.
\nThe list of available algorithms to choose from depends on the training mode set in\n \n TabularJobConfig.Mode\n .
\n AlgorithmsConfig should not be set if the training mode is set on\n AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms\n attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is\n empty, CandidateGenerationConfig uses the full set of algorithms for the\n given training mode.
When AlgorithmsConfig is not provided,\n CandidateGenerationConfig uses the full set of algorithms for the\n given training mode.
For the list of all algorithms per problem type and training mode, see \n AutoMLAlgorithmConfig.
\nFor more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
" + "smithy.api#documentation": "Stores the configuration information for the selection of algorithms trained on tabular data.
The list of available algorithms to choose from depends on the training mode set in TabularJobConfig.Mode .
AlgorithmsConfig should not be set if the training mode is set on AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per problem type and training mode, see AutoMLAlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in Autopilot developer guide.
" } } }, @@ -3363,38 +3335,38 @@ "CompressionType": { "target": "com.amazonaws.sagemaker#CompressionType", "traits": { - "smithy.api#documentation": "You can use Gzip or None. The default value is\n None.
You can use Gzip or None. The default value is None.
The name of the target variable in supervised learning, usually represented by\n 'y'.
", + "smithy.api#documentation": "The name of the target variable in supervised learning, usually represented by 'y'.
", "smithy.api#required": {} } }, "ContentType": { "target": "com.amazonaws.sagemaker#ContentType", "traits": { - "smithy.api#documentation": "The content type of the data from the input source. You can use\n text/csv;header=present or x-application/vnd.amazon+parquet.\n The default value is text/csv;header=present.
The content type of the data from the input source. You can use text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The channel type (optional) is an enum string. The default value is\n training. Channels for training and validation must share the same\n ContentType and TargetAttributeName. For information on\n specifying training and validation channel types, see How to specify training and validation datasets.
The channel type (optional) is an enum string. The default value is training. Channels for training and validation must share the same ContentType and TargetAttributeName. For information on specifying training and validation channel types, see How to specify training and validation datasets.
If specified, this column name indicates which column of the dataset should be treated\n as sample weights for use by the objective metric during the training, evaluation, and the\n selection of the best model. This column is not considered as a predictive feature. For\n more information on Autopilot metrics, see Metrics and\n validation.
\nSample weights should be numeric, non-negative, with larger values indicating which rows\n are more important than others. Data points that have invalid or no weight value are\n excluded.
\nSupport for sample weights is available in Ensembling\n mode only.
" + "smithy.api#documentation": "If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
" } } }, "traits": { - "smithy.api#documentation": "A channel is a named input source that training algorithms can consume. The validation\n dataset size is limited to less than 2 GB. The training dataset size must be less than 100\n GB. For more information, see Channel.
\nA validation dataset must contain the same headers as the training dataset.
\nA channel is a named input source that training algorithms can consume. The validation dataset size is limited to less than 2 GB. The training dataset size must be less than 100 GB. For more information, see Channel.
A validation dataset must contain the same headers as the training dataset.
The configuration for using EMR Serverless\n to run the AutoML job V2.
\nTo allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless\n when additional compute resources are needed to process large datasets, you need to provide\n an EmrServerlessComputeConfig object, which includes an\n ExecutionRoleARN attribute, to the AutoMLComputeConfig of the\n AutoML job V2 input request.
By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle\n datasets that would otherwise exceed the initially provisioned resources, without any\n manual intervention from you.
\nEMR Serverless is available for the tabular and time series problem types. We\n recommend setting up this option for tabular datasets larger than 5 GB and time series\n datasets larger than 30 GB.
" + "smithy.api#documentation": "The configuration for using EMR Serverless to run the AutoML job V2.
To allow your AutoML job V2 to automatically initiate a remote job on EMR Serverless when additional compute resources are needed to process large datasets, you need to provide an EmrServerlessComputeConfig object, which includes an ExecutionRoleARN attribute, to the AutoMLComputeConfig of the AutoML job V2 input request.
By seamlessly transitioning to EMR Serverless when required, the AutoML job can handle datasets that would otherwise exceed the initially provisioned resources, without any manual intervention from you.
EMR Serverless is available for the tabular and time series problem types. We recommend setting up this option for tabular datasets larger than 5 GB and time series datasets larger than 30 GB.
" } } }, "traits": { - "smithy.api#documentation": "This data type is intended for use exclusively by SageMaker Canvas and cannot be used in\n other contexts at the moment.
\nSpecifies the compute configuration for an AutoML job V2.
" + "smithy.api#documentation": "This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for an AutoML job V2.
" } }, "com.amazonaws.sagemaker#AutoMLContainerDefinition": { @@ -3435,7 +3407,7 @@ "target": "com.amazonaws.sagemaker#ContainerImage", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more\n information, see \n ContainerDefinition.
", + "smithy.api#documentation": "The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see ContainerDefinition.
", "smithy.api#required": {} } }, @@ -3443,19 +3415,19 @@ "target": "com.amazonaws.sagemaker#Url", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The location of the model artifacts. For more information, see \n ContainerDefinition.
", + "smithy.api#documentation": "The location of the model artifacts. For more information, see ContainerDefinition.
", "smithy.api#required": {} } }, "Environment": { "target": "com.amazonaws.sagemaker#EnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the container. For more information, see \n ContainerDefinition.
" + "smithy.api#documentation": "The environment variables to set in the container. For more information, see ContainerDefinition.
" } } }, "traits": { - "smithy.api#documentation": "A list of container definitions that describe the different containers that make up an\n AutoML candidate. For more information, see \n ContainerDefinition.
" + "smithy.api#documentation": "A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see ContainerDefinition.
" } }, "com.amazonaws.sagemaker#AutoMLContainerDefinitions": { @@ -3492,12 +3464,12 @@ "ValidationFraction": { "target": "com.amazonaws.sagemaker#ValidationFraction", "traits": { - "smithy.api#documentation": "The validation fraction (optional) is a float that specifies the portion of the training\n dataset to be used for validation. The default value is 0.2, and values must be greater\n than 0 and less than 1. We recommend setting this value to be less than 0.5.
" + "smithy.api#documentation": "The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.
" } } }, "traits": { - "smithy.api#documentation": "This structure specifies how to split the data into train and validation\n datasets.
\nThe validation and training datasets must contain the same headers. For jobs created by\n calling CreateAutoMLJob, the validation dataset must be less than 2 GB in\n size.
This structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
Processing unit for an inference container. Currently Autopilot only supports\n CPU or GPU.
Processing unit for an inference container. Currently Autopilot only supports CPU or GPU.
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container\n definitions for the candidate. This field is populated for the V2 API only (for example,\n for jobs created by calling CreateAutoMLJobV2).
The mapping of all supported processing unit (CPU, GPU, etc...) to inference container definitions for the candidate. This field is populated for the V2 API only (for example, for jobs created by calling CreateAutoMLJobV2).
The type of channel. Defines whether the data are used for training or validation. The\n default value is training. Channels for training and\n validation must share the same ContentType\n
The type of channel defaults to training for the time-series forecasting\n problem type.
The type of channel. Defines whether the data are used for training or validation. The default value is training. Channels for training and validation must share the same ContentType
The type of channel defaults to training for the time-series forecasting problem type.
The content type of the data from the input source. The following are the allowed\n content types for different problems:
\nFor tabular problem types: text/csv;header=present or\n x-application/vnd.amazon+parquet. The default value is\n text/csv;header=present.
For image classification: image/png, image/jpeg, or\n image/*. The default value is image/*.
For text classification: text/csv;header=present or\n x-application/vnd.amazon+parquet. The default value is\n text/csv;header=present.
For time-series forecasting: text/csv;header=present or\n x-application/vnd.amazon+parquet. The default value is\n text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or\n x-application/vnd.amazon+parquet. The default value is\n text/csv;header=present.
The content type of the data from the input source. The following are the allowed content types for different problems:
For tabular problem types: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For image classification: image/png, image/jpeg, or image/*. The default value is image/*.
For text classification: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For time-series forecasting: text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
For text generation (LLMs fine-tuning): text/csv;header=present or x-application/vnd.amazon+parquet. The default value is text/csv;header=present.
The allowed compression types depend on the input format and problem type. We allow the\n compression type Gzip for S3Prefix inputs on tabular data only.\n For all other inputs, the compression type should be None. If no compression\n type is provided, we default to None.
The allowed compression types depend on the input format and problem type. We allow the compression type Gzip for S3Prefix inputs on tabular data only. For all other inputs, the compression type should be None. If no compression type is provided, we default to None.
A channel is a named input source that training algorithms can consume. This channel is\n used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
" + "smithy.api#documentation": "A channel is a named input source that training algorithms can consume. This channel is used for AutoML jobs V2 (jobs created by calling CreateAutoMLJobV2).
" } }, "com.amazonaws.sagemaker#AutoMLJobCompletionCriteria": { @@ -3611,24 +3583,24 @@ "MaxCandidates": { "target": "com.amazonaws.sagemaker#MaxCandidates", "traits": { - "smithy.api#documentation": "The maximum number of times a training job is allowed to run.
\nFor text and image classification, time-series forecasting, as well as text generation\n (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the\n maximum value is 750.
" + "smithy.api#documentation": "The maximum number of times a training job is allowed to run.
For text and image classification, time-series forecasting, as well as text generation (LLMs fine-tuning) problem types, the supported value is 1. For tabular problem types, the maximum value is 750.
" } }, "MaxRuntimePerTrainingJobInSeconds": { "target": "com.amazonaws.sagemaker#MaxRuntimePerTrainingJobInSeconds", "traits": { - "smithy.api#documentation": "The maximum time, in seconds, that each training job executed inside hyperparameter\n tuning is allowed to run as part of a hyperparameter tuning job. For more information, see\n the StoppingCondition\n used by the CreateHyperParameterTuningJob action.
\nFor job V2s (jobs created by calling CreateAutoMLJobV2), this field\n controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours\n (259200 seconds).
" + "smithy.api#documentation": "The maximum time, in seconds, that each training job executed inside hyperparameter tuning is allowed to run as part of a hyperparameter tuning job. For more information, see the StoppingCondition used by the CreateHyperParameterTuningJob action.
For job V2s (jobs created by calling CreateAutoMLJobV2), this field controls the runtime of the job candidate.
For TextGenerationJobConfig problem types, the maximum time defaults to 72 hours (259200 seconds).
" } }, "MaxAutoMLJobRuntimeInSeconds": { "target": "com.amazonaws.sagemaker#MaxAutoMLJobRuntimeInSeconds", "traits": { - "smithy.api#documentation": "The maximum runtime, in seconds, an AutoML job has to complete.
\nIf an AutoML job exceeds the maximum runtime, the job is stopped automatically and its\n processing is ended gracefully. The AutoML job identifies the best model whose training was\n completed and marks it as the best-performing model. Any unfinished steps of the job, such\n as automatic one-click Autopilot model deployment, are not completed.
" + "smithy.api#documentation": "The maximum runtime, in seconds, an AutoML job has to complete.
If an AutoML job exceeds the maximum runtime, the job is stopped automatically and its processing is ended gracefully. The AutoML job identifies the best model whose training was completed and marks it as the best-performing model. Any unfinished steps of the job, such as automatic one-click Autopilot model deployment, are not completed.
" } } }, "traits": { - "smithy.api#documentation": "How long a job is allowed to run, or how many candidates a job is allowed to\n generate.
" + "smithy.api#documentation": "How long a job is allowed to run, or how many candidates a job is allowed to generate.
" } }, "com.amazonaws.sagemaker#AutoMLJobConfig": { @@ -3637,7 +3609,7 @@ "CompletionCriteria": { "target": "com.amazonaws.sagemaker#AutoMLJobCompletionCriteria", "traits": { - "smithy.api#documentation": "How long an AutoML job is allowed to run, or how many candidates a job is allowed to\n generate.
" + "smithy.api#documentation": "How long an AutoML job is allowed to run, or how many candidates a job is allowed to generate.
" } }, "SecurityConfig": { @@ -3655,13 +3627,13 @@ "DataSplitConfig": { "target": "com.amazonaws.sagemaker#AutoMLDataSplitConfig", "traits": { - "smithy.api#documentation": "The configuration for splitting the input training dataset.
\nType: AutoMLDataSplitConfig
" + "smithy.api#documentation": "The configuration for splitting the input training dataset.
Type: AutoMLDataSplitConfig
" } }, "Mode": { "target": "com.amazonaws.sagemaker#AutoMLMode", "traits": { - "smithy.api#documentation": "The method that Autopilot uses to train the data. You can either specify the mode manually\n or let Autopilot choose for you based on the dataset size by selecting AUTO. In\n AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than\n 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict\n classification and regression tasks directly from your dataset. This machine learning mode\n combines several base models to produce an optimal predictive model. It then uses a\n stacking ensemble method to combine predictions from contributing members. A multi-stack\n ensemble model can provide better performance over a single model by combining the\n predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by\n ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train\n the best version of a model. HPO automatically selects an algorithm for the type of problem\n you want to solve. Then HPO finds the best hyperparameters according to your objective\n metric. See Autopilot algorithm support for a list of algorithms supported by\n HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
The name of the objective metric used to measure the predictive quality of a machine\n learning system. During training, the model's parameters are updated iteratively to\n optimize its performance based on the feedback provided by the objective metric when\n evaluating the model on the validation dataset.
\nThe list of available metrics supported by Autopilot and the default metric applied when you\n do not specify a metric name explicitly depend on the problem type.
\nFor tabular problem types:
\nList of available metrics:
\n Regression: MAE, MSE, R2,\n RMSE\n
Binary classification: Accuracy, AUC,\n BalancedAccuracy, F1,\n Precision, Recall\n
Multiclass classification: Accuracy,\n BalancedAccuracy, F1macro,\n PrecisionMacro, RecallMacro\n
For a description of each metric, see Autopilot metrics for classification and regression.
\nDefault objective metrics:
\nRegression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
\nList of available metrics: Accuracy\n
For a description of each metric, see Autopilot metrics for text and image classification.
\nDefault objective metrics: Accuracy\n
For time-series forecasting problem types:
\nList of available metrics: RMSE, wQL,\n Average wQL, MASE, MAPE,\n WAPE\n
For a description of each metric, see Autopilot metrics for\n time-series forecasting.
\nDefault objective metrics: AverageWeightedQuantileLoss\n
For text generation problem types (LLMs fine-tuning): \n Fine-tuning language models in Autopilot does not\n require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs\n without requiring multiple candidates to be trained and evaluated. \n Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a\n default objective metric, the cross-entropy loss. After fine-tuning a language model,\n you can evaluate the quality of its generated text using different metrics. \n For a list of the available metrics, see Metrics for\n fine-tuning LLMs in Autopilot.
The name of the objective metric used to measure the predictive quality of a machine learning system. During training, the model's parameters are updated iteratively to optimize its performance based on the feedback provided by the objective metric when evaluating the model on the validation dataset.
The list of available metrics supported by Autopilot and the default metric applied when you do not specify a metric name explicitly depend on the problem type.
For tabular problem types:
List of available metrics:
Regression: MAE, MSE, R2, RMSE
Binary classification: Accuracy, AUC, BalancedAccuracy, F1, Precision, Recall
Multiclass classification: Accuracy, BalancedAccuracy, F1macro, PrecisionMacro, RecallMacro
For a description of each metric, see Autopilot metrics for classification and regression.
Default objective metrics:
Regression: MSE.
Binary classification: F1.
Multiclass classification: Accuracy.
For image or text classification problem types:
List of available metrics: Accuracy
For a description of each metric, see Autopilot metrics for text and image classification.
Default objective metrics: Accuracy
For time-series forecasting problem types:
List of available metrics: RMSE, wQL, Average wQL, MASE, MAPE, WAPE
For a description of each metric, see Autopilot metrics for time-series forecasting.
Default objective metrics: AverageWeightedQuantileLoss
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Settings used to configure an AutoML job V2 for the image classification problem\n type.
" + "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the image classification problem type.
" } }, "TextClassificationJobConfig": { "target": "com.amazonaws.sagemaker#TextClassificationJobConfig", "traits": { - "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the text classification problem\n type.
" + "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the text classification problem type.
" } }, "TimeSeriesForecastingJobConfig": { "target": "com.amazonaws.sagemaker#TimeSeriesForecastingJobConfig", "traits": { - "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the time-series forecasting problem\n type.
" + "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the time-series forecasting problem type.
" } }, "TabularJobConfig": { "target": "com.amazonaws.sagemaker#TabularJobConfig", "traits": { - "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the tabular problem type (regression,\n classification).
" + "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the tabular problem type (regression, classification).
" } }, "TextGenerationJobConfig": { "target": "com.amazonaws.sagemaker#TextGenerationJobConfig", "traits": { - "smithy.api#documentation": "Settings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning)\n problem type.
\nThe text generation models that support fine-tuning in Autopilot are currently accessible\n exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported\n Regions.
\nSettings used to configure an AutoML job V2 for the text generation (LLMs fine-tuning) problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
A collection of settings specific to the problem type used to configure an AutoML job V2.\n There must be one and only one config of the following type.
" + "smithy.api#documentation": "A collection of settings specific to the problem type used to configure an AutoML job V2. There must be one and only one config of the following type.
" } }, "com.amazonaws.sagemaker#AutoMLProblemTypeConfigName": { @@ -4476,7 +4448,7 @@ "target": "com.amazonaws.sagemaker#AutoMLS3DataType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The data type.
\nIf you choose S3Prefix, S3Uri identifies a key name\n prefix. SageMaker AI uses all objects that match the specified key name prefix\n for model training.
The S3Prefix should have the following format:
\n s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE\n
If you choose ManifestFile, S3Uri identifies an object\n that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.
A ManifestFile should have the format shown below:
\n [ {\"prefix\":\n \"s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/\"}, \n
\n \"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1\",\n
\n \"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2\",\n
\n ... \"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N\" ]\n
If you choose AugmentedManifestFile, S3Uri identifies an\n object that is an augmented manifest file in JSON lines format. This file contains\n the data you want to use for model training. AugmentedManifestFile is\n available for V2 API jobs only (for example, for jobs created by calling\n CreateAutoMLJobV2).
Here is a minimal, single-record example of an\n AugmentedManifestFile:
\n {\"source-ref\":\n \"s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg\",\n
\n \"label-metadata\": {\"class-name\": \"cat\" }
For more information on AugmentedManifestFile, see Provide\n Dataset Metadata to Training Jobs with an Augmented Manifest File.
The data type.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker AI uses all objects that match the specified key name prefix for model training.
The S3Prefix should have the following format:
s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker AI to use for model training.
A ManifestFile should have the format shown below:
[ {\"prefix\": \"s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/\"},
\"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1\",
\"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2\",
... \"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N\" ]
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile is available for V2 API jobs only (for example, for jobs created by calling CreateAutoMLJobV2).
Here is a minimal, single-record example of an AugmentedManifestFile:
{\"source-ref\": \"s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg\",
\"label-metadata\": {\"class-name\": \"cat\" }
For more information on AugmentedManifestFile, see Provide Dataset Metadata to Training Jobs with an Augmented Manifest File.
The URL to the Amazon S3 data source. The Uri refers to the Amazon S3\n prefix or ManifestFile depending on the data type.
", + "smithy.api#documentation": "The URL to the Amazon S3 data source. The Uri refers to the Amazon S3 prefix or ManifestFile depending on the data type.
", "smithy.api#required": {} } } @@ -4626,7 +4598,7 @@ } }, "traits": { - "smithy.api#documentation": "The name and an example value of the hyperparameter that you want to use in Autotune.\n If Automatic model tuning (AMT) determines that your hyperparameter is eligible for\n Autotune, an optimal hyperparameter range is selected for you.
" + "smithy.api#documentation": "The name and an example value of the hyperparameter that you want to use in Autotune. If Automatic model tuning (AMT) determines that your hyperparameter is eligible for Autotune, an optimal hyperparameter range is selected for you.
" } }, "com.amazonaws.sagemaker#AutoParameters": { @@ -4659,12 +4631,12 @@ "Alarms": { "target": "com.amazonaws.sagemaker#AlarmList", "traits": { - "smithy.api#documentation": "List of CloudWatch alarms in your account that are configured to monitor metrics on an\n endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the\n deployment.
" + "smithy.api#documentation": "List of CloudWatch alarms in your account that are configured to monitor metrics on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls back the deployment.
" } } }, "traits": { - "smithy.api#documentation": "Automatic rollback configuration for handling endpoint deployment failures and\n recovery.
" + "smithy.api#documentation": "Automatic rollback configuration for handling endpoint deployment failures and recovery.
" } }, "com.amazonaws.sagemaker#Autotune": { @@ -4680,7 +4652,7 @@ } }, "traits": { - "smithy.api#documentation": "A flag to indicate if you want to use Autotune to automatically find optimal values\n for the following fields:
\n\n ParameterRanges: The names and ranges of parameters that a\n hyperparameter tuning job can optimize.
\n\n ResourceLimits: The maximum resources that can be used for a\n training job. These resources include the maximum number of training jobs, the\n maximum runtime of a tuning job, and the maximum number of training jobs to run\n at the same time.
\n\n TrainingJobEarlyStoppingType: A flag that specifies whether or not\n to use early stopping for training jobs launched by a hyperparameter tuning\n job.
\n\n RetryStrategy: The number of times to retry a training job.
\n\n Strategy: Specifies how hyperparameter tuning chooses the\n combinations of hyperparameter values to use for the training jobs that it\n launches.
\n\n ConvergenceDetected: A flag to indicate that Automatic model tuning\n (AMT) has detected model convergence.
\nA flag to indicate if you want to use Autotune to automatically find optimal values for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on\n the storage volume attached to the ML compute instance that hosts the batch transform job.
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the batch transform job.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Deletes specific nodes within a SageMaker HyperPod cluster. BatchDeleteClusterNodes\n accepts a cluster name and a list of node IDs.
To safeguard your work, back up your data to Amazon S3 or an FSx for\n Lustre file system before invoking the API on a worker node group. This will help\n prevent any potential data loss from the instance root volume. For more\n information about backup, see Use the backup script provided by SageMaker HyperPod.
\nIf you want to invoke this API on an existing cluster, you'll first need to\n patch the cluster by running the UpdateClusterSoftware API. For more information about patching a\n cluster, see Update the SageMaker HyperPod platform software of a cluster.
\nDeletes specific nodes within a SageMaker HyperPod cluster. BatchDeleteClusterNodes accepts a cluster name and a list of node IDs.
To safeguard your work, back up your data to Amazon S3 or an FSx for Lustre file system before invoking the API on a worker node group. This will help prevent any potential data loss from the instance root volume. For more information about backup, see Use the backup script provided by SageMaker HyperPod.
If you want to invoke this API on an existing cluster, you'll first need to patch the cluster by running the UpdateClusterSoftware API. For more information about patching a cluster, see Update the SageMaker HyperPod platform software of a cluster.
The error code associated with the error encountered when deleting a node.
\nThe code provides information about the specific issue encountered, such as the node not\n being found, the node's status being invalid for deletion, or the node ID being in use by\n another process.
", + "smithy.api#documentation": "The error code associated with the error encountered when deleting a node.
The code provides information about the specific issue encountered, such as the node not being found, the node's status being invalid for deletion, or the node ID being in use by another process.
", "smithy.api#required": {} } }, @@ -4874,7 +4846,7 @@ "target": "com.amazonaws.sagemaker#ClusterNodeIds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of node IDs to be deleted from the specified cluster.
\nFor SageMaker HyperPod clusters using the Slurm workload manager, you cannot remove\n instances that are configured as Slurm controller nodes.
\nIf you need to delete more than 99 instances, contact Support for assistance.
\nA list of node IDs to be deleted from the specified cluster.
For SageMaker HyperPod clusters using the Slurm workload manager, you cannot remove instances that are configured as Slurm controller nodes.
If you need to delete more than 99 instances, contact Support for assistance.
A map of the resource and BatchDescribeModelPackageError objects reporting the error\n associated with describing the model package.
" + "smithy.api#documentation": "A map of the resource and BatchDescribeModelPackageError objects reporting the error associated with describing the model package.
" } } }, @@ -5096,13 +5068,13 @@ "S3InputMode": { "target": "com.amazonaws.sagemaker#ProcessingS3InputMode", "traits": { - "smithy.api#documentation": "Whether the Pipe or File is used as the input mode for\n transferring data for the monitoring job. Pipe mode is recommended for large\n datasets. File mode is useful for small files that fit in memory. Defaults to\n File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key.\n Defaults to FullyReplicated\n
Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defaults to FullyReplicated
If specified, monitoring jobs substract this time from the start time. For information\n about using offsets for scheduling monitoring jobs, see Schedule Model\n Quality Monitoring Jobs.
" + "smithy.api#documentation": "If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
" } }, "EndTimeOffset": { "target": "com.amazonaws.sagemaker#MonitoringTimeOffsetString", "traits": { - "smithy.api#documentation": "If specified, monitoring jobs subtract this time from the end time. For information\n about using offsets for scheduling monitoring jobs, see Schedule Model\n Quality Monitoring Jobs.
" + "smithy.api#documentation": "If specified, monitoring jobs subtract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
" } }, "ExcludeFeaturesAttribute": { @@ -5158,12 +5130,12 @@ "MaxNumberOfTrainingJobsNotImproving": { "target": "com.amazonaws.sagemaker#MaxNumberOfTrainingJobsNotImproving", "traits": { - "smithy.api#documentation": "The number of training jobs that have failed to improve model performance by 1% or\n greater over prior training jobs as evaluated against an objective function.
" + "smithy.api#documentation": "The number of training jobs that have failed to improve model performance by 1% or greater over prior training jobs as evaluated against an objective function.
" } } }, "traits": { - "smithy.api#documentation": "A structure that keeps track of which training jobs launched by your hyperparameter\n tuning job are not improving model performance as evaluated against an objective\n function.
" + "smithy.api#documentation": "A structure that keeps track of which training jobs launched by your hyperparameter tuning job are not improving model performance as evaluated against an objective function.
" } }, "com.amazonaws.sagemaker#Bias": { @@ -5216,25 +5188,25 @@ "target": "com.amazonaws.sagemaker#TrafficRoutingConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Defines the traffic routing strategy to shift traffic from the old fleet to the new\n fleet during an endpoint deployment.
", + "smithy.api#documentation": "Defines the traffic routing strategy to shift traffic from the old fleet to the new fleet during an endpoint deployment.
", "smithy.api#required": {} } }, "TerminationWaitInSeconds": { "target": "com.amazonaws.sagemaker#TerminationWaitInSeconds", "traits": { - "smithy.api#documentation": "Additional waiting time in seconds after the completion of an endpoint deployment\n before terminating the old endpoint fleet. Default is 0.
" + "smithy.api#documentation": "Additional waiting time in seconds after the completion of an endpoint deployment before terminating the old endpoint fleet. Default is 0.
" } }, "MaximumExecutionTimeoutInSeconds": { "target": "com.amazonaws.sagemaker#MaximumExecutionTimeoutInSeconds", "traits": { - "smithy.api#documentation": "Maximum execution timeout for the deployment. Note that the timeout value should be\n larger than the total waiting time specified in TerminationWaitInSeconds\n and WaitIntervalInSeconds.
Maximum execution timeout for the deployment. Note that the timeout value should be larger than the total waiting time specified in TerminationWaitInSeconds and WaitIntervalInSeconds.
Update policy for a blue/green deployment. If this update policy is specified, SageMaker\n creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips\n traffic to the new fleet according to the specified traffic routing configuration. Only\n one update policy should be used in the deployment configuration. If no update policy is\n specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting\n by default.
" + "smithy.api#documentation": "Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
" } }, "com.amazonaws.sagemaker#Boolean": { @@ -5343,20 +5315,20 @@ "target": "com.amazonaws.sagemaker#ExplainabilityLocation", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon S3 prefix to the explainability artifacts generated for the AutoML\n candidate.
", + "smithy.api#documentation": "The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.
", "smithy.api#required": {} } }, "ModelInsights": { "target": "com.amazonaws.sagemaker#ModelInsightsLocation", "traits": { - "smithy.api#documentation": "The Amazon S3 prefix to the model insight artifacts generated for the AutoML\n candidate.
" + "smithy.api#documentation": "The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.
" } }, "BacktestResults": { "target": "com.amazonaws.sagemaker#BacktestResultsLocation", "traits": { - "smithy.api#documentation": "The Amazon S3 prefix to the accuracy metrics and the inference results observed\n over the testing window. Available only for the time-series forecasting problem\n type.
" + "smithy.api#documentation": "The Amazon S3 prefix to the accuracy metrics and the inference results observed over the testing window. Available only for the time-series forecasting problem type.
" } } }, @@ -5378,12 +5350,12 @@ "AlgorithmsConfig": { "target": "com.amazonaws.sagemaker#AutoMLAlgorithmsConfig", "traits": { - "smithy.api#documentation": "Your Autopilot job trains a default set of algorithms on your dataset. For tabular and\n time-series data, you can customize the algorithm list by selecting a subset of algorithms\n for your problem type.
\n\n AlgorithmsConfig stores the customized selection of algorithms to train on\n your data.
\n For the tabular problem type\n TabularJobConfig, the list of available algorithms to\n choose from depends on the training mode set in \n AutoMLJobConfig.Mode\n .
\n AlgorithmsConfig should not be set when the training mode\n AutoMLJobConfig.Mode is set to AUTO.
When AlgorithmsConfig is provided, one\n AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for\n AutoMLAlgorithms is empty,\n CandidateGenerationConfig uses the full set of algorithms for\n the given training mode.
When AlgorithmsConfig is not provided,\n CandidateGenerationConfig uses the full set of algorithms for\n the given training mode.
For the list of all algorithms per training mode, see \n AlgorithmConfig.
\nFor more information on each algorithm, see the Algorithm support section in the Autopilot developer guide.
\n\n For the time-series forecasting problem type\n TimeSeriesForecastingJobConfig, choose your algorithms\n from the list provided in \n AlgorithmConfig.
For more information on each algorithm, see the Algorithms\n support for time-series forecasting section in the Autopilot developer\n guide.
\nWhen AlgorithmsConfig is provided, one\n AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for\n AutoMLAlgorithms is empty,\n CandidateGenerationConfig uses the full set of algorithms for\n time-series forecasting.
When AlgorithmsConfig is not provided,\n CandidateGenerationConfig uses the full set of algorithms for\n time-series forecasting.
Your Autopilot job trains a default set of algorithms on your dataset. For tabular and time-series data, you can customize the algorithm list by selecting a subset of algorithms for your problem type.
AlgorithmsConfig stores the customized selection of algorithms to train on your data.
For the tabular problem type TabularJobConfig, the list of available algorithms to choose from depends on the training mode set in AutoMLJobConfig.Mode .
AlgorithmsConfig should not be set when the training mode AutoMLJobConfig.Mode is set to AUTO.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for the given training mode.
For the list of all algorithms per training mode, see AlgorithmConfig.
For more information on each algorithm, see the Algorithm support section in the Autopilot developer guide.
For the time-series forecasting problem type TimeSeriesForecastingJobConfig, choose your algorithms from the list provided in AlgorithmConfig.
For more information on each algorithm, see the Algorithms support for time-series forecasting section in the Autopilot developer guide.
When AlgorithmsConfig is provided, one AutoMLAlgorithms attribute must be set and one only.
If the list of algorithms provided as values for AutoMLAlgorithms is empty, CandidateGenerationConfig uses the full set of algorithms for time-series forecasting.
When AlgorithmsConfig is not provided, CandidateGenerationConfig uses the full set of algorithms for time-series forecasting.
Stores the configuration information for how model candidates are generated using an\n AutoML job V2.
" + "smithy.api#documentation": "Stores the configuration information for how model candidates are generated using an AutoML job V2.
" } }, "com.amazonaws.sagemaker#CandidateName": { @@ -5584,7 +5556,7 @@ "target": "com.amazonaws.sagemaker#CapacitySizeType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the endpoint capacity type.
\n\n INSTANCE_COUNT: The endpoint activates based on the number of\n instances.
\n CAPACITY_PERCENT: The endpoint activates based on the specified\n percentage of capacity.
Specifies the endpoint capacity type.
INSTANCE_COUNT: The endpoint activates based on the number of instances.
CAPACITY_PERCENT: The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of instances or a capacity\n percentage.
", + "smithy.api#documentation": "Defines the capacity size, either as a number of instances or a capacity percentage.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies the type and size of the endpoint capacity to activate for a blue/green\n deployment, a rolling deployment, or a rollback strategy. You can specify your batches\n as either instance count or the overall percentage or your fleet.
\nFor a rollback strategy, if you don't specify the fields in this object, or if you set\n the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls\n all traffic back to the blue fleet.
Specifies the type and size of the endpoint capacity to activate for a blue/green deployment, a rolling deployment, or a rollback strategy. You can specify your batches as either instance count or the overall percentage or your fleet.
For a rollback strategy, if you don't specify the fields in this object, or if you set the Value to 100%, then SageMaker uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
The configuration of the size measurements of the AMI update. Using this\n configuration, you can specify whether SageMaker should update your instance group\n by an amount or percentage of instances.
" + "smithy.api#documentation": "The configuration of the size measurements of the AMI update. Using this configuration, you can specify whether SageMaker should update your instance group by an amount or percentage of instances.
" } }, "com.amazonaws.sagemaker#CapacitySizeType": { @@ -5665,18 +5637,18 @@ "CsvContentTypes": { "target": "com.amazonaws.sagemaker#CsvContentTypes", "traits": { - "smithy.api#documentation": "The list of all content type headers that Amazon SageMaker AI will treat as CSV and\n capture accordingly.
" + "smithy.api#documentation": "The list of all content type headers that Amazon SageMaker AI will treat as CSV and capture accordingly.
" } }, "JsonContentTypes": { "target": "com.amazonaws.sagemaker#JsonContentTypes", "traits": { - "smithy.api#documentation": "The list of all content type headers that SageMaker AI will treat as JSON and\n capture accordingly.
" + "smithy.api#documentation": "The list of all content type headers that SageMaker AI will treat as JSON and capture accordingly.
" } } }, "traits": { - "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified\n Amazon SageMaker AI will by default base64 encode when capturing the data.
" + "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified Amazon SageMaker AI will by default base64 encode when capturing the data.
" } }, "com.amazonaws.sagemaker#CaptureMode": { @@ -5796,7 +5768,7 @@ "target": "com.amazonaws.sagemaker#ParameterValues", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of the categories\n for\n the hyperparameter.
", + "smithy.api#documentation": "A list of the categories for the hyperparameter.
", "smithy.api#required": {} } } @@ -5897,25 +5869,25 @@ "CompressionType": { "target": "com.amazonaws.sagemaker#CompressionType", "traits": { - "smithy.api#documentation": "If training data is compressed, the compression type. The default value is\n None. CompressionType is used only in Pipe input mode. In\n File mode, leave this field unset or set it to None.
If training data is compressed, the compression type. The default value is None. CompressionType is used only in Pipe input mode. In File mode, leave this field unset or set it to None.
Specify RecordIO as the value when input data is in raw format but the training\n algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3\n object in a RecordIO record. If the input data is already in RecordIO format, you don't\n need to set this attribute. For more information, see Create\n a Dataset Using RecordIO.
\nIn File mode, leave this field unset or set it to None.
" + "smithy.api#documentation": "Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format. In this case, SageMaker wraps each individual S3 object in a RecordIO record. If the input data is already in RecordIO format, you don't need to set this attribute. For more information, see Create a Dataset Using RecordIO.
In File mode, leave this field unset or set it to None.
" } }, "InputMode": { "target": "com.amazonaws.sagemaker#TrainingInputMode", "traits": { - "smithy.api#documentation": "(Optional) The input mode to use for the data channel in a training job. If you don't\n set a value for InputMode, SageMaker uses the value set for\n TrainingInputMode. Use this parameter to override the\n TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a\n different input mode from the training job's general setting. To download the data from\n Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a\n Docker volume, use File input mode. To stream data directly from Amazon S3 to\n the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
(Optional) The input mode to use for the data channel in a training job. If you don't set a value for InputMode, SageMaker uses the value set for TrainingInputMode. Use this parameter to override the TrainingInputMode setting in a AlgorithmSpecification request when you have a channel that needs a different input mode from the training job's general setting. To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, use File input mode. To stream data directly from Amazon S3 to the container, choose Pipe input mode.
To use a model for incremental training, choose File input model.
A configuration for a shuffle option for input data in a channel. If you use\n S3Prefix for S3DataType, this shuffles the results of the\n S3 key prefix matches. If you use ManifestFile, the order of the S3 object\n references in the ManifestFile is shuffled. If you use\n AugmentedManifestFile, the order of the JSON lines in the\n AugmentedManifestFile is shuffled. The shuffling order is determined\n using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large\n datasets this ensures that the order of the training data is different for each epoch,\n it helps reduce bias and possible overfitting. In a multi-node training job when\n ShuffleConfig is combined with S3DataDistributionType of\n ShardedByS3Key, the data is shuffled across nodes so that the content\n sent to a particular node on the first epoch might be sent to a different node on the\n second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, shuffling is done at the start of every epoch. With large datasets this ensures that the order of the training data is different for each epoch, it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The allowed input mode, either FILE or PIPE.
\nIn FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon\n Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This\n is the most commonly used input mode.
\nIn PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm\n without using the EBS volume.
", + "smithy.api#documentation": "The allowed input mode, either FILE or PIPE.
In FILE mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode.
In PIPE mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
", "smithy.api#required": {} } } @@ -6002,19 +5974,19 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the S3 path where you want SageMaker to store checkpoints. For example,\n s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store checkpoints. For example, s3://bucket-name/key-name-prefix.
(Optional) The local directory where checkpoints are written. The default directory is\n /opt/ml/checkpoints/.
(Optional) The local directory where checkpoints are written. The default directory is /opt/ml/checkpoints/.
Contains information about the output location for managed spot training checkpoint\n data.
" + "smithy.api#documentation": "Contains information about the output location for managed spot training checkpoint data.
" } }, "com.amazonaws.sagemaker#Cidr": { @@ -6069,24 +6041,24 @@ "CheckJobArn": { "target": "com.amazonaws.sagemaker#String256", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the check processing job that was run by this step's\n execution.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the check processing job that was run by this step's execution.
" } }, "SkipCheck": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "This flag indicates if the drift check against the previous baseline will be skipped\n or not. If it is set to False, the previous baseline of the configured\n check type must be available.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step\n properties BaselineUsedForDriftCheckConstraints and\n BaselineUsedForDriftCheckStatistics. If it is set to\n False, the previous baseline of the configured check type must also be\n available. These can be accessed through the\n BaselineUsedForDriftCheckConstraints property.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints property.
The container for the metadata for the ClarifyCheck step. For more information, see\n the topic on ClarifyCheck step in the Amazon SageMaker Developer\n Guide.
" + "smithy.api#documentation": "The container for the metadata for the ClarifyCheck step. For more information, see the topic on ClarifyCheck step in the Amazon SageMaker Developer Guide.
" } }, "com.amazonaws.sagemaker#ClarifyContentTemplate": { @@ -6115,7 +6087,7 @@ "EnableExplanations": { "target": "com.amazonaws.sagemaker#ClarifyEnableExplanations", "traits": { - "smithy.api#documentation": "A JMESPath boolean expression used to filter which records to explain. Explanations\n are activated by default. See \n EnableExplanations\n for additional information.
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanations for additional information.
Provides the JMESPath expression to extract the features from a model container input\n in JSON Lines format. For example, if FeaturesAttribute is the JMESPath\n expression 'myfeatures', it extracts a list of features\n [1,2,3] from request data '{\"myfeatures\":[1,2,3]}'.
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{\"myfeatures\":[1,2,3]}'.
A template string used to format a JSON record into an acceptable model container\n input. For example, a ContentTemplate string\n '{\"myfeatures\":$features}' will format a list of features\n [1,2,3] into the record string '{\"myfeatures\":[1,2,3]}'.\n Required only when the model container input is in JSON Lines format.
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{\"myfeatures\":$features}' will format a list of features [1,2,3] into the record string '{\"myfeatures\":[1,2,3]}'. Required only when the model container input is in JSON Lines format.
The maximum number of records in a request that the model container can process when\n querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be\n made on, for example, a single line in CSV data. If MaxRecordCount is\n 1, the model container expects one record per request. A value of 2 or\n greater means that the model expects batch requests, which can reduce overhead and speed\n up the inferencing process. If this parameter is not provided, the explainer will tune\n the record count per request according to the model container's capacity at\n runtime.
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
The maximum payload size (MB) allowed of a request from the explainer to the model\n container. Defaults to 6 MB.
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
A zero-based index used to extract a probability value (score) or list from model\n container output in CSV format. If this value is not provided, the entire model\n container output will be treated as a probability value (score) or list.
\n\n Example for a single class model: If the model\n container output consists of a string-formatted prediction label followed by its\n probability: '1,0.6', set ProbabilityIndex to 1\n to select the probability value 0.6.
\n Example for a multiclass model: If the model\n container output consists of a string-formatted prediction label followed by its\n probability: '\"[\\'cat\\',\\'dog\\',\\'fish\\']\",\"[0.1,0.6,0.3]\"', set\n ProbabilityIndex to 1 to select the probability values\n [0.1,0.6,0.3].
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.
Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.
Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '\"[\\'cat\\',\\'dog\\',\\'fish\\']\",\"[0.1,0.6,0.3]\"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
A zero-based index used to extract a label header or list of label headers from model\n container output in CSV format.
\n\n Example for a multiclass model: If the model\n container output consists of label headers followed by probabilities:\n '\"[\\'cat\\',\\'dog\\',\\'fish\\']\",\"[0.1,0.6,0.3]\"', set\n LabelIndex to 0 to select the label headers\n ['cat','dog','fish'].
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.
Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '\"[\\'cat\\',\\'dog\\',\\'fish\\']\",\"[0.1,0.6,0.3]\"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
A JMESPath expression used to extract the probability (or score) from the model\n container output if the model container is in JSON Lines format.
\n\n Example: If the model container output of a single\n request is '{\"predicted_label\":1,\"probability\":0.6}', then set\n ProbabilityAttribute to 'probability'.
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.
Example: If the model container output of a single request is '{\"predicted_label\":1,\"probability\":0.6}', then set ProbabilityAttribute to 'probability'.
A JMESPath expression used to locate the list of label headers in the model container\n output.
\n\n Example: If the model container output of a batch\n request is '{\"labels\":[\"cat\",\"dog\",\"fish\"],\"probability\":[0.6,0.3,0.1]}',\n then set LabelAttribute to 'labels' to extract the list of\n label headers [\"cat\",\"dog\",\"fish\"]\n
A JMESPath expression used to locate the list of label headers in the model container output.
Example: If the model container output of a batch request is '{\"labels\":[\"cat\",\"dog\",\"fish\"],\"probability\":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers [\"cat\",\"dog\",\"fish\"]
For multiclass classification problems, the label headers are the names of the\n classes. Otherwise, the label header is the name of the predicted label. These are used\n to help readability for the output of the InvokeEndpoint API. See the\n response section under Invoke the endpoint\n in the Developer Guide for more information. If there are no label headers in the model\n container output, provide them manually using this parameter.
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter.
The names of the features. If provided, these are included in the endpoint response\n payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint\n in the Developer Guide for more information.
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP\n explainability. If provided, FeatureTypes must have at least one\n 'text' string (for example, ['text']). If\n FeatureTypes is not provided, the explainer infers the feature types\n based on the baseline data. The feature types are included in the endpoint response\n payload. For additional information see the response section under Invoke the endpoint\n in the Developer Guide for more information.
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information.
The MIME type of the baseline data. Choose from 'text/csv' or\n 'application/jsonlines'. Defaults to 'text/csv'.
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
The inline SHAP baseline data in string format. ShapBaseline can have one\n or multiple records to be used as the baseline dataset. The format of the SHAP baseline\n file should be the same format as the training dataset. For example, if the training\n dataset is in CSV format and each record contains four features, and all features are\n numerical, then the format of the baseline data should also share these characteristics.\n For natural language processing (NLP) of text columns, the baseline value should be the\n value used to replace the unit of text specified by the Granularity of the\n TextConfig parameter. The size limit for ShapBasline is 4\n KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB\n of baseline data.
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is\n stored. The format of the SHAP baseline file should be the same format as the format of\n the training dataset. For example, if the training dataset is in CSV format, and each\n record in the training dataset has four features, and all features are numerical, then\n the baseline file should also have this same format. Each record should contain only the\n features. If you are using a virtual private cloud (VPC), the\n ShapBaselineUri should be accessible to the VPC. For more information\n about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to\n Resources in your Amazon Virtual Private Cloud.
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
The configuration for the SHAP\n baseline (also called the background or reference dataset) of the Kernal\n SHAP algorithm.
\nThe number of records in the baseline data determines the size of the\n synthetic dataset, which has an impact on latency of explainability\n requests. For more information, see the Synthetic\n data of Configure and create an endpoint.
\n\n ShapBaseline and ShapBaselineUri are mutually\n exclusive parameters. One or the either is required to configure a SHAP\n baseline.
The configuration for the SHAP baseline (also called the background or reference dataset) of the Kernal SHAP algorithm.
The number of records in the baseline data determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
ShapBaseline and ShapBaselineUri are mutually exclusive parameters. One or the either is required to configure a SHAP baseline.
The number of samples to be used for analysis by the Kernal SHAP algorithm.
\nThe number of samples determines the size of the synthetic dataset, which has an\n impact on latency of explainability requests. For more information, see the\n Synthetic data of Configure and create an endpoint.
\nThe number of samples to be used for analysis by the Kernal SHAP algorithm.
The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds\n units (false) for model predictions. Defaults to false.
" + "smithy.api#documentation": "A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
" } }, "Seed": { "target": "com.amazonaws.sagemaker#ClarifyShapSeed", "traits": { - "smithy.api#documentation": "The starting value used to initialize the random number generator in the explainer.\n Provide a value for this parameter to obtain a deterministic SHAP result.
" + "smithy.api#documentation": "The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
" } }, "TextConfig": { "target": "com.amazonaws.sagemaker#ClarifyTextConfig", "traits": { - "smithy.api#documentation": "A parameter that indicates if text features are treated as text and explanations are\n provided for individual units of text. Required for natural language processing (NLP)\n explainability only.
" + "smithy.api#documentation": "A parameter that indicates if text features are treated as text and explanations are provided for individual units of text. Required for natural language processing (NLP) explainability only.
" } } }, @@ -6450,7 +6422,7 @@ "target": "com.amazonaws.sagemaker#ClarifyTextLanguage", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the language of the text features in ISO 639-1 or\n ISO 639-3 code of a\n supported language.
\nFor a mix of multiple languages, use code 'xx'.
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language.
For a mix of multiple languages, use code 'xx'.
The unit of granularity for the analysis of text features. For example, if the unit is\n 'token', then each token (like a word in English) of the text is\n treated as a feature. SHAP values are computed for each unit/feature.
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
A parameter used to configure the SageMaker Clarify explainer to treat text features as text so\n that explanations are provided for individual units of text. Required only for natural\n language processing (NLP) explainability.
" + "smithy.api#documentation": "A parameter used to configure the SageMaker Clarify explainer to treat text features as text so that explanations are provided for individual units of text. Required only for natural language processing (NLP) explainability.
" } }, "com.amazonaws.sagemaker#ClarifyTextGranularity": { @@ -6915,13 +6887,13 @@ "target": "com.amazonaws.sagemaker#ClusterEbsVolumeSizeInGB", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The size in gigabytes (GB) of the additional EBS volume to be attached to the instances\n in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each\n instance within the SageMaker HyperPod cluster instance group and mounted to\n /opt/sagemaker.
The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to /opt/sagemaker.
Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS)\n volume to each instance of the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
" + "smithy.api#documentation": "Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS) volume to each instance of the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
" } }, "com.amazonaws.sagemaker#ClusterEbsVolumeSizeInGB": { @@ -6948,13 +6920,13 @@ "CurrentCount": { "target": "com.amazonaws.sagemaker#ClusterNonNegativeInstanceCount", "traits": { - "smithy.api#documentation": "The number of instances that are currently in the instance group of a SageMaker HyperPod\n cluster.
" + "smithy.api#documentation": "The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
" } }, "TargetCount": { "target": "com.amazonaws.sagemaker#ClusterInstanceCount", "traits": { - "smithy.api#documentation": "The number of instances you specified to add to the instance group of a SageMaker HyperPod\n cluster.
" + "smithy.api#documentation": "The number of instances you specified to add to the instance group of a SageMaker HyperPod cluster.
" } }, "InstanceGroupName": { @@ -6984,43 +6956,43 @@ "ThreadsPerCore": { "target": "com.amazonaws.sagemaker#ClusterThreadsPerCore", "traits": { - "smithy.api#documentation": "The number you specified to TreadsPerCore in CreateCluster for\n enabling or disabling multithreading. For instance types that support multithreading, you\n can specify 1 for disabling multithreading and 2 for enabling multithreading. For more\n information, see the reference table of CPU cores and\n threads per CPU core per instance type in the Amazon Elastic Compute Cloud User\n Guide.
The number you specified to TreadsPerCore in CreateCluster for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
The additional storage configurations for the instances in the SageMaker HyperPod cluster instance\n group.
" + "smithy.api#documentation": "The additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
" } }, "OnStartDeepHealthChecks": { "target": "com.amazonaws.sagemaker#OnStartDeepHealthChecks", "traits": { - "smithy.api#documentation": "A flag indicating whether deep health checks should be performed when the cluster\n instance group is created or updated.
" + "smithy.api#documentation": "A flag indicating whether deep health checks should be performed when the cluster instance group is created or updated.
" } }, "Status": { "target": "com.amazonaws.sagemaker#InstanceGroupStatus", "traits": { - "smithy.api#documentation": "The current status of the cluster instance group.
\n\n InService: The instance group is active and healthy.
\n Creating: The instance group is being provisioned.
\n Updating: The instance group is being updated.
\n Failed: The instance group has failed to provision or is no longer\n healthy.
\n Degraded: The instance group is degraded, meaning that some instances\n have failed to provision or are no longer healthy.
\n Deleting: The instance group is being deleted.
The current status of the cluster instance group.
InService: The instance group is active and healthy.
Creating: The instance group is being provisioned.
Updating: The instance group is being updated.
Failed: The instance group has failed to provision or is no longer healthy.
Degraded: The instance group is degraded, meaning that some instances have failed to provision or are no longer healthy.
Deleting: The instance group is being deleted.
The Amazon Resource Name (ARN); of the training plan associated with this cluster instance group.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
The Amazon Resource Name (ARN); of the training plan associated with this cluster instance group.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The current status of the training plan associated with this cluster instance\n group.
" + "smithy.api#documentation": "The current status of the training plan associated with this cluster instance group.
" } }, "OverrideVpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "The customized Amazon VPC configuration at the instance group level that\n overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
" + "smithy.api#documentation": "The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
" } }, "ScheduledUpdateConfig": { @@ -7057,7 +7029,7 @@ "target": "com.amazonaws.sagemaker#ClusterInstanceCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the number of instances to add to the instance group of a SageMaker HyperPod\n cluster.
", + "smithy.api#documentation": "Specifies the number of instances to add to the instance group of a SageMaker HyperPod cluster.
", "smithy.api#required": {} } }, @@ -7096,31 +7068,31 @@ "ThreadsPerCore": { "target": "com.amazonaws.sagemaker#ClusterThreadsPerCore", "traits": { - "smithy.api#documentation": "Specifies the value for Threads per core. For instance\n types that support multithreading, you can specify 1 for disabling\n multithreading and 2 for enabling multithreading. For instance types that\n doesn't support multithreading, specify 1. For more information, see the\n reference table of CPU cores and\n threads per CPU core per instance type in the Amazon Elastic Compute Cloud User\n Guide.
Specifies the value for Threads per core. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading. For instance types that doesn't support multithreading, specify 1. For more information, see the reference table of CPU cores and threads per CPU core per instance type in the Amazon Elastic Compute Cloud User Guide.
Specifies the additional storage configurations for the instances in the SageMaker HyperPod cluster\n instance group.
" + "smithy.api#documentation": "Specifies the additional storage configurations for the instances in the SageMaker HyperPod cluster instance group.
" } }, "OnStartDeepHealthChecks": { "target": "com.amazonaws.sagemaker#OnStartDeepHealthChecks", "traits": { - "smithy.api#documentation": "A flag indicating whether deep health checks should be performed when the cluster\n instance group is created or updated.
" + "smithy.api#documentation": "A flag indicating whether deep health checks should be performed when the cluster instance group is created or updated.
" } }, "TrainingPlanArn": { "target": "com.amazonaws.sagemaker#TrainingPlanArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN); of the training plan to use for this cluster instance group.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
The Amazon Resource Name (ARN); of the training plan to use for this cluster instance group.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
To configure multi-AZ deployments, customize the Amazon VPC configuration at the\n instance group level. You can specify different subnets and security groups across\n different AZs in the instance group specification to override a SageMaker HyperPod cluster's default\n Amazon VPC configuration. For more information about deploying a cluster in\n multiple AZs, see Setting up SageMaker HyperPod clusters across multiple AZs.
\nWhen your Amazon VPC and subnets support IPv6, network communications differ\n based on the cluster orchestration platform:
\nSlurm-orchestrated clusters automatically configure nodes with dual IPv6 and\n IPv4 addresses, allowing immediate IPv6 network communications.
\nIn Amazon EKS-orchestrated clusters, nodes receive dual-stack\n addressing, but pods can only use IPv6 when the Amazon EKS cluster is\n explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
\nAdditional resources for IPv6 configuration:
\nFor information about adding IPv6 support to your VPC, see to IPv6\n Support for VPC.
\nFor information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
\nTo configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
\nTo configure multi-AZ deployments, customize the Amazon VPC configuration at the instance group level. You can specify different subnets and security groups across different AZs in the instance group specification to override a SageMaker HyperPod cluster's default Amazon VPC configuration. For more information about deploying a cluster in multiple AZs, see Setting up SageMaker HyperPod clusters across multiple AZs.
When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:
Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.
In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
Additional resources for IPv6 configuration:
For information about adding IPv6 support to your VPC, see to IPv6 Support for VPC.
For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
The unique identifier (ID) of the Availability Zone where the node in the SageMaker HyperPod cluster\n is launched.
" + "smithy.api#documentation": "The unique identifier (ID) of the Availability Zone where the node in the SageMaker HyperPod cluster is launched.
" } } }, "traits": { - "smithy.api#documentation": "Specifies the placement details for the node in the SageMaker HyperPod cluster, including the\n Availability Zone and the unique identifier (ID) of the Availability Zone.
" + "smithy.api#documentation": "Specifies the placement details for the node in the SageMaker HyperPod cluster, including the Availability Zone and the unique identifier (ID) of the Availability Zone.
" } }, "com.amazonaws.sagemaker#ClusterInstanceStatus": { @@ -7247,12 +7219,12 @@ "EbsVolumeConfig": { "target": "com.amazonaws.sagemaker#ClusterEbsVolumeConfig", "traits": { - "smithy.api#documentation": "Defines the configuration for attaching additional Amazon Elastic Block Store (EBS)\n volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is\n attached to each instance within the SageMaker HyperPod cluster instance group and mounted to\n /opt/sagemaker.
Defines the configuration for attaching additional Amazon Elastic Block Store (EBS) volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to /opt/sagemaker.
Defines the configuration for attaching additional storage to the instances in the\n SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
" + "smithy.api#documentation": "Defines the configuration for attaching additional storage to the instances in the SageMaker HyperPod cluster instance group. To learn more, see SageMaker HyperPod release notes: June 20, 2024.
" } }, "com.amazonaws.sagemaker#ClusterInstanceStorageConfigs": { @@ -7945,7 +7917,7 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An Amazon S3 bucket path where your lifecycle scripts are stored.
\nMake sure that the S3 bucket path starts with s3://sagemaker-. The\n IAM role for SageMaker HyperPod has the managed \n AmazonSageMakerClusterInstanceRolePolicy\n attached, which\n allows access to S3 buckets with the specific prefix sagemaker-.
An Amazon S3 bucket path where your lifecycle scripts are stored.
Make sure that the S3 bucket path starts with s3://sagemaker-. The IAM role for SageMaker HyperPod has the managed AmazonSageMakerClusterInstanceRolePolicy attached, which allows access to S3 buckets with the specific prefix sagemaker-.
The file name of the entrypoint script of lifecycle scripts under\n SourceS3Uri. This entrypoint script runs during cluster creation.
The file name of the entrypoint script of lifecycle scripts under SourceS3Uri. This entrypoint script runs during cluster creation.
The customized Amazon VPC configuration at the instance group level that\n overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
" + "smithy.api#documentation": "The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.
" } }, "ThreadsPerCore": { "target": "com.amazonaws.sagemaker#ClusterThreadsPerCore", "traits": { - "smithy.api#documentation": "The number of threads per CPU core you specified under\n CreateCluster.
The number of threads per CPU core you specified under CreateCluster.
The configurations of additional storage specified to the instance group where the\n instance (node) is launched.
" + "smithy.api#documentation": "The configurations of additional storage specified to the instance group where the instance (node) is launched.
" } }, "PrivatePrimaryIp": { @@ -8064,7 +8036,7 @@ "PrivatePrimaryIpv6": { "target": "com.amazonaws.sagemaker#ClusterPrivatePrimaryIpv6", "traits": { - "smithy.api#documentation": "The private primary IPv6 address of the SageMaker HyperPod cluster node when configured with an\n Amazon VPC that supports IPv6 and includes subnets with IPv6 addressing enabled\n in either the cluster Amazon VPC configuration or the instance group Amazon VPC configuration.
" + "smithy.api#documentation": "The private primary IPv6 address of the SageMaker HyperPod cluster node when configured with an Amazon VPC that supports IPv6 and includes subnets with IPv6 addressing enabled in either the cluster Amazon VPC configuration or the instance group Amazon VPC configuration.
" } }, "PrivateDnsHostname": { @@ -8081,7 +8053,7 @@ } }, "traits": { - "smithy.api#documentation": "Details of an instance (also called a node interchangeably) in a\n SageMaker HyperPod cluster.
" + "smithy.api#documentation": "Details of an instance (also called a node interchangeably) in a SageMaker HyperPod cluster.
" } }, "com.amazonaws.sagemaker#ClusterNodeId": { @@ -8180,7 +8152,7 @@ } }, "traits": { - "smithy.api#documentation": "Lists a summary of the properties of an instance (also called a\n node interchangeably) of a SageMaker HyperPod cluster.
" + "smithy.api#documentation": "Lists a summary of the properties of an instance (also called a node interchangeably) of a SageMaker HyperPod cluster.
" } }, "com.amazonaws.sagemaker#ClusterNonNegativeInstanceCount": { @@ -8214,13 +8186,13 @@ "target": "com.amazonaws.sagemaker#EksClusterArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon EKS cluster associated with the SageMaker HyperPod\n cluster.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon EKS cluster associated with the SageMaker HyperPod cluster.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The configuration settings for the Amazon EKS cluster used as the orchestrator for the\n SageMaker HyperPod cluster.
" + "smithy.api#documentation": "The configuration settings for the Amazon EKS cluster used as the orchestrator for the SageMaker HyperPod cluster.
" } }, "com.amazonaws.sagemaker#ClusterPrivateDnsHostname": { @@ -8450,7 +8422,7 @@ "TrainingPlanArns": { "target": "com.amazonaws.sagemaker#TrainingPlanArns", "traits": { - "smithy.api#documentation": "A list of Amazon Resource Names (ARNs) of the training plans associated with this\n cluster.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
A list of Amazon Resource Names (ARNs) of the training plans associated with this cluster.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The configuration for the file system and kernels in a SageMaker image running as a Code Editor app. \n The FileSystemConfig object is not supported.
The configuration for the file system and kernels in a SageMaker image running as a Code Editor app. The FileSystemConfig object is not supported.
The Amazon Resource Name (ARN) of the Code Editor application \n lifecycle configuration.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Code Editor application lifecycle configuration.
" } }, "AppLifecycleManagement": { "target": "com.amazonaws.sagemaker#AppLifecycleManagement", "traits": { - "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of CodeEditor\n applications.
" + "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of CodeEditor applications.
" } }, "BuiltInLifecycleConfigArn": { "target": "com.amazonaws.sagemaker#StudioLifecycleConfigArn", "traits": { - "smithy.api#documentation": "The lifecycle configuration that runs before the default lifecycle configuration. It can\n override changes made in the default lifecycle configuration.
" + "smithy.api#documentation": "The lifecycle configuration that runs before the default lifecycle configuration. It can override changes made in the default lifecycle configuration.
" } } }, "traits": { - "smithy.api#documentation": "The Code Editor application settings.
\nFor more information about Code Editor, see Get started with Code \n Editor in Amazon SageMaker.
" + "smithy.api#documentation": "The Code Editor application settings.
For more information about Code Editor, see Get started with Code Editor in Amazon SageMaker.
" } }, "com.amazonaws.sagemaker#CodeRepositories": { @@ -8541,7 +8513,7 @@ } }, "traits": { - "smithy.api#documentation": "A Git repository that SageMaker AI automatically displays to users for cloning in the\n JupyterServer application.
" + "smithy.api#documentation": "A Git repository that SageMaker AI automatically displays to users for cloning in the JupyterServer application.
" } }, "com.amazonaws.sagemaker#CodeRepositoryArn": { @@ -8662,7 +8634,7 @@ "GitConfig": { "target": "com.amazonaws.sagemaker#GitConfig", "traits": { - "smithy.api#documentation": "Configuration details for the Git repository, including the URL where it is located\n and the ARN of the Amazon Web Services Secrets Manager secret that contains the\n credentials used to access the repository.
" + "smithy.api#documentation": "Configuration details for the Git repository, including the URL where it is located and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
" } } }, @@ -8683,7 +8655,7 @@ "target": "com.amazonaws.sagemaker#CognitoUserPool", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A \n user pool is a user directory in Amazon Cognito. \n With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. \n Your users can also sign in through social identity providers like \n Google, Facebook, Amazon, or Apple, and through SAML identity providers.
", + "smithy.api#documentation": "A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.
", "smithy.api#required": {} } }, @@ -8697,7 +8669,7 @@ } }, "traits": { - "smithy.api#documentation": "Use this parameter to configure your Amazon Cognito workforce. \n A single Cognito workforce is created using and corresponds to a single\n \n Amazon Cognito user pool.
" + "smithy.api#documentation": "Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
" } }, "com.amazonaws.sagemaker#CognitoMemberDefinition": { @@ -8707,7 +8679,7 @@ "target": "com.amazonaws.sagemaker#CognitoUserPool", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An identifier for a user pool. The user pool must be in the same region as the service\n that you are calling.
", + "smithy.api#documentation": "An identifier for a user pool. The user pool must be in the same region as the service that you are calling.
", "smithy.api#required": {} } }, @@ -8723,13 +8695,13 @@ "target": "com.amazonaws.sagemaker#ClientId", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An identifier for an application client. You must create the app client ID using\n Amazon Cognito.
", + "smithy.api#documentation": "An identifier for an application client. You must create the app client ID using Amazon Cognito.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Identifies a Amazon Cognito user group. A user group can be used in on or more work\n teams.
" + "smithy.api#documentation": "Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
" } }, "com.amazonaws.sagemaker#CognitoUserGroup": { @@ -8758,7 +8730,7 @@ "VectorConfig": { "target": "com.amazonaws.sagemaker#VectorConfig", "traits": { - "smithy.api#documentation": "Configuration for your vector collection type.
\n\n Dimension: The number of elements in your vector.
Configuration for your vector collection type.
Dimension: The number of elements in your vector.
Parameter values for the tensor collection. The allowed parameters are\n \"name\", \"include_regex\", \"reduction_config\",\n \"save_config\", \"tensor_names\", and\n \"save_histogram\".
Parameter values for the tensor collection. The allowed parameters are \"name\", \"include_regex\", \"reduction_config\", \"save_config\", \"tensor_names\", and \"save_histogram\".
The type of device that the model will run on after the compilation job has\n completed.
" + "smithy.api#documentation": "The type of device that the model will run on after the compilation job has completed.
" } }, "CompilationTargetPlatformOs": { "target": "com.amazonaws.sagemaker#TargetPlatformOs", "traits": { - "smithy.api#documentation": "The type of OS that the model will run on after the compilation job has\n completed.
" + "smithy.api#documentation": "The type of OS that the model will run on after the compilation job has completed.
" } }, "CompilationTargetPlatformArch": { "target": "com.amazonaws.sagemaker#TargetPlatformArch", "traits": { - "smithy.api#documentation": "The type of architecture that the model will run on after the compilation job has\n completed.
" + "smithy.api#documentation": "The type of architecture that the model will run on after the compilation job has completed.
" } }, "CompilationTargetPlatformAccelerator": { "target": "com.amazonaws.sagemaker#TargetPlatformAccelerator", "traits": { - "smithy.api#documentation": "The type of accelerator that the model will run on after the compilation job has\n completed.
" + "smithy.api#documentation": "The type of accelerator that the model will run on after the compilation job has completed.
" } }, "LastModifiedTime": { @@ -9057,18 +9029,18 @@ "ResourceSharingConfig": { "target": "com.amazonaws.sagemaker#ResourceSharingConfig", "traits": { - "smithy.api#documentation": "Resource sharing configuration. This defines how an entity can lend and borrow idle\n compute with other entities within the cluster.
" + "smithy.api#documentation": "Resource sharing configuration. This defines how an entity can lend and borrow idle compute with other entities within the cluster.
" } }, "PreemptTeamTasks": { "target": "com.amazonaws.sagemaker#PreemptTeamTasks", "traits": { - "smithy.api#documentation": "Allows workloads from within an entity to preempt same-team workloads. When set to\n LowerPriority, the entity's lower priority tasks are preempted by their own\n higher priority tasks.
Default is LowerPriority.
Allows workloads from within an entity to preempt same-team workloads. When set to LowerPriority, the entity's lower priority tasks are preempted by their own higher priority tasks.
Default is LowerPriority.
Configuration of the compute allocation definition for an entity. This includes the\n resource sharing option and the setting to preempt low priority tasks.
" + "smithy.api#documentation": "Configuration of the compute allocation definition for an entity. This includes the resource sharing option and the setting to preempt low priority tasks.
" } }, "com.amazonaws.sagemaker#ComputeQuotaId": { @@ -9092,7 +9064,7 @@ "target": "com.amazonaws.sagemaker#InstanceCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of instances to add to the instance group of a SageMaker HyperPod\n cluster.
", + "smithy.api#documentation": "The number of instances to add to the instance group of a SageMaker HyperPod cluster.
", "smithy.api#required": {} } } @@ -9163,7 +9135,7 @@ "ComputeQuotaConfig": { "target": "com.amazonaws.sagemaker#ComputeQuotaConfig", "traits": { - "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing\n option, and the setting to preempt low priority tasks.
" + "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
" } }, "ComputeQuotaTarget": { @@ -9177,7 +9149,7 @@ "ActivationState": { "target": "com.amazonaws.sagemaker#ActivationState", "traits": { - "smithy.api#documentation": "The state of the compute allocation being described. Use to enable or disable compute\n allocation.
\nDefault is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
Assigned entity fair-share weight. Idle compute will be shared across entities based on\n these assigned weights. This weight is only used when FairShare is\n enabled.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the\n default.
" + "smithy.api#documentation": "Assigned entity fair-share weight. Idle compute will be shared across entities based on these assigned weights. This weight is only used when FairShare is enabled.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the default.
" } } }, @@ -9298,7 +9270,7 @@ } }, "traits": { - "smithy.api#documentation": "There was a conflict when you attempted to modify a SageMaker entity such as an\n Experiment or Artifact.
There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.
This parameter is ignored for models that contain only a\n PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of\n the parameter uniquely identifies the container for the purposes of logging and metrics.\n For information, see Use Logs and Metrics\n to Monitor an Inference Pipeline. If you don't specify a value for this\n parameter for a ContainerDefinition that is part of an inference pipeline,\n a unique name is automatically assigned based on the position of the\n ContainerDefinition in the pipeline. If you specify a value for the\n ContainerHostName for any ContainerDefinition that is part\n of an inference pipeline, you must specify a value for the\n ContainerHostName parameter of every ContainerDefinition\n in that pipeline.
This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a\n Docker registry that is accessible from the same VPC that you configure for your\n endpoint. If you are using your own custom algorithm instead of an algorithm provided by\n SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both\n registry/repository[:tag] and registry/repository[@digest]\n image path formats. For more information, see Using Your Own Algorithms with\n Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container\n in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are\n creating.
\nThe path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
Specifies whether the model container is in Amazon ECR or a private Docker registry\n accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a\n private Docker registry, see Use a\n Private Docker Registry for Real-Time Inference Containers.
\nThe model artifacts in an Amazon S3 bucket and the Docker image for inference container\n in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are\n creating.
\nSpecifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers.
The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.
The S3 path where the model artifacts, which result from model training, are stored.\n This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3\n path is required for SageMaker built-in algorithms, but not if you use your own algorithms.\n For more information on built-in algorithms, see Common\n Parameters.
\nThe model artifacts must be in an S3 bucket that is in the same region as the\n model or endpoint you are creating.
\nIf you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token\n Service to download model artifacts from the S3 path you provide. Amazon Web Services STS\n is activated in your Amazon Web Services account by default. If you previously\n deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and\n Deactivating Amazon Web Services STS in an Amazon Web Services Region in the\n Amazon Web Services Identity and Access Management User\n Guide.
\nIf you use a built-in algorithm to create a model, SageMaker requires that you provide\n a S3 path to the model artifacts in ModelDataUrl.
The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl.
Specifies the location of ML model data to deploy.
\nCurrently you cannot use ModelDataSource in conjunction with SageMaker\n batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker\n Marketplace.
Specifies the location of ML model data to deploy.
Currently you cannot use ModelDataSource in conjunction with SageMaker batch transform, SageMaker serverless endpoints, SageMaker multi-model endpoints, and SageMaker Marketplace.
The environment variables to set in the Docker container. Don't include any\n sensitive data in your environment variables.
\nThe maximum length of each key and value in the Environment map is\n 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If\n you pass multiple containers to a CreateModel request, then the maximum\n length of all of their maps, combined, is also 32 KB.
The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables.
The maximum length of each key and value in the Environment map is 1024 bytes. The maximum length of all keys and values in the map, combined, is 32 KB. If you pass multiple containers to a CreateModel request, then the maximum length of all of their maps, combined, is also 32 KB.
The name or Amazon Resource Name (ARN) of the model package to use to create the\n model.
" + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package to use to create the model.
" } }, "InferenceSpecificationName": { @@ -9664,7 +9636,7 @@ } }, "traits": { - "smithy.api#documentation": "Lists a summary of the properties of a context. A context provides a logical grouping\n of other entities.
" + "smithy.api#documentation": "Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
" } }, "com.amazonaws.sagemaker#ContinuousParameterRange": { @@ -9682,7 +9654,7 @@ "target": "com.amazonaws.sagemaker#ParameterValue", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The minimum value for the hyperparameter.\n The\n tuning job uses floating-point values between this value and MaxValuefor\n tuning.
The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values\n between MinValue value and this value for tuning.
The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.
The scale that hyperparameter tuning uses to search the hyperparameter range. For\n information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
\nSageMaker hyperparameter tuning chooses the best scale for the\n hyperparameter.
\nHyperparameter tuning searches the values in the hyperparameter range by\n using a linear scale.
\nHyperparameter tuning searches the values in the hyperparameter range by\n using a logarithmic scale.
\nLogarithmic scaling works only for ranges that have only values greater\n than 0.
\nHyperparameter tuning searches the values in the hyperparameter range by\n using a reverse logarithmic scale.
\nReverse logarithmic scaling works only for ranges that are entirely within\n the range 0<=x<1.0.
\nThe scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.
Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.
A flag to indicating that automatic model tuning (AMT) has detected model convergence,\n defined as a lack of significant improvement (1% or less) against an objective\n metric.
" + "smithy.api#documentation": "A flag to indicating that automatic model tuning (AMT) has detected model convergence, defined as a lack of significant improvement (1% or less) against an objective metric.
" } }, "com.amazonaws.sagemaker#CountryCode": { @@ -9779,7 +9751,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an action. An action is a lineage tracking entity that\n represents an action or activity. For example, a model deployment or an HPO job.\n Generally, an action involves at least one input or output artifact. For more information, see\n Amazon SageMaker\n ML Lineage Tracking.
" + "smithy.api#documentation": "Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
" } }, "com.amazonaws.sagemaker#CreateActionRequest": { @@ -9888,32 +9860,32 @@ "target": "com.amazonaws.sagemaker#TrainingSpecification", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies details about training jobs run by this algorithm, including the\n following:
\nThe Amazon ECR path of the container and the version digest of the\n algorithm.
\nThe hyperparameters that the algorithm supports.
\nThe instance types that the algorithm supports for training.
\nWhether the algorithm supports distributed training.
\nThe metrics that the algorithm emits to Amazon CloudWatch.
\nWhich metrics that the algorithm emits can be used as the objective metric for\n hyperparameter tuning jobs.
\nThe input channels that the algorithm supports for training data. For example,\n an algorithm might support train, validation, and\n test channels.
Specifies details about training jobs run by this algorithm, including the following:
The Amazon ECR path of the container and the version digest of the algorithm.
The hyperparameters that the algorithm supports.
The instance types that the algorithm supports for training.
Whether the algorithm supports distributed training.
The metrics that the algorithm emits to Amazon CloudWatch.
Which metrics that the algorithm emits can be used as the objective metric for hyperparameter tuning jobs.
The input channels that the algorithm supports for training data. For example, an algorithm might support train, validation, and test channels.
Specifies details about inference jobs that the algorithm runs, including the\n following:
\nThe Amazon ECR paths of containers that contain the inference code and model\n artifacts.
\nThe instance types that the algorithm supports for transform jobs and\n real-time endpoints used for inference.
\nThe input and output content formats that the algorithm supports for\n inference.
\nSpecifies details about inference jobs that the algorithm runs, including the following:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the algorithm supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the algorithm supports for inference.
Specifies configurations for one or more training jobs and that SageMaker runs to test the\n algorithm's training code and, optionally, one or more batch transform jobs that SageMaker\n runs to test the algorithm's inference code.
" + "smithy.api#documentation": "Specifies configurations for one or more training jobs and that SageMaker runs to test the algorithm's training code and, optionally, one or more batch transform jobs that SageMaker runs to test the algorithm's inference code.
" } }, "CertifyForMarketplace": { "target": "com.amazonaws.sagemaker#CertifyForMarketplace", "traits": { - "smithy.api#documentation": "Whether to certify the algorithm so that it can be listed in Amazon Web Services\n Marketplace.
" + "smithy.api#documentation": "Whether to certify the algorithm so that it can be listed in Amazon Web Services Marketplace.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -9954,7 +9926,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a running app for the specified UserProfile. This operation is automatically\n invoked by Amazon SageMaker AI upon access to the associated Domain, and when new kernel\n configurations are selected by the user. A user may have multiple Apps active\n simultaneously.
" + "smithy.api#documentation": "Creates a running app for the specified UserProfile. This operation is automatically invoked by Amazon SageMaker AI upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
" } }, "com.amazonaws.sagemaker#CreateAppImageConfig": { @@ -9971,7 +9943,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a configuration for running a SageMaker AI image as a KernelGateway app. The\n configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the\n kernels in the image.
" + "smithy.api#documentation": "Creates a configuration for running a SageMaker AI image as a KernelGateway app. The configuration specifies the Amazon Elastic File System storage volume on the image, and a list of the kernels in the image.
" } }, "com.amazonaws.sagemaker#CreateAppImageConfigRequest": { @@ -9994,7 +9966,7 @@ "KernelGatewayImageConfig": { "target": "com.amazonaws.sagemaker#KernelGatewayImageConfig", "traits": { - "smithy.api#documentation": "The KernelGatewayImageConfig. You can only specify one image kernel in the \n AppImageConfig API. This kernel will be shown to users before the \n image starts. Once the image runs, all kernels are visible in JupyterLab.
" + "smithy.api#documentation": "The KernelGatewayImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel will be shown to users before the image starts. Once the image runs, all kernels are visible in JupyterLab.
" } }, "JupyterLabAppImageConfig": { @@ -10006,7 +9978,7 @@ "CodeEditorAppImageConfig": { "target": "com.amazonaws.sagemaker#CodeEditorAppImageConfig", "traits": { - "smithy.api#documentation": "The CodeEditorAppImageConfig. You can only specify one image kernel \n in the AppImageConfig API. This kernel is shown to users before the image starts. \n After the image runs, all kernels are visible in Code Editor.
The CodeEditorAppImageConfig. You can only specify one image kernel in the AppImageConfig API. This kernel is shown to users before the image starts. After the image runs, all kernels are visible in Code Editor.
The user profile name. If this value is not set, then SpaceName must be\n set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be\n set.
The name of the space. If this value is not set, then UserProfileName must be set.
Each tag consists of a key and an optional value. Tag keys must be unique per\n resource.
" + "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per resource.
" } }, "ResourceSpec": { "target": "com.amazonaws.sagemaker#ResourceSpec", "traits": { - "smithy.api#documentation": "The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image\n created on the instance.
\nThe value of InstanceType passed as part of the ResourceSpec\n in the CreateApp call overrides the value passed as part of the\n ResourceSpec configured for the user profile or the domain. If\n InstanceType is not specified in any of those three ResourceSpec\n values for a KernelGateway app, the CreateApp call fails with a\n request validation error.
The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
The value of InstanceType passed as part of the ResourceSpec in the CreateApp call overrides the value passed as part of the ResourceSpec configured for the user profile or the domain. If InstanceType is not specified in any of those three ResourceSpec values for a KernelGateway app, the CreateApp call fails with a request validation error.
Creates an artifact. An artifact is a lineage tracking entity that\n represents a URI addressable object or data. Some examples are the S3 URI of a dataset and\n the ECR registry path of an image. For more information, see\n Amazon SageMaker\n ML Lineage Tracking.
" + "smithy.api#documentation": "Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
" } }, "com.amazonaws.sagemaker#CreateArtifactRequest": { @@ -10197,7 +10169,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
\nAn AutoML job in SageMaker AI is a fully automated process that allows you to build machine\n learning models with minimal effort and machine learning expertise. When initiating an\n AutoML job, you provide your data and optionally specify parameters tailored to your use\n case. SageMaker AI then automates the entire model development lifecycle, including data\n preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify\n and accelerate the model building process by automating various tasks and exploring\n different combinations of machine learning algorithms, data preprocessing techniques, and\n hyperparameter values. The output of an AutoML job comprises one or more trained models\n ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate\n model leaderboard, allowing you to select the best-performing model for deployment.
\nFor more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html\n in the SageMaker AI developer guide.
\nWe recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as time-series forecasting,\n non-tabular problem types such as image or text classification, and text generation\n (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
" + "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.
An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.
We recommend using the new versions CreateAutoMLJobV2 and DescribeAutoMLJobV2, which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
You can find the best-performing model after you run an AutoML job by calling DescribeAutoMLJobV2 (recommended) or DescribeAutoMLJob.
" } }, "com.amazonaws.sagemaker#CreateAutoMLJobRequest": { @@ -10207,7 +10179,7 @@ "target": "com.amazonaws.sagemaker#AutoMLJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies an Autopilot job. The name must be unique to your account and is case\n insensitive.
", + "smithy.api#documentation": "Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
", "smithy.api#required": {} } }, @@ -10215,7 +10187,7 @@ "target": "com.amazonaws.sagemaker#AutoMLInputDataConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of channel objects that describes the input data and its location. Each channel\n is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A\n minimum of 500 rows is required for the training dataset. There is not a minimum number of\n rows required for the validation dataset.
An array of channel objects that describes the input data and its location. Each channel is a named input source. Similar to InputDataConfig supported by HyperParameterTrainingJobDefinition. Format(s) supported: CSV, Parquet. A minimum of 500 rows is required for the training dataset. There is not a minimum number of rows required for the validation dataset.
Provides information about encryption and the Amazon S3 output path needed to\n store artifacts from an AutoML job. Format(s) supported: CSV.
", + "smithy.api#documentation": "Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job. Format(s) supported: CSV.
", "smithy.api#required": {} } }, "ProblemType": { "target": "com.amazonaws.sagemaker#ProblemType", "traits": { - "smithy.api#documentation": "Defines the type of supervised learning problem available for the candidates. For more\n information, see \n SageMaker Autopilot problem types.
" + "smithy.api#documentation": "Defines the type of supervised learning problem available for the candidates. For more information, see SageMaker Autopilot problem types.
" } }, "AutoMLJobObjective": { "target": "com.amazonaws.sagemaker#AutoMLJobObjective", "traits": { - "smithy.api#documentation": "Specifies a metric to minimize or maximize as the objective of a job. If not specified,\n the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
" + "smithy.api#documentation": "Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. See AutoMLJobObjective for the default values.
" } }, "AutoMLJobConfig": { @@ -10256,19 +10228,19 @@ "GenerateCandidateDefinitionsOnly": { "target": "com.amazonaws.sagemaker#GenerateCandidateDefinitionsOnly", "traits": { - "smithy.api#documentation": "Generates possible candidates without training the models. A candidate is a combination\n of data preprocessors, algorithms, and algorithm parameter settings.
" + "smithy.api#documentation": "Generates possible candidates without training the models. A candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per\n resource.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
" } }, "ModelDeployConfig": { "target": "com.amazonaws.sagemaker#ModelDeployConfig", "traits": { - "smithy.api#documentation": "Specifies how to generate the endpoint name for an automatic one-click Autopilot model\n deployment.
" + "smithy.api#documentation": "Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
" } } }, @@ -10309,7 +10281,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
\nAn AutoML job in SageMaker AI is a fully automated process that allows you to build machine\n learning models with minimal effort and machine learning expertise. When initiating an\n AutoML job, you provide your data and optionally specify parameters tailored to your use\n case. SageMaker AI then automates the entire model development lifecycle, including data\n preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify\n and accelerate the model building process by automating various tasks and exploring\n different combinations of machine learning algorithms, data preprocessing techniques, and\n hyperparameter values. The output of an AutoML job comprises one or more trained models\n ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate\n model leaderboard, allowing you to select the best-performing model for deployment.
\nFor more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html\n in the SageMaker AI developer guide.
\nAutoML jobs V2 support various problem types such as regression, binary, and multiclass\n classification with tabular data, text and image classification, time-series forecasting,\n and fine-tuning of large language models (LLMs) for text generation.
\n\n CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob\n and DescribeAutoMLJob which offer backward compatibility.
\n\n CreateAutoMLJobV2 can manage tabular problem types identical to those of\n its previous version CreateAutoMLJob, as well as time-series forecasting,\n non-tabular problem types such as image or text classification, and text generation\n (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to\n CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see\n AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
" + "smithy.api#documentation": "Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.
An AutoML job in SageMaker AI is a fully automated process that allows you to build machine learning models with minimal effort and machine learning expertise. When initiating an AutoML job, you provide your data and optionally specify parameters tailored to your use case. SageMaker AI then automates the entire model development lifecycle, including data preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify and accelerate the model building process by automating various tasks and exploring different combinations of machine learning algorithms, data preprocessing techniques, and hyperparameter values. The output of an AutoML job comprises one or more trained models ready for deployment and inference. Additionally, SageMaker AI AutoML jobs generate a candidate model leaderboard, allowing you to select the best-performing model for deployment.
For more information about AutoML jobs, see https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html in the SageMaker AI developer guide.
AutoML jobs V2 support various problem types such as regression, binary, and multiclass classification with tabular data, text and image classification, time-series forecasting, and fine-tuning of large language models (LLMs) for text generation.
CreateAutoMLJobV2 and DescribeAutoMLJobV2 are new versions of CreateAutoMLJob and DescribeAutoMLJob which offer backward compatibility.
CreateAutoMLJobV2 can manage tabular problem types identical to those of its previous version CreateAutoMLJob, as well as time-series forecasting, non-tabular problem types such as image or text classification, and text generation (LLMs fine-tuning).
Find guidelines about how to migrate a CreateAutoMLJob to CreateAutoMLJobV2 in Migrate a CreateAutoMLJob to CreateAutoMLJobV2.
For the list of available problem types supported by CreateAutoMLJobV2, see AutoMLProblemTypeConfig.
You can find the best-performing model after you run an AutoML job V2 by calling DescribeAutoMLJobV2.
" } }, "com.amazonaws.sagemaker#CreateAutoMLJobV2Request": { @@ -10319,7 +10291,7 @@ "target": "com.amazonaws.sagemaker#AutoMLJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies an Autopilot job. The name must be unique to your account and is case\n insensitive.
", + "smithy.api#documentation": "Identifies an Autopilot job. The name must be unique to your account and is case insensitive.
", "smithy.api#required": {} } }, @@ -10327,7 +10299,7 @@ "target": "com.amazonaws.sagemaker#AutoMLJobInputDataConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of channel objects describing the input data and their location. Each channel\n is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters.\n The supported formats depend on the problem type:
For tabular problem types: S3Prefix,\n ManifestFile.
For image classification: S3Prefix, ManifestFile,\n AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:
For tabular problem types: S3Prefix, ManifestFile.
For image classification: S3Prefix, ManifestFile, AugmentedManifestFile.
For text classification: S3Prefix.
For time-series forecasting: S3Prefix.
For text generation (LLMs fine-tuning): S3Prefix.
Provides information about encryption and the Amazon S3 output path needed to\n store artifacts from an AutoML job.
", + "smithy.api#documentation": "Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
", "smithy.api#required": {} } }, @@ -10358,7 +10330,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, such as by purpose, owner, or environment. For more\n information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per\n resource.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.
" } }, "SecurityConfig": { @@ -10370,19 +10342,19 @@ "AutoMLJobObjective": { "target": "com.amazonaws.sagemaker#AutoMLJobObjective", "traits": { - "smithy.api#documentation": "Specifies a metric to minimize or maximize as the objective of a job. If not specified,\n the default objective metric depends on the problem type. For the list of default values\n per problem type, see AutoMLJobObjective.
\nFor tabular problem types: You must either provide both the\n AutoMLJobObjective and indicate the type of supervised learning\n problem in AutoMLProblemTypeConfig\n (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning): \n Fine-tuning language models in Autopilot does not\n require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs\n without requiring multiple candidates to be trained and evaluated. \n Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a\n default objective metric, the cross-entropy loss. After fine-tuning a language model,\n you can evaluate the quality of its generated text using different metrics. \n For a list of the available metrics, see Metrics for\n fine-tuning LLMs in Autopilot.
Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.
For tabular problem types: You must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig (TabularJobConfig.ProblemType), or none at all.
For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model\n deployment.
" + "smithy.api#documentation": "Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
" } }, "DataSplitConfig": { "target": "com.amazonaws.sagemaker#AutoMLDataSplitConfig", "traits": { - "smithy.api#documentation": "This structure specifies how to split the data into train and validation\n datasets.
\nThe validation and training datasets must contain the same headers. For jobs created by\n calling CreateAutoMLJob, the validation dataset must be less than 2 GB in\n size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot\n automatically splits the input dataset into training and validation sets.
\nThis structure specifies how to split the data into train and validation datasets.
The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.
This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.
Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing\n persistent clusters for developing large machine learning models, such as large language\n models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the\n Amazon SageMaker Developer Guide.
" + "smithy.api#documentation": "Creates a SageMaker HyperPod cluster. SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide.
" } }, "com.amazonaws.sagemaker#CreateClusterRequest": { @@ -10454,25 +10426,25 @@ "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You\n can control access to and from your resources by configuring your VPC. For more\n information, see Give SageMaker access to resources\n in your Amazon VPC.
\nWhen your Amazon VPC and subnets support IPv6, network communications differ\n based on the cluster orchestration platform:
\nSlurm-orchestrated clusters automatically configure nodes with dual IPv6 and\n IPv4 addresses, allowing immediate IPv6 network communications.
\nIn Amazon EKS-orchestrated clusters, nodes receive dual-stack\n addressing, but pods can only use IPv6 when the Amazon EKS cluster is\n explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
\nAdditional resources for IPv6 configuration:
\nFor information about adding IPv6 support to your VPC, see to IPv6\n Support for VPC.
\nFor information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
\nTo configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
\nSpecifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You can control access to and from your resources by configuring your VPC. For more information, see Give SageMaker access to resources in your Amazon VPC.
When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:
Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.
In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see Amazon EKS IPv6 Cluster Deployment.
Additional resources for IPv6 configuration:
For information about adding IPv6 support to your VPC, see to IPv6 Support for VPC.
For information about creating a new IPv6-compatible VPC, see Amazon VPC Creation Guide.
To configure SageMaker HyperPod with a custom Amazon VPC, see Custom Amazon VPC Setup for SageMaker HyperPod.
Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can\n add tags to your cluster in the same way you add them in other Amazon Web Services services\n that support tagging. To learn more about tagging Amazon Web Services resources in general,\n see Tagging\n Amazon Web Services Resources User Guide.
" + "smithy.api#documentation": "Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see Tagging Amazon Web Services Resources User Guide.
" } }, "Orchestrator": { "target": "com.amazonaws.sagemaker#ClusterOrchestrator", "traits": { - "smithy.api#documentation": "The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, the only supported\n value is \"eks\", which is to use an Amazon Elastic Kubernetes Service (EKS)\n cluster as the orchestrator.
The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, the only supported value is \"eks\", which is to use an Amazon Elastic Kubernetes Service (EKS) cluster as the orchestrator.
The node recovery mode for the SageMaker HyperPod cluster. When set to Automatic,\n SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set\n to None, cluster administrators will need to manually manage any faulty\n cluster instances.
The node recovery mode for the SageMaker HyperPod cluster. When set to Automatic, SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set to None, cluster administrators will need to manually manage any faulty cluster instances.
Create cluster policy configuration. This policy is used for task prioritization and\n fair-share allocation of idle compute. This helps prioritize critical workloads and distributes\n idle compute across entities.
" + "smithy.api#documentation": "Create cluster policy configuration. This policy is used for task prioritization and fair-share allocation of idle compute. This helps prioritize critical workloads and distributes idle compute across entities.
" } }, "com.amazonaws.sagemaker#CreateClusterSchedulerConfigRequest": { @@ -10593,7 +10565,7 @@ "target": "com.amazonaws.sagemaker#CreateCodeRepositoryOutput" }, "traits": { - "smithy.api#documentation": "Creates a Git repository as a resource in your SageMaker AI account. You can\n associate the repository with notebook instances so that you can use Git source control\n for the notebooks you create. The Git repository is a resource in your SageMaker AI\n account, so it can be associated with more than one notebook instance, and it persists\n independently from the lifecycle of any notebook instances it is associated with.
\nThe repository can be hosted either in Amazon Web Services CodeCommit\n or in any other Git repository.
" + "smithy.api#documentation": "Creates a Git repository as a resource in your SageMaker AI account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker AI account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
" } }, "com.amazonaws.sagemaker#CreateCodeRepositoryInput": { @@ -10603,7 +10575,7 @@ "target": "com.amazonaws.sagemaker#EntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the Git repository. The name must have 1 to 63 characters. Valid\n characters are a-z, A-Z, 0-9, and - (hyphen).
", + "smithy.api#documentation": "The name of the Git repository. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
", "smithy.api#required": {} } }, @@ -10611,14 +10583,14 @@ "target": "com.amazonaws.sagemaker#GitConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies details about the repository, including the URL where the repository is\n located, the default branch, and credentials to use to access the repository.
", + "smithy.api#documentation": "Specifies details about the repository, including the URL where the repository is located, the default branch, and credentials to use to access the repository.
", "smithy.api#required": {} } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -10659,7 +10631,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the\n resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
\nIf\n you choose to host your model using Amazon SageMaker AI hosting services, you can use the resulting\n model artifacts as part of the model. You can also use the artifacts with\n Amazon Web Services IoT Greengrass. In that case, deploy them as an ML\n resource.
\nIn the request body, you provide the following:
\nA name for the compilation job
\nInformation about the input model artifacts
\nThe output location for the compiled model and the device (target) that the\n model runs on
\nThe Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker AI assumes to perform\n the model compilation job.
\nYou can also provide a Tag to track the model compilation job's resource\n use and costs. The response body contains the\n CompilationJobArn\n for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation\n job, use DescribeCompilationJob. To get information about multiple model compilation\n jobs, use ListCompilationJobs.
" + "smithy.api#documentation": "Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker AI hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker AI assumes to perform the model compilation job.
You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
" } }, "com.amazonaws.sagemaker#CreateCompilationJobRequest": { @@ -10677,48 +10649,48 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on\n your behalf.
\nDuring model compilation, Amazon SageMaker AI needs your permission to:
\nRead input data from an S3 bucket
\nWrite model artifacts to an S3 bucket
\nWrite logs to Amazon CloudWatch Logs
\nPublish metrics to Amazon CloudWatch
\nYou grant permissions for all of these tasks to an IAM role. To pass this role to\n Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For\n more information, see Amazon SageMaker AI\n Roles.\n
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model compilation, Amazon SageMaker AI needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
The Amazon Resource Name (ARN) of a versioned model package. Provide either a \n ModelPackageVersionArn or an InputConfig object in the \n request syntax. The presence of both objects in the CreateCompilationJob \n request will return an exception.
The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
Provides information about the location of input model artifacts, the name and shape\n of the expected data inputs, and the framework in which the model was trained.
" + "smithy.api#documentation": "Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
" } }, "OutputConfig": { "target": "com.amazonaws.sagemaker#OutputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Provides information about the output location for the compiled model and the target\n device the model runs on.
", + "smithy.api#documentation": "Provides information about the output location for the compiled model and the target device the model runs on.
", "smithy.api#required": {} } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#NeoVpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your compilation job\n to connect to. Control access to your models by configuring the VPC. For more\n information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
" } }, "StoppingCondition": { "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a limit to how long a model compilation job can run. When the job reaches\n the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training\n costs.
", + "smithy.api#documentation": "Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
", "smithy.api#required": {} } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -10733,7 +10705,7 @@ "target": "com.amazonaws.sagemaker#CompilationJobArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns\n the following data in JSON format:
\n\n CompilationJobArn: The Amazon Resource Name (ARN) of the compiled\n job.
If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns the following data in JSON format:
CompilationJobArn: The Amazon Resource Name (ARN) of the compiled job.
Create compute allocation definition. This defines how compute is allocated, shared, and\n borrowed for specified entities. Specifically, how to lend and borrow idle compute and\n assign a fair-share weight to the specified entities.
" + "smithy.api#documentation": "Create compute allocation definition. This defines how compute is allocated, shared, and borrowed for specified entities. Specifically, how to lend and borrow idle compute and assign a fair-share weight to the specified entities.
" } }, "com.amazonaws.sagemaker#CreateComputeQuotaRequest": { @@ -10791,7 +10763,7 @@ "target": "com.amazonaws.sagemaker#ComputeQuotaConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing\n option, and the setting to preempt low priority tasks.
", + "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
", "smithy.api#required": {} } }, @@ -10806,7 +10778,7 @@ "ActivationState": { "target": "com.amazonaws.sagemaker#ActivationState", "traits": { - "smithy.api#documentation": "The state of the compute allocation being described. Use to enable or disable compute\n allocation.
\nDefault is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
Creates a context. A context is a lineage tracking entity that\n represents a logical grouping of other tracking or experiment entities. Some examples are\n an endpoint and a model package. For more information, see\n Amazon SageMaker\n ML Lineage Tracking.
" + "smithy.api#documentation": "Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
" } }, "com.amazonaws.sagemaker#CreateContextRequest": { @@ -10942,7 +10914,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a definition for a job that monitors data quality and drift. For information\n about model monitor, see Amazon SageMaker AI Model\n Monitor.
" + "smithy.api#documentation": "Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.
" } }, "com.amazonaws.sagemaker#CreateDataQualityJobDefinitionRequest": { @@ -10974,7 +10946,7 @@ "target": "com.amazonaws.sagemaker#DataQualityJobInput", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of inputs for the monitoring job. Currently endpoints are supported as monitoring\n inputs.
", + "smithy.api#documentation": "A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.
", "smithy.api#required": {} } }, @@ -11002,7 +10974,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -11012,7 +10984,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -11096,7 +11068,7 @@ "EnableIotRoleAlias": { "target": "com.amazonaws.sagemaker#EnableIotRoleAlias", "traits": { - "smithy.api#documentation": "Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. \n The name of the role alias generated will match this pattern: \n \"SageMakerEdge-{DeviceFleetName}\".
\nFor example, if your device fleet is called \"demo-fleet\", the name of \n the role alias will be \"SageMakerEdge-demo-fleet\".
" + "smithy.api#documentation": "Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: \"SageMakerEdge-{DeviceFleetName}\".
For example, if your device fleet is called \"demo-fleet\", the name of the role alias will be \"SageMakerEdge-demo-fleet\".
" } } }, @@ -11121,7 +11093,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a Domain. A domain consists of an associated Amazon Elastic File System\n volume, a list of authorized users, and a variety of security, application, policy, and\n Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files\n and other artifacts with each other.
\n EFS storage\n
\nWhen a domain is created, an EFS volume is created for use by all of the users within the\n domain. Each user receives a private home directory within the EFS volume for notebooks, Git\n repositories, and data files.
\nSageMaker AI uses the Amazon Web Services Key Management Service (Amazon Web Services\n KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key\n by default. For more control, you can specify a customer managed key. For more information,\n see Protect Data\n at Rest Using Encryption.
\n\n VPC configuration\n
\nAll traffic between the domain and the Amazon EFS volume is through the specified\n VPC and subnets. For other traffic, you can specify the AppNetworkAccessType\n parameter. AppNetworkAccessType corresponds to the network access type that you\n choose when you onboard to the domain. The following options are available:
\n PublicInternetOnly - Non-EFS traffic goes through a VPC managed by\n Amazon SageMaker AI, which allows internet access. This is the default value.
\n VpcOnly - All traffic is through the specified VPC and subnets. Internet\n access is disabled by default. To allow internet access, you must specify a NAT\n gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker AI\n Studio notebook or to train or host models unless your VPC has an interface endpoint to\n the SageMaker AI API and runtime or a NAT gateway and your security groups allow\n outbound connections.
\nNFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules\n in order to launch a Amazon SageMaker AI Studio app successfully.
\nFor more information, see Connect Amazon SageMaker AI Studio Notebooks to Resources in a VPC.
" + "smithy.api#documentation": "Creates a Domain. A domain consists of an associated Amazon Elastic File System volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. Users within a domain can share notebook files and other artifacts with each other.
EFS storage
When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
SageMaker AI uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
VPC configuration
All traffic between the domain and the Amazon EFS volume is through the specified VPC and subnets. For other traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to the domain. The following options are available:
PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker AI, which allows internet access. This is the default value.
VpcOnly - All traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
When internet access is disabled, you won't be able to run a Amazon SageMaker AI Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker AI API and runtime or a NAT gateway and your security groups allow outbound connections.
NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a Amazon SageMaker AI Studio app successfully.
For more information, see Connect Amazon SageMaker AI Studio Notebooks to Resources in a VPC.
" } }, "com.amazonaws.sagemaker#CreateDomainRequest": { @@ -11147,7 +11119,7 @@ "target": "com.amazonaws.sagemaker#UserSettings", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The default settings to use to create a user profile when UserSettings isn't\n specified in the call to the CreateUserProfile API.
\n SecurityGroups is aggregated when specified in both calls. For all other\n settings in UserSettings, the values specified in CreateUserProfile\n take precedence over those specified in CreateDomain.
The default settings to use to create a user profile when UserSettings isn't specified in the call to the CreateUserProfile API.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag\n keys must be unique per resource. Tags are searchable using the Search\n API.
Tags that you specify for the Domain are also added to all Apps that the Domain\n launches.
" + "smithy.api#documentation": "Tags to associated with the Domain. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Tags that you specify for the Domain are also added to all Apps that the Domain launches.
" } }, "AppNetworkAccessType": { "target": "com.amazonaws.sagemaker#AppNetworkAccessType", "traits": { - "smithy.api#documentation": "Specifies the VPC used for non-EFS traffic. The default value is\n PublicInternetOnly.
\n PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
\n VpcOnly - All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
VpcOnly - All traffic is through the specified VPC and subnets
SageMaker AI uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to\n the domain with an Amazon Web Services managed key by default. For more control, specify a\n customer managed key.
" + "smithy.api#documentation": "SageMaker AI uses Amazon Web Services KMS to encrypt EFS and EBS volumes attached to the domain with an Amazon Web Services managed key by default. For more control, specify a customer managed key.
" } }, "AppSecurityGroupManagement": { "target": "com.amazonaws.sagemaker#AppSecurityGroupManagement", "traits": { - "smithy.api#documentation": "The entity that creates and manages the required security groups for inter-app\n communication in VPCOnly mode. Required when\n CreateDomain.AppNetworkAccessType is VPCOnly and\n DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is\n provided. If setting up the domain for use with RStudio, this value must be set to\n Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
Indicates whether custom tag propagation is supported for the domain. Defaults to\n DISABLED.
Indicates whether custom tag propagation is supported for the domain. Defaults to DISABLED.
Creates an edge deployment plan, consisting of multiple stages. Each stage may have a\n different deployment configuration and devices.
" + "smithy.api#documentation": "Creates an edge deployment plan, consisting of multiple stages. Each stage may have a different deployment configuration and devices.
" } }, "com.amazonaws.sagemaker#CreateEdgeDeploymentPlanRequest": { @@ -11296,7 +11268,7 @@ "Stages": { "target": "com.amazonaws.sagemaker#DeploymentStages", "traits": { - "smithy.api#documentation": "List of stages of the edge deployment plan. The number of stages is limited to 10 per\n deployment.
" + "smithy.api#documentation": "List of stages of the edge deployment plan. The number of stages is limited to 10 per deployment.
" } }, "Tags": { @@ -11466,7 +11438,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an endpoint using the endpoint configuration specified in the request. SageMaker\n uses the endpoint to provision resources and deploy models. You create the endpoint\n configuration with the CreateEndpointConfig API.
\nUse this API to deploy models using SageMaker hosting services.
\n You must not delete an EndpointConfig that is in use by an endpoint\n that is live or while the UpdateEndpoint or CreateEndpoint\n operations are being performed on the endpoint. To update an endpoint, you must\n create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your\n Amazon Web Services account.
\nWhen it receives the request, SageMaker creates the endpoint, launches the resources (ML\n compute instances), and deploys the model(s) on them.
\nWhen you call CreateEndpoint, a load call is made to DynamoDB to verify that your\n endpoint configuration exists. When you read data from a DynamoDB table supporting\n \n Eventually Consistent Reads\n , the response might not\n reflect the results of a recently completed write operation. The response might\n include some stale data. If the dependent entities are not yet in DynamoDB, this\n causes a validation error. If you repeat your read request after a short time, the\n response should return the latest data. So retry logic is recommended to handle\n these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB\n eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to\n Creating. After it creates the endpoint, it sets the status to\n InService. SageMaker can then process incoming requests for inferences. To\n check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location,\n SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the\n S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services\n account by default. If you previously deactivated Amazon Web Services STS for a region,\n you need to reactivate Amazon Web Services STS for that region. For more information, see\n Activating and\n Deactivating Amazon Web Services STS in an Amazon Web Services Region in the\n Amazon Web Services Identity and Access Management User\n Guide.
\nTo add the IAM role policies for using this API operation, go to the IAM console, and choose\n Roles in the left navigation pane. Search the IAM role that you want to grant\n access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the\n role.
\nOption 1: For a full SageMaker access, search and attach the\n AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the\n following Action elements manually into the JSON file of the IAM role:
\n\n \"Action\": [\"sagemaker:CreateEndpoint\",\n \"sagemaker:CreateEndpointConfig\"]\n
\n \"Resource\": [\n
\n \"arn:aws:sagemaker:region:account-id:endpoint/endpointName\"\n
\n \"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName\"\n
\n ]\n
For more information, see SageMaker API\n Permissions: Actions, Permissions, and Resources\n Reference.
\nCreates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
Use this API to deploy models using SageMaker hosting services.
You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
\"Action\": [\"sagemaker:CreateEndpoint\", \"sagemaker:CreateEndpointConfig\"]
\"Resource\": [
\"arn:aws:sagemaker:region:account-id:endpoint/endpointName\"
\"arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName\"
]
For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In\n the configuration, you identify one or more models, created using the\n CreateModel API, to deploy and the resources that you want SageMaker to\n provision. Then you call the CreateEndpoint\n API.
Use this API if you want to use SageMaker hosting services to deploy models into\n production.
\nIn the request, you define a ProductionVariant, for each model that you\n want to deploy. Each ProductionVariant parameter also describes the\n resources that you want SageMaker to provision. This includes the number and type of ML\n compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to\n specify how much traffic you want to allocate to each model. For example, suppose that\n you want to host two models, A and B, and you assign traffic weight 2 for model A and 1\n for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to\n model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your\n endpoint configuration exists. When you read data from a DynamoDB table supporting\n \n Eventually Consistent Reads\n , the response might not\n reflect the results of a recently completed write operation. The response might\n include some stale data. If the dependent entities are not yet in DynamoDB, this\n causes a validation error. If you repeat your read request after a short time, the\n response should return the latest data. So retry logic is recommended to handle\n these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB\n eventually consistent read.
Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
Use this API if you want to use SageMaker hosting services to deploy models into production.
In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
An array of ProductionVariant objects, one for each model that you want\n to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } }, "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that\n SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that\n hosts the endpoint.
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The KMS key policy must grant permission to the IAM role that you specify in your\n CreateEndpoint, UpdateEndpoint requests. For more\n information, refer to the Amazon Web Services Key Management Service section Using Key\n Policies in Amazon Web Services KMS \n
Certain Nitro-based instances include local storage, dependent on the instance\n type. Local storage volumes are encrypted using a hardware module on the instance.\n You can't request a KmsKeyId when using an instance type with local\n storage. If any of the models that you specify in the\n ProductionVariants parameter use nitro-based instances with local\n storage, do not specify a value for the KmsKeyId parameter. If you\n specify a value for KmsKeyId when using any nitro-based instances with\n local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
\nFor more information about local instance storage encryption, see SSD\n Instance Store Volumes.
\nThe Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
Specifies configuration for how an endpoint performs asynchronous inference. This is a\n required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
" + "smithy.api#documentation": "Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.
" } }, "ExplainerConfig": { @@ -11535,13 +11507,13 @@ "ShadowProductionVariants": { "target": "com.amazonaws.sagemaker#ProductionVariantList", "traits": { - "smithy.api#documentation": "An array of ProductionVariant objects, one for each model that you want\n to host at this endpoint in shadow mode with production traffic replicated from the\n model specified on ProductionVariants. If you use this field, you can only\n specify one variant for ProductionVariants and one variant for\n ShadowProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants. If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI\n Roles.
\nTo be able to pass this role to Amazon SageMaker AI, the caller of this action must\n have the iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.
To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.
Sets whether all model containers deployed to the endpoint are isolated. If they are, no\n inbound or outbound network calls can be made to or from the model containers.
" + "smithy.api#documentation": "Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
" } } }, @@ -11581,7 +11553,7 @@ "target": "com.amazonaws.sagemaker#EndpointName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the endpoint.The name must be unique within an Amazon Web Services\n Region in your Amazon Web Services account. The name is case-insensitive in\n CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
The name of the endpoint.The name must be unique within an Amazon Web Services Region in your Amazon Web Services account. The name is case-insensitive in CreateEndpoint, but the case is preserved and must be matched in InvokeEndpoint.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -11637,7 +11609,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a SageMaker experiment. An experiment is a collection of\n trials that are observed, compared and evaluated as a group. A trial is\n a set of steps, called trial components, that produce a machine learning\n model.
\nIn the Studio UI, trials are referred to as run groups and trial\n components are referred to as runs.
\nThe goal of an experiment is to determine the components that produce the best model.\n Multiple trials are performed, each one isolating and measuring the impact of a change to one\n or more inputs, while keeping the remaining inputs constant.
\nWhen you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial\n components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you\n must use the logging APIs provided by the SDK.
\nYou can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
\nTo add a description to an experiment, specify the optional Description\n parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To\n view an experiment's properties, call the DescribeExperiment API. To get a\n list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
" + "smithy.api#documentation": "Creates a SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
In the Studio UI, trials are referred to as run groups and trial components are referred to as runs.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
" } }, "com.amazonaws.sagemaker#CreateExperimentRequest": { @@ -11647,14 +11619,14 @@ "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the experiment. The name must be unique in your Amazon Web Services account and is not\n case-sensitive.
", + "smithy.api#documentation": "The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.
", "smithy.api#required": {} } }, "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the experiment as displayed. The name doesn't need to be unique. If you don't\n specify DisplayName, the value in ExperimentName is\n displayed.
The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify DisplayName, the value in ExperimentName is displayed.
A list of tags to associate with the experiment. You can use Search API\n to search on the tags.
" + "smithy.api#documentation": "A list of tags to associate with the experiment. You can use Search API to search on the tags.
" } } }, @@ -11705,7 +11677,7 @@ } ], "traits": { - "smithy.api#documentation": "Create a new FeatureGroup. A FeatureGroup is a group of\n Features defined in the FeatureStore to describe a\n Record.
The FeatureGroup defines the schema and features contained in the\n FeatureGroup. A FeatureGroup definition is composed of a list\n of Features, a RecordIdentifierFeatureName, an\n EventTimeFeatureName and configurations for its OnlineStore\n and OfflineStore. Check Amazon Web Services service\n quotas to see the FeatureGroups quota for your Amazon Web Services\n account.
Note that it can take approximately 10-15 minutes to provision an\n OnlineStore\n FeatureGroup with the InMemory\n StorageType.
You must include at least one of OnlineStoreConfig and\n OfflineStoreConfig to create a FeatureGroup.
Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
Note that it can take approximately 10-15 minutes to provision an OnlineStore FeatureGroup with the InMemory StorageType.
You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
The name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
The name:
\nMust start with an alphanumeric character.
\nCan only include alphanumeric characters, underscores, and hyphens. Spaces are not\n allowed.
\nThe name of the FeatureGroup. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
The name:
Must start with an alphanumeric character.
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
The name of the Feature whose value uniquely identifies a\n Record defined in the FeatureStore. Only the latest record per\n identifier value will be stored in the OnlineStore.\n RecordIdentifierFeatureName must be one of feature definitions'\n names.
You use the RecordIdentifierFeatureName to access data in a\n FeatureStore.
This name:
\nMust start with an alphanumeric character.
\nCan only contains alphanumeric characters, hyphens, underscores. Spaces are not\n allowed.
\nThe name of the Feature whose value uniquely identifies a Record defined in the FeatureStore. Only the latest record per identifier value will be stored in the OnlineStore. RecordIdentifierFeatureName must be one of feature definitions' names.
You use the RecordIdentifierFeatureName to access data in a FeatureStore.
This name:
Must start with an alphanumeric character.
Can only contains alphanumeric characters, hyphens, underscores. Spaces are not allowed.
The name of the feature that stores the EventTime of a Record\n in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to\n the creation or update of a Record in a FeatureGroup. All\n Records in the FeatureGroup must have a corresponding\n EventTime.
An EventTime can be a String or Fractional.
\n Fractional: EventTime feature values must be a Unix\n timestamp in seconds.
\n String: EventTime feature values must be an ISO-8601\n string in the format. The following formats are supported\n yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ\n where yyyy, MM, and dd represent the year,\n month, and day respectively and HH, mm, ss,\n and if applicable, SSS represent the hour, month, second and\n milliseconds respsectively. 'T' and Z are constants.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
An EventTime can be a String or Fractional.
Fractional: EventTime feature values must be a Unix timestamp in seconds.
String: EventTime feature values must be an ISO-8601 string in the format. The following formats are supported yyyy-MM-dd'T'HH:mm:ssZ and yyyy-MM-dd'T'HH:mm:ss.SSSZ where yyyy, MM, and dd represent the year, month, and day respectively and HH, mm, ss, and if applicable, SSS represent the hour, month, second and milliseconds respsectively. 'T' and Z are constants.
A list of Feature names and types. Name and Type\n is compulsory per Feature.
Valid feature FeatureTypes are Integral,\n Fractional and String.
\n FeatureNames cannot be any of the following: is_deleted,\n write_time, api_invocation_time\n
You can create up to 2,500 FeatureDefinitions per\n FeatureGroup.
A list of Feature names and types. Name and Type is compulsory per Feature.
Valid feature FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
You can turn the OnlineStore on or off by specifying True for\n the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for\n at-rest encryption of the OnlineStore.
The default value is False.
You can turn the OnlineStore on or off by specifying True for the EnableOnlineStore flag in OnlineStoreConfig.
You can also include an Amazon Web Services KMS key ID (KMSKeyId) for at-rest encryption of the OnlineStore.
The default value is False.
Use this to configure an OfflineFeatureStore. This parameter allows you to\n specify:
The Amazon Simple Storage Service (Amazon S3) location of an\n OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data\n catalog.
\nAn KMS encryption key to encrypt the Amazon S3 location used for\n OfflineStore. If KMS encryption key is not specified, by default we\n encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level\n key for SSE, you can reduce Amazon Web Services KMS requests costs by up to\n 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and\n Apache Iceberg.
\nTo learn more about this parameter, see OfflineStoreConfig.
" + "smithy.api#documentation": "Use this to configure an OfflineFeatureStore. This parameter allows you to specify:
The Amazon Simple Storage Service (Amazon S3) location of an OfflineStore.
A configuration for an Amazon Web Services Glue or Amazon Web Services Hive data catalog.
An KMS encryption key to encrypt the Amazon S3 location used for OfflineStore. If KMS encryption key is not specified, by default we encrypt all data at rest using Amazon Web Services KMS key. By defining your bucket-level key for SSE, you can reduce Amazon Web Services KMS requests costs by up to 99 percent.
Format for the offline store table. Supported formats are Glue (Default) and Apache Iceberg.
To learn more about this parameter, see OfflineStoreConfig.
" } }, "ThroughputConfig": { @@ -11761,7 +11733,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the\n OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique\n identifier for the feature group.
The Amazon Resource Name (ARN) of the FeatureGroup. This is a unique identifier for the feature group.
Container for configuring the source of human task requests. Use to specify if\n Amazon Rekognition or Amazon Textract is used as an integration source.
" + "smithy.api#documentation": "Container for configuring the source of human task requests. Use to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
" } }, "HumanLoopActivationConfig": { @@ -12144,7 +12116,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version\n of a model by running many training jobs on your dataset using the algorithm you choose\n and values for hyperparameters within ranges that you specify. It then chooses the\n hyperparameter values that result in a model that performs the best, as measured by an\n objective metric that you choose.
\nA hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and\n trial components for each training job that it runs. You can view these entities in\n Amazon SageMaker Studio. For more information, see View\n Experiments, Trials, and Trial Components.
\nDo not include any security-sensitive information including account access IDs, secrets, \n or tokens in any hyperparameter fields. As part of the shared responsibility model, \n you are responsible for any potential exposure, unauthorized access, or \n compromise of your sensitive data if caused by any security-sensitive information included \n in the request hyperparameter variable or plain text fields..
\nStarts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
A hyperparameter tuning job automatically creates Amazon SageMaker experiments, trials, and trial components for each training job that it runs. You can view these entities in Amazon SageMaker Studio. For more information, see View Experiments, Trials, and Trial Components.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request hyperparameter variable or plain text fields..
The name of the tuning job. This name is the prefix for the names of all training jobs\n that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid\n characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case\n sensitive.
", + "smithy.api#documentation": "The name of the tuning job. This name is the prefix for the names of all training jobs that this tuning job launches. The name must be unique within the same Amazon Web Services account and Amazon Web Services Region. The name must have 1 to 32 characters. Valid characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case sensitive.
", "smithy.api#required": {} } }, @@ -12162,38 +12134,38 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The HyperParameterTuningJobConfig object that describes the tuning job,\n including the search strategy, the objective metric used to evaluate training jobs,\n ranges of parameters to search, and resource limits for the tuning job. For more\n information, see How\n Hyperparameter Tuning Works.
", + "smithy.api#documentation": "The HyperParameterTuningJobConfig object that describes the tuning job, including the search strategy, the objective metric used to evaluate training jobs, ranges of parameters to search, and resource limits for the tuning job. For more information, see How Hyperparameter Tuning Works.
", "smithy.api#required": {} } }, "TrainingJobDefinition": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobDefinition", "traits": { - "smithy.api#documentation": "The HyperParameterTrainingJobDefinition object that describes the training jobs\n that this tuning job launches, including static hyperparameters, input data\n configuration, output data configuration, resource configuration, and stopping\n condition.
" + "smithy.api#documentation": "The HyperParameterTrainingJobDefinition object that describes the training jobs that this tuning job launches, including static hyperparameters, input data configuration, output data configuration, resource configuration, and stopping condition.
" } }, "TrainingJobDefinitions": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobDefinitions", "traits": { - "smithy.api#documentation": "A list of the HyperParameterTrainingJobDefinition objects launched for this tuning\n job.
" + "smithy.api#documentation": "A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
" } }, "WarmStartConfig": { "target": "com.amazonaws.sagemaker#HyperParameterTuningJobWarmStartConfig", "traits": { - "smithy.api#documentation": "Specifies the configuration for starting the hyperparameter tuning job using one or\n more previous tuning jobs as a starting point. The results of previous tuning jobs are\n used to inform which combinations of hyperparameters to search over in the new tuning\n job.
\nAll training jobs launched by the new hyperparameter tuning job are evaluated by using\n the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the\n WarmStartType value for the warm start configuration, the training job\n that performs the best in the new tuning job is compared to the best training jobs from\n the parent tuning jobs. From these, the training job that performs the best as measured\n by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new\n hyperparameter tuning jobs count against the limit of training jobs for the tuning\n job.
\nSpecifies the configuration for starting the hyperparameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric. If you specify IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start configuration, the training job that performs the best in the new tuning job is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
\nTags that you specify for the tuning job are also added to all training jobs that the\n tuning job launches.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Tags that you specify for the tuning job are also added to all training jobs that the tuning job launches.
" } }, "Autotune": { "target": "com.amazonaws.sagemaker#Autotune", "traits": { - "smithy.api#documentation": "Configures SageMaker Automatic model tuning (AMT) to automatically find optimal\n parameters for the following fields:
\n\n ParameterRanges: The names and ranges of parameters that a\n hyperparameter tuning job can optimize.
\n\n ResourceLimits: The maximum resources that can be used for a\n training job. These resources include the maximum number of training jobs, the\n maximum runtime of a tuning job, and the maximum number of training jobs to run\n at the same time.
\n\n TrainingJobEarlyStoppingType: A flag that specifies whether or not\n to use early stopping for training jobs launched by a hyperparameter tuning\n job.
\n\n RetryStrategy: The number of times to retry a training job.
\n\n Strategy: Specifies how hyperparameter tuning chooses the\n combinations of hyperparameter values to use for the training jobs that it\n launches.
\n\n ConvergenceDetected: A flag to indicate that Automatic model tuning\n (AMT) has detected model convergence.
\nConfigures SageMaker Automatic model tuning (AMT) to automatically find optimal parameters for the following fields:
ParameterRanges: The names and ranges of parameters that a hyperparameter tuning job can optimize.
ResourceLimits: The maximum resources that can be used for a training job. These resources include the maximum number of training jobs, the maximum runtime of a tuning job, and the maximum number of training jobs to run at the same time.
TrainingJobEarlyStoppingType: A flag that specifies whether or not to use early stopping for training jobs launched by a hyperparameter tuning job.
RetryStrategy: The number of times to retry a training job.
Strategy: Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training jobs that it launches.
ConvergenceDetected: A flag to indicate that Automatic model tuning (AMT) has detected model convergence.
The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a\n hyperparameter tuning job when you create it.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns an ARN to a hyperparameter tuning job when you create it.
", "smithy.api#required": {} } } @@ -12234,7 +12206,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image\n version represents a container image stored in Amazon ECR. For more information, see\n Bring your own SageMaker AI image.
" + "smithy.api#documentation": "Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker AI image.
" } }, "com.amazonaws.sagemaker#CreateImageRequest": { @@ -12313,7 +12285,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a version of the SageMaker AI image specified by ImageName. The version\n represents the Amazon ECR container image specified by BaseImage.
Creates a version of the SageMaker AI image specified by ImageName. The version represents the Amazon ECR container image specified by BaseImage.
The registry path of the container image to use as the starting point for this\n version. The path is an Amazon ECR URI in the following format:
\n\n
The registry path of the container image to use as the starting point for this version. The path is an Amazon ECR URI in the following format:
<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or [@digest]>
A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python\n (Boto3), add a unique value to the call.
", + "smithy.api#documentation": "A unique ID. If not specified, the Amazon Web Services CLI and Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a unique value to the call.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -12353,13 +12325,13 @@ "VendorGuidance": { "target": "com.amazonaws.sagemaker#VendorGuidance", "traits": { - "smithy.api#documentation": "The stability of the image version, specified by the maintainer.
\n\n NOT_PROVIDED: The maintainers did not provide a status for image version stability.
\n STABLE: The image version is stable.
\n TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
\n ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version, specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
\n\n TRAINING: The image version is compatible with SageMaker AI training jobs.
\n INFERENCE: The image version is compatible with SageMaker AI inference jobs.
\n NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
\n\n CPU: The image version is compatible with CPU.
\n GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Creates an inference component, which is a SageMaker AI hosting object that you can\n use to deploy a model to an endpoint. In the inference component settings, you specify the\n model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You\n can optimize resource utilization by tailoring how the required CPU cores, accelerators,\n and memory are allocated. You can deploy multiple inference components to an endpoint,\n where each inference component contains one model and the resource utilization needs for\n that individual model. After you deploy an inference component, you can directly invoke the\n associated model when you use the InvokeEndpoint API action.
" + "smithy.api#documentation": "Creates an inference component, which is a SageMaker AI hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.
" } }, "com.amazonaws.sagemaker#CreateInferenceComponentInput": { @@ -12450,14 +12422,14 @@ "VariantName": { "target": "com.amazonaws.sagemaker#VariantName", "traits": { - "smithy.api#documentation": "The name of an existing production variant where you host the inference\n component.
" + "smithy.api#documentation": "The name of an existing production variant where you host the inference component.
" } }, "Specification": { "target": "com.amazonaws.sagemaker#InferenceComponentSpecification", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Details about the resources to deploy with this inference component, including the\n model, container, and compute resources.
", + "smithy.api#documentation": "Details about the resources to deploy with this inference component, including the model, container, and compute resources.
", "smithy.api#required": {} } }, @@ -12470,7 +12442,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services\n resources in the Amazon Web Services General\n Reference.
" + "smithy.api#documentation": "A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference.
" } } }, @@ -12511,7 +12483,7 @@ } ], "traits": { - "smithy.api#documentation": "\n Creates an inference experiment using the configurations specified in the request.\n
\n\n Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For\n more information about inference experiments, see Shadow tests.\n
\n\n Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based\n on your specified configuration.\n
\n\n While the experiment is in progress or after it has concluded, you can view metrics that compare your model\n variants. For more information, see View, monitor, and edit shadow tests.\n
" + "smithy.api#documentation": "Creates an inference experiment using the configurations specified in the request.
Use this API to setup and schedule an experiment to compare model variants on a Amazon SageMaker inference endpoint. For more information about inference experiments, see Shadow tests.
Amazon SageMaker begins your experiment at the scheduled time and routes traffic to your endpoint's model variants based on your specified configuration.
While the experiment is in progress or after it has concluded, you can view metrics that compare your model variants. For more information, see View, monitor, and edit shadow tests.
" } }, "com.amazonaws.sagemaker#CreateInferenceExperimentRequest": { @@ -12529,14 +12501,14 @@ "target": "com.amazonaws.sagemaker#InferenceExperimentType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The type of the inference experiment that you want to run. The following types of experiments are possible:\n
\n\n ShadowMode: You can use this type to validate a shadow variant. For more information,\n see Shadow tests.\n
The type of the inference experiment that you want to run. The following types of experiments are possible:
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
\n The duration for which you want the inference experiment to run. If you don't specify this field, the\n experiment automatically starts immediately upon creation and concludes after 7 days.\n
" + "smithy.api#documentation": "The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
" } }, "Description": { @@ -12549,7 +12521,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage\n Amazon SageMaker Inference endpoints for model deployment.\n
", + "smithy.api#documentation": "The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
", "smithy.api#required": {} } }, @@ -12557,7 +12529,7 @@ "target": "com.amazonaws.sagemaker#EndpointName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.\n
", + "smithy.api#documentation": "The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
", "smithy.api#required": {} } }, @@ -12565,34 +12537,34 @@ "target": "com.amazonaws.sagemaker#ModelVariantConfigList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n An array of ModelVariantConfig objects. There is one for each variant in the inference\n experiment. Each ModelVariantConfig object in the array describes the infrastructure\n configuration for the corresponding variant.\n
An array of ModelVariantConfig objects. There is one for each variant in the inference experiment. Each ModelVariantConfig object in the array describes the infrastructure configuration for the corresponding variant.
\n The Amazon S3 location and configuration for storing inference request and response data.\n
\n\n This is an optional parameter that you can use for data capture. For more information, see Capture data.\n
" + "smithy.api#documentation": "The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
" } }, "ShadowModeConfig": { "target": "com.amazonaws.sagemaker#ShadowModeConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The configuration of ShadowMode inference experiment type. Use this field to specify a\n production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a\n percentage of the inference requests. For the shadow variant also specify the percentage of requests that\n Amazon SageMaker replicates.\n
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
\n The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on\n the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can\n be any of the following formats:\n
KMS key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
Amazon Resource Name (ARN) of a KMS key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
KMS key Alias
\n\n \"alias/ExampleAlias\"\n
Amazon Resource Name (ARN) of a KMS key Alias
\n\n \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"\n
\n If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to\n call kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for\n your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for\n OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that\n only allows objects with server-side encryption, set the condition key of\n s3:x-amz-server-side-encryption to \"aws:kms\". For more information, see KMS managed Encryption Keys\n in the Amazon Simple Storage Service Developer Guide.\n
\n The KMS key policy must grant permission to the IAM role that you specify in your\n CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer\n Guide.\n
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The KmsKey can be any of the following formats:
KMS key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
Amazon Resource Name (ARN) of a KMS key
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
KMS key Alias
\"alias/ExampleAlias\"
Amazon Resource Name (ARN) of a KMS key Alias
\"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to \"aws:kms\". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
\n Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different\n ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.\n
" + "smithy.api#documentation": "Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
" } } }, @@ -12633,7 +12605,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a recommendation job. You can create either an instance \n recommendation or load test job.
" + "smithy.api#documentation": "Starts a recommendation job. You can create either an instance recommendation or load test job.
" } }, "com.amazonaws.sagemaker#CreateInferenceRecommendationsJobRequest": { @@ -12643,7 +12615,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A name for the recommendation job. The name must be unique within \n the Amazon Web Services Region and within your Amazon Web Services account.\n The job name is passed down to the resources created by the recommendation job.\n The names of resources (such as the model, endpoint configuration, endpoint, and compilation)\n that are prefixed with the job name are truncated at 40 characters.
", + "smithy.api#documentation": "A name for the recommendation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account. The job name is passed down to the resources created by the recommendation job. The names of resources (such as the model, endpoint configuration, endpoint, and compilation) that are prefixed with the job name are truncated at 40 characters.
", "smithy.api#required": {} } }, @@ -12651,7 +12623,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Defines the type of recommendation job. Specify Default to initiate an instance \n recommendation and Advanced to initiate a load test. If left unspecified, \n Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
Defines the type of recommendation job. Specify Default to initiate an instance recommendation and Advanced to initiate a load test. If left unspecified, Amazon SageMaker Inference Recommender will run an instance recommendation (DEFAULT) job.
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker \n to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -12667,7 +12639,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobInputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Provides information about the versioned model package Amazon Resource Name (ARN), \n the traffic pattern, and endpoint configurations.
", + "smithy.api#documentation": "Provides information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations.
", "smithy.api#required": {} } }, @@ -12680,19 +12652,19 @@ "StoppingConditions": { "target": "com.amazonaws.sagemaker#RecommendationJobStoppingConditions", "traits": { - "smithy.api#documentation": "A set of conditions for stopping a recommendation job. If any of \n the conditions are met, the job is automatically stopped.
" + "smithy.api#documentation": "A set of conditions for stopping a recommendation job. If any of the conditions are met, the job is automatically stopped.
" } }, "OutputConfig": { "target": "com.amazonaws.sagemaker#RecommendationJobOutputConfig", "traits": { - "smithy.api#documentation": "Provides information about the output artifacts and the KMS key \n to use for Amazon S3 server-side encryption.
" + "smithy.api#documentation": "Provides information about the output artifacts and the KMS key to use for Amazon S3 server-side encryption.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "The metadata that you apply to Amazon Web Services resources to help you \n categorize and organize them. Each tag consists of a key and a value, both of \n which you define. For more information, see \n Tagging Amazon Web Services Resources \n in the Amazon Web Services General Reference.
" + "smithy.api#documentation": "The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.
" } } }, @@ -12733,7 +12705,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a job that uses workers to label the data objects in your input dataset. You\n can use the labeled data to train machine learning models.
\nYou can select your workforce from one of three providers:
\nA private workforce that you create. It can include employees, contractors,\n and outside experts. Use a private workforce when want the data to stay within\n your organization or when a specific set of skills is required.
\nOne or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide\n expertise in specific areas.
\nThe Amazon Mechanical Turk workforce. This is the largest workforce, but it\n should only be used for public data or data that has been stripped of any\n personally identifiable information.
\nYou can also use automated data labeling to reduce the number of\n data objects that need to be labeled by a human. Automated data labeling uses\n active learning to determine if a data object can be labeled by\n machine or if it needs to be sent to a human worker. For more information, see Using\n Automated Data Labeling.
\nThe data objects to be labeled are contained in an Amazon S3 bucket. You create a\n manifest file that describes the location of each object. For\n more information, see Using Input and Output Data.
\nThe output can be used as the manifest file for another labeling job or as training\n data for your machine learning models.
\nYou can use this operation to create a static labeling job or a streaming labeling\n job. A static labeling job stops if all data objects in the input manifest file\n identified in ManifestS3Uri have been labeled. A streaming labeling job\n runs perpetually until it is manually stopped, or remains idle for 10 days. You can send\n new data objects to an active (InProgress) streaming labeling job in real\n time. To learn how to create a static labeling job, see Create a Labeling Job\n (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming\n labeling job, see Create a Streaming Labeling\n Job.
Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
You can select your workforce from one of three providers:
A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
The name of the labeling job. This name is used to identify the job in a list of\n labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region.\n LabelingJobName is not case sensitive. For example, Example-job and\n example-job are considered the same labeling job name by Ground Truth.
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
The attribute name to use for the label in the output manifest file. This is the key\n for the key/value pair formed with the label that a worker assigns to the object. The\n LabelAttributeName must meet the following requirements.
The name can't end with \"-metadata\".
\nIf you are using one of the following built-in task types,\n the attribute name must end with \"-ref\". If the task type\n you are using is not listed below, the attribute name must\n not end with \"-ref\".
\nImage semantic segmentation (SemanticSegmentation), and\n adjustment (AdjustmentSemanticSegmentation) and\n verification (VerificationSemanticSegmentation) labeling\n jobs for this task type.
Video frame object detection (VideoObjectDetection), and\n adjustment and verification\n (AdjustmentVideoObjectDetection) labeling jobs for this\n task type.
Video frame object tracking (VideoObjectTracking), and\n adjustment and verification (AdjustmentVideoObjectTracking)\n labeling jobs for this task type.
3D point cloud semantic segmentation\n (3DPointCloudSemanticSegmentation), and adjustment and\n verification (Adjustment3DPointCloudSemanticSegmentation)\n labeling jobs for this task type.
3D point cloud object tracking\n (3DPointCloudObjectTracking), and adjustment and\n verification (Adjustment3DPointCloudObjectTracking)\n labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a\n different\n LabelAttributeName than the one used in the original labeling job. The\n original labeling job is the Ground Truth labeling job that produced the labels that you\n want verified or adjusted. To learn more about adjustment and verification labeling\n jobs, see Verify and Adjust\n Labels.
The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
The name can't end with \"-metadata\".
If you are using one of the following built-in task types, the attribute name must end with \"-ref\". If the task type you are using is not listed below, the attribute name must not end with \"-ref\".
Image semantic segmentation (SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.
Video frame object detection (VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.
Video frame object tracking (VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.
3D point cloud semantic segmentation (3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.
3D point cloud object tracking (3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels.
Input data for the labeling job, such as the Amazon S3 location of the data objects and the\n location of the manifest file that describes the data objects.
\nYou must specify at least one of the following: S3DataSource or\n SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming\n labeling job. If you do not specify and SNS input topic ARN, Ground Truth will\n create a one-time labeling job that stops after all data objects in the input\n manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both\n streaming and one-time labeling jobs. Adding an S3DataSource is\n optional if you use SnsDataSource to create a streaming labeling\n job.
If you use the Amazon Mechanical Turk workforce, your input data should not include\n confidential information, personal information or protected health information. Use\n ContentClassifiers to specify that your data is free of personally\n identifiable information and adult content.
Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.
The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt\n the output data, if any.
", + "smithy.api#documentation": "The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
", "smithy.api#required": {} } }, @@ -12775,20 +12747,20 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf\n during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker\n can successfully complete data labeling.
", + "smithy.api#documentation": "The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
", "smithy.api#required": {} } }, "LabelCategoryConfigS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The S3 URI of the file, referred to as a label category configuration\n file, that defines the categories used to label the data objects.
\nFor 3D point cloud and video frame task types, you can add label category attributes\n and frame attributes to your label category configuration file. To learn how, see Create a\n Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
\nFor named entity recognition jobs, in addition to Add Instructions Add additional instructions.\"labels\", you must\n provide worker instructions in the label category configuration file using the\n \"instructions\" parameter: \"instructions\":\n {\"shortInstruction\":\". For details\n and an example, see Create a\n Named Entity Recognition Labeling Job (API) .Add header
For all other built-in task types and custom\n tasks, your label category configuration file must be a JSON file in the\n following format. Identify the labels you want to use by replacing label_1,\n label_2,...,label_n with your label\n categories.
\n { \n
\n \"document-version\": \"2018-11-28\",\n
\n \"labels\": [{\"label\": \"label_1\"},{\"label\": \"label_2\"},...{\"label\":\n \"label_n\"}]\n
\n }\n
Note the following about the label category configuration file:
\nFor image classification and text classification (single and multi-label) you\n must specify at least two label categories. For all other task types, the\n minimum number of label categories required is one.
\nEach label category must be unique, you cannot specify duplicate label\n categories.
\nIf you create a 3D point cloud or video frame adjustment or verification\n labeling job, you must include auditLabelAttributeName in the label\n category configuration. Use this parameter to enter the \n LabelAttributeName\n of the labeling job you want to\n adjust or verify annotations of.
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs.
For named entity recognition jobs, in addition to \"labels\", you must provide worker instructions in the label category configuration file using the \"instructions\" parameter: \"instructions\": {\"shortInstruction\":\"<h1>Add header</h1><p>Add Instructions</p>\", \"fullInstruction\":\"<p>Add additional instructions.</p>\"}. For details and an example, see Create a Named Entity Recognition Labeling Job (API) .
For all other built-in task types and custom tasks, your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.
{
\"document-version\": \"2018-11-28\",
\"labels\": [{\"label\": \"label_1\"},{\"label\": \"label_2\"},...{\"label\": \"label_n\"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include auditLabelAttributeName in the label category configuration. Use this parameter to enter the LabelAttributeName of the labeling job you want to adjust or verify annotations of.
A set of conditions for stopping the labeling job. If any of the conditions are met,\n the job is automatically stopped. You can use these conditions to control the cost of\n data labeling.
" + "smithy.api#documentation": "A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
" } }, "LabelingJobAlgorithmsConfig": { @@ -12808,7 +12780,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management\n User Guide.
" + "smithy.api#documentation": "An array of key/value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -12823,7 +12795,7 @@ "target": "com.amazonaws.sagemaker#LabelingJobArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the\n labeling job.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify the labeling job.
", "smithy.api#required": {} } } @@ -12846,7 +12818,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact\n store. For more information, see Create an MLflow Tracking\n Server.
" + "smithy.api#documentation": "Creates an MLflow Tracking Server using a general purpose Amazon S3 bucket as the artifact store. For more information, see Create an MLflow Tracking Server.
" } }, "com.amazonaws.sagemaker#CreateMlflowTrackingServerRequest": { @@ -12856,7 +12828,7 @@ "target": "com.amazonaws.sagemaker#TrackingServerName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A unique string identifying the tracking server name. This string is part of the tracking server\n ARN.
", + "smithy.api#documentation": "A unique string identifying the tracking server name. This string is part of the tracking server ARN.
", "smithy.api#required": {} } }, @@ -12864,34 +12836,34 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact\n store.
", + "smithy.api#documentation": "The S3 URI for a general purpose bucket to use as the MLflow Tracking Server artifact store.
", "smithy.api#required": {} } }, "TrackingServerSize": { "target": "com.amazonaws.sagemaker#TrackingServerSize", "traits": { - "smithy.api#documentation": "The size of the tracking server you want to create. You can choose between\n \"Small\", \"Medium\", and \"Large\". The default MLflow\n Tracking Server configuration size is \"Small\". You can choose a size depending on\n the projected use of the tracking server such as the volume of data logged, number of users,\n and frequency of use.
We recommend using a small tracking server for teams of up to 25 users, a medium tracking\n server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
" + "smithy.api#documentation": "The size of the tracking server you want to create. You can choose between \"Small\", \"Medium\", and \"Large\". The default MLflow Tracking Server configuration size is \"Small\". You can choose a size depending on the projected use of the tracking server such as the volume of data logged, number of users, and frequency of use.
We recommend using a small tracking server for teams of up to 25 users, a medium tracking server for teams of up to 50 users, and a large tracking server for teams of up to 100 users.
" } }, "MlflowVersion": { "target": "com.amazonaws.sagemaker#MlflowVersion", "traits": { - "smithy.api#documentation": "The version of MLflow that the tracking server uses. To see which MLflow versions are\n available to use, see How it works.
" + "smithy.api#documentation": "The version of MLflow that the tracking server uses. To see which MLflow versions are available to use, see How it works.
" } }, "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to\n access the artifact store in Amazon S3. The role should have AmazonS3FullAccess\n permissions. For more information on IAM permissions for tracking server creation, see\n Set up IAM permissions for MLflow.
The Amazon Resource Name (ARN) for an IAM role in your account that the MLflow Tracking Server uses to access the artifact store in Amazon S3. The role should have AmazonS3FullAccess permissions. For more information on IAM permissions for tracking server creation, see Set up IAM permissions for MLflow.
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. \n To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False.
Creates a model in SageMaker. In the request, you name the model and describe a primary\n container. For the primary container, you specify the Docker image that\n contains inference code, artifacts (from prior training), and a custom environment map\n that the inference code uses when you deploy the model for predictions.
\nUse this API to create a model if you want to use SageMaker hosting services or run a batch\n transform job.
\nTo host your model, you create an endpoint configuration with the\n CreateEndpointConfig API, and then create an endpoint with the\n CreateEndpoint API. SageMaker then deploys all of the containers that you\n defined for the model in the hosting environment.
To run a batch transform using your model, you start a job with the\n CreateTransformJob API. SageMaker uses your model and your dataset to get\n inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model\n artifacts and docker image for deployment on ML compute hosting instances or for batch\n transform jobs. In addition, you also use the IAM role to manage permissions the\n inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
" + "smithy.api#documentation": "Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
" } }, "com.amazonaws.sagemaker#CreateModelBiasJobDefinition": { @@ -12969,7 +12941,7 @@ "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services \n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -13019,7 +12991,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -13029,7 +13001,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -13070,7 +13042,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an Amazon SageMaker Model Card.
\nFor information about how to use model cards, see Amazon SageMaker Model Card.
" + "smithy.api#documentation": "Creates an Amazon SageMaker Model Card.
For information about how to use model cards, see Amazon SageMaker Model Card.
" } }, "com.amazonaws.sagemaker#CreateModelCardExportJob": { @@ -13164,7 +13136,7 @@ "SecurityConfig": { "target": "com.amazonaws.sagemaker#ModelCardSecurityConfig", "traits": { - "smithy.api#documentation": "An optional Key Management Service \n key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with\n highly sensitive data.
" + "smithy.api#documentation": "An optional Key Management Service key to encrypt, decrypt, and re-encrypt model card content for regulated workloads with highly sensitive data.
" } }, "Content": { @@ -13179,7 +13151,7 @@ "target": "com.amazonaws.sagemaker#ModelCardStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The name of the model explainability job definition. The name must be unique within an\n Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -13287,7 +13259,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -13297,7 +13269,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -13335,7 +13307,7 @@ "PrimaryContainer": { "target": "com.amazonaws.sagemaker#ContainerDefinition", "traits": { - "smithy.api#documentation": "The location of the primary docker image containing inference code, associated\n artifacts, and custom environment map that the inference code uses when the model is\n deployed for predictions.
" + "smithy.api#documentation": "The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
" } }, "Containers": { @@ -13353,25 +13325,25 @@ "ExecutionRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model\n artifacts and docker image for deployment on ML compute instances or for batch transform\n jobs. Deploying on ML compute instances is part of model hosting. For more information,\n see SageMaker\n Roles.
\nTo be able to pass this role to SageMaker, the caller of this API must have the\n iam:PassRole permission.
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your model to connect\n to. Control access to and from your model container by configuring the VPC.\n VpcConfig is used in hosting services and in batch transform. For more\n information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch\n Transform Jobs by Using an Amazon Virtual Private Cloud.
A VpcConfig object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. VpcConfig is used in hosting services and in batch transform. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud.
Isolates the model container. No inbound or outbound network calls can be made to or\n from the model container.
" + "smithy.api#documentation": "Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
" } } }, @@ -13412,7 +13384,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers\n can subscribe to model packages listed on Amazon Web Services Marketplace to create\n models in SageMaker.
\nTo create a model package by specifying a Docker container that contains your\n inference code and the Amazon S3 location of your model artifacts, provide values for\n InferenceSpecification. To create a model from an algorithm resource\n that you created or subscribed to in Amazon Web Services Marketplace, provide a value for\n SourceAlgorithmSpecification.
There are two types of model packages:
\nVersioned - a model that is part of a model group in the model\n registry.
\nUnversioned - a model package that is not part of a model group.
\nCreates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
There are two types of model packages:
Versioned - a model that is part of a model group in the model registry.
Unversioned - a model package that is not part of a model group.
A list of key value pairs associated with the model group. For more information, see\n Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
" + "smithy.api#documentation": "A list of key value pairs associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } } }, @@ -13482,13 +13454,13 @@ "ModelPackageName": { "target": "com.amazonaws.sagemaker#EntityName", "traits": { - "smithy.api#documentation": "The name of the model package. The name must have 1 to 63 characters. Valid characters\n are a-z, A-Z, 0-9, and - (hyphen).
\nThis parameter is required for unversioned models. It is not applicable to versioned\n models.
" + "smithy.api#documentation": "The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
" } }, "ModelPackageGroupName": { "target": "com.amazonaws.sagemaker#ArnOrName", "traits": { - "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package group that this model version belongs\n to.
\nThis parameter is required for versioned models, and does not apply to unversioned\n models.
" + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
" } }, "ModelPackageDescription": { @@ -13500,13 +13472,13 @@ "InferenceSpecification": { "target": "com.amazonaws.sagemaker#InferenceSpecification", "traits": { - "smithy.api#documentation": "Specifies details about inference jobs that you can run with models based on this\n model package, including the following information:
\nThe Amazon ECR paths of containers that contain the inference code and model\n artifacts.
\nThe instance types that the model package supports for transform jobs and\n real-time endpoints used for inference.
\nThe input and output content formats that the model package supports for\n inference.
\nSpecifies details about inference jobs that you can run with models based on this model package, including the following information:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
Specifies configurations for one or more transform jobs that SageMaker runs to test the\n model package.
" + "smithy.api#documentation": "Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
" } }, "SourceAlgorithmSpecification": { @@ -13518,19 +13490,19 @@ "CertifyForMarketplace": { "target": "com.amazonaws.sagemaker#CertifyForMarketplace", "traits": { - "smithy.api#documentation": "Whether to certify the model package for listing on Amazon Web Services\n Marketplace.
\nThis parameter is optional for unversioned models, and does not apply to versioned\n models.
" + "smithy.api#documentation": "Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
\nIf you supply ModelPackageGroupName, your model package belongs to the\n model group you specify and uses the tags associated with the model group. In this case,\n you cannot supply a tag argument.
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply ModelPackageGroupName, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag argument.
Whether the model is approved for deployment.
\nThis parameter is optional for versioned models, and does not apply to unversioned\n models.
\nFor versioned models, the value of this parameter must be set to Approved\n to deploy the model.
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to Approved to deploy the model.
The machine learning domain of your model package and its components. Common machine\n learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine learning\n tasks include object detection and image classification. The following tasks are\n supported by Inference Recommender: \"IMAGE_CLASSIFICATION\" |\n \"OBJECT_DETECTION\" | \"TEXT_GENERATION\"\n |\"IMAGE_SEGMENTATION\" | \"FILL_MASK\" |\n \"CLASSIFICATION\" | \"REGRESSION\" |\n \"OTHER\".
Specify \"OTHER\" if none of the tasks listed fit your use case.
" + "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender: \"IMAGE_CLASSIFICATION\" | \"OBJECT_DETECTION\" | \"TEXT_GENERATION\" |\"IMAGE_SEGMENTATION\" | \"FILL_MASK\" | \"CLASSIFICATION\" | \"REGRESSION\" | \"OTHER\".
Specify \"OTHER\" if none of the tasks listed fit your use case.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a\n single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple\n files that are all equally used in the load test. Each file in the archive must satisfy\n the size constraints of the InvokeEndpoint call.
" + "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
" } }, "CustomerMetadataProperties": { @@ -13576,13 +13548,13 @@ "DriftCheckBaselines": { "target": "com.amazonaws.sagemaker#DriftCheckBaselines", "traits": { - "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set\n using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker\n Pipelines in the Amazon SageMaker Developer Guide.
" + "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
" } }, "AdditionalInferenceSpecifications": { "target": "com.amazonaws.sagemaker#AdditionalInferenceSpecifications", "traits": { - "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional Inference\n Specification specifies artifacts based on this model package that can be used on\n inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.\n
" + "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
" } }, "SkipModelValidation": { @@ -13594,19 +13566,19 @@ "SourceUri": { "target": "com.amazonaws.sagemaker#ModelPackageSourceUri", "traits": { - "smithy.api#documentation": "The URI of the source for the model package. If you want to clone a model package, set\n it to the model package Amazon Resource Name (ARN). If you want to register a model, set\n it to the model ARN.
" + "smithy.api#documentation": "The URI of the source for the model package. If you want to clone a model package, set it to the model package Amazon Resource Name (ARN). If you want to register a model, set it to the model ARN.
" } }, "SecurityConfig": { "target": "com.amazonaws.sagemaker#ModelPackageSecurityConfig", "traits": { - "smithy.api#documentation": "The KMS Key ID (KMSKeyId) used for encryption of model\n package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
The model card associated with the model package. Since\n ModelPackageModelCard is tied to a model package, it is a specific\n usage of a model card and its schema is simplified compared to the schema of\n ModelCard. The ModelPackageModelCard schema does not\n include model_package_details, and model_overview is composed\n of the model_creator and model_artifact properties. For more\n information about the model package model card schema, see Model\n package model card schema. For more information about the model card\n associated with the model package, see View the Details of a Model\n Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
Creates a definition for a job that monitors model quality and drift. For information\n about model monitor, see Amazon SageMaker AI Model\n Monitor.
" + "smithy.api#documentation": "Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.
" } }, "com.amazonaws.sagemaker#CreateModelQualityJobDefinitionRequest": { @@ -13713,7 +13685,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -13723,7 +13695,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see \n \n Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -13764,7 +13736,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to\n monitor the data captured for an Amazon SageMaker AI Endpoint.
" + "smithy.api#documentation": "Creates a schedule that regularly starts Amazon SageMaker AI Processing Jobs to monitor the data captured for an Amazon SageMaker AI Endpoint.
" } }, "com.amazonaws.sagemaker#CreateMonitoringScheduleRequest": { @@ -13774,7 +13746,7 @@ "target": "com.amazonaws.sagemaker#MonitoringScheduleName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services \n Region within an Amazon Web Services account.
", + "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -13782,14 +13754,14 @@ "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring job.
", "smithy.api#required": {} } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost\n Management User Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -13827,7 +13799,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an SageMaker AI notebook instance. A notebook instance is a machine\n learning (ML) compute instance running on a Jupyter notebook.
\nIn a CreateNotebookInstance request, specify the type of ML compute\n instance that you want to run. SageMaker AI launches the instance, installs common\n libraries that you can use to explore datasets for model training, and attaches an ML\n storage volume to the notebook instance.
SageMaker AI also provides a set of example notebooks. Each notebook\n demonstrates how to use SageMaker AI with a specific algorithm or with a machine\n learning framework.
\nAfter receiving the request, SageMaker AI does the following:
\nCreates a network interface in the SageMaker AI VPC.
\n(Option) If you specified SubnetId, SageMaker AI creates\n a network interface in your own VPC, which is inferred from the subnet ID that\n you provide in the input. When creating this network interface, SageMaker AI attaches the security group that you specified in the request to the network\n interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the\n SageMaker AI VPC. If you specified SubnetId of your VPC,\n SageMaker AI specifies both network interfaces when launching this\n instance. This enables inbound traffic from your own VPC to the notebook\n instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker AI returns its Amazon Resource\n Name (ARN). You can't change the name of a notebook instance after you create\n it.
\nAfter SageMaker AI creates the notebook instance, you can connect to the\n Jupyter server and work in Jupyter notebooks. For example, you can write code to explore\n a dataset that you can use for model training, train a model, host models by creating\n SageMaker AI endpoints, and validate hosted models.
\nFor more information, see How It Works.
" + "smithy.api#documentation": "Creates an SageMaker AI notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker AI launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
SageMaker AI also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker AI with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker AI does the following:
Creates a network interface in the SageMaker AI VPC.
(Option) If you specified SubnetId, SageMaker AI creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker AI attaches the security group that you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker AI VPC. If you specified SubnetId of your VPC, SageMaker AI specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker AI returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
After SageMaker AI creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker AI endpoints, and validate hosted models.
For more information, see How It Works.
" } }, "com.amazonaws.sagemaker#CreateNotebookInstanceInput": { @@ -13852,75 +13824,75 @@ "SubnetId": { "target": "com.amazonaws.sagemaker#SubnetId", "traits": { - "smithy.api#documentation": "The ID of the subnet in a VPC to which you would like to have a connectivity from\n your ML compute instance.
" + "smithy.api#documentation": "The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
" } }, "SecurityGroupIds": { "target": "com.amazonaws.sagemaker#SecurityGroupIds", "traits": { - "smithy.api#documentation": "The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be\n for the same VPC as specified in the subnet.
" + "smithy.api#documentation": "The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
" } }, "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "When you send any requests to Amazon Web Services resources from the notebook\n instance, SageMaker AI assumes this role to perform tasks on your behalf. You must\n grant this role necessary permissions so SageMaker AI can perform these tasks. The\n policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com)\n permissions to assume this role. For more information, see SageMaker AI Roles.
\nTo be able to pass this role to SageMaker AI, the caller of this API must\n have the iam:PassRole permission.
When you send any requests to Amazon Web Services resources from the notebook instance, SageMaker AI assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker AI can perform these tasks. The policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker AI Roles.
To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that\n SageMaker AI uses to encrypt data on the storage volume attached to your\n notebook instance. The KMS key you provide must be enabled. For information, see Enabling and\n Disabling Keys in the Amazon Web Services Key Management Service\n Developer Guide.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service key that SageMaker AI uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the Amazon Web Services Key Management Service Developer Guide.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } }, "LifecycleConfigName": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigName", "traits": { - "smithy.api#documentation": "The name of a lifecycle configuration to associate with the notebook instance. For\n information about lifestyle configurations, see Step 2.1: (Optional)\n Customize a Notebook Instance.
" + "smithy.api#documentation": "The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "DirectInternetAccess": { "target": "com.amazonaws.sagemaker#DirectInternetAccess", "traits": { - "smithy.api#documentation": "Sets whether SageMaker AI provides internet access to the notebook instance. If\n you set this to Disabled this notebook instance is able to access resources\n only in your VPC, and is not be able to connect to SageMaker AI training and\n endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value\n of this parameter to Disabled only if you set a value for the\n SubnetId parameter.
Sets whether SageMaker AI provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker AI training and endpoint services unless you configure a NAT Gateway in your VPC.
For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
The size, in GB, of the ML storage volume to attach to the notebook instance. The\n default value is 5 GB.
" + "smithy.api#documentation": "The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
" } }, "AcceleratorTypes": { "target": "com.amazonaws.sagemaker#NotebookInstanceAcceleratorTypes", "traits": { - "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify a list of EI instance types to associate with this\n notebook instance.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of EI instance types to associate with this notebook instance.
" } }, "DefaultCodeRepository": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameOrUrl", "traits": { - "smithy.api#documentation": "A Git repository to associate with the notebook instance as its default code\n repository. This can be either the name of a Git repository stored as a resource in your\n account, or the URL of a Git repository in Amazon Web Services CodeCommit\n or in any other Git repository. When you open a notebook instance, it opens in the\n directory that contains this repository. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "A Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "AdditionalCodeRepositories": { "target": "com.amazonaws.sagemaker#AdditionalCodeRepositoryNamesOrUrls", "traits": { - "smithy.api#documentation": "An array of up to three Git repositories to associate with the notebook instance.\n These can be either the names of Git repositories stored as resources in your account,\n or the URL of Git repositories in Amazon Web Services CodeCommit\n or in any other Git repository. These repositories are cloned at the same level as the\n default repository of your notebook instance. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "RootAccess": { "target": "com.amazonaws.sagemaker#RootAccess", "traits": { - "smithy.api#documentation": "Whether root access is enabled or disabled for users of the notebook instance. The\n default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook\n instance. Because of this, lifecycle configurations associated with a notebook\n instance always run with root access even if you disable root access for\n users.
\nWhether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
Creates a lifecycle configuration that you can associate with a notebook instance. A\n lifecycle configuration is a collection of shell scripts that\n run when you create or start a notebook instance.
\nEach lifecycle configuration script has a limit of 16384 characters.
\nThe value of the $PATH environment variable that is available to both\n scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log\n group /aws/sagemaker/NotebookInstances in log stream\n [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs\n for longer than 5 minutes, it fails and the notebook instance is not created or\n started.
\nFor information about notebook instance lifestyle configurations, see Step\n 2.1: (Optional) Customize a Notebook Instance.
" + "smithy.api#documentation": "Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "com.amazonaws.sagemaker#CreateNotebookInstanceLifecycleConfigInput": { @@ -13971,19 +13943,19 @@ "OnCreate": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigList", "traits": { - "smithy.api#documentation": "A shell script that runs only once, when you create a notebook instance. The shell\n script must be a base64-encoded string.
" + "smithy.api#documentation": "A shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
" } }, "OnStart": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigList", "traits": { - "smithy.api#documentation": "A shell script that runs every time you start a notebook instance, including when you\n create the notebook instance. The shell script must be a base64-encoded string.
" + "smithy.api#documentation": "A shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -14036,7 +14008,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a job that optimizes a model for inference performance. To create the job, you\n provide the location of a source model, and you provide the settings for the optimization\n techniques that you want the job to apply. When the job completes successfully, SageMaker\n uploads the new optimized model to the output destination that you specify.
\nFor more information about how to use this action, and about the supported optimization\n techniques, see Optimize model inference with Amazon SageMaker.
" + "smithy.api#documentation": "Creates a job that optimizes a model for inference performance. To create the job, you provide the location of a source model, and you provide the settings for the optimization techniques that you want the job to apply. When the job completes successfully, SageMaker uploads the new optimized model to the output destination that you specify.
For more information about how to use this action, and about the supported optimization techniques, see Optimize model inference with Amazon SageMaker.
" } }, "com.amazonaws.sagemaker#CreateOptimizationJobRequest": { @@ -14054,7 +14026,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
\nDuring model optimization, Amazon SageMaker AI needs your permission to:
\nRead input data from an S3 bucket
\nWrite model artifacts to an S3 bucket
\nWrite logs to Amazon CloudWatch Logs
\nPublish metrics to Amazon CloudWatch
\nYou grant permissions for all of these tasks to an IAM role. To pass this\n role to Amazon SageMaker AI, the caller of this API must have the\n iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.\n
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model optimization, Amazon SageMaker AI needs your permission to:
Read input data from an S3 bucket
Write model artifacts to an S3 bucket
Write logs to Amazon CloudWatch Logs
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
A list of key-value pairs associated with the optimization job. For more information,\n see Tagging Amazon Web Services resources in the Amazon Web Services General Reference\n Guide.
" + "smithy.api#documentation": "A list of key-value pairs associated with the optimization job. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } }, "VpcConfig": { @@ -14245,7 +14217,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "SageMaker Partner AI Apps uses Amazon Web Services KMS to encrypt data at rest using an Amazon Web Services managed key by default. For more control, specify a\n customer managed key.
" + "smithy.api#documentation": "SageMaker Partner AI Apps uses Amazon Web Services KMS to encrypt data at rest using an Amazon Web Services managed key by default. For more control, specify a customer managed key.
" } }, "MaintenanceConfig": { @@ -14292,7 +14264,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per\n resource.
" + "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per resource.
" } } }, @@ -14357,13 +14329,13 @@ "PipelineDefinition": { "target": "com.amazonaws.sagemaker#PipelineDefinition", "traits": { - "smithy.api#documentation": "The JSON \n pipeline definition of the pipeline.
" + "smithy.api#documentation": "The JSON pipeline definition of the pipeline.
" } }, "PipelineDefinitionS3Location": { "target": "com.amazonaws.sagemaker#PipelineDefinitionS3Location", "traits": { - "smithy.api#documentation": "The location of the pipeline definition stored in Amazon S3. If specified, \n SageMaker will retrieve the pipeline definition from this location.
" + "smithy.api#documentation": "The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
" } }, "PipelineDescription": { @@ -14376,7 +14348,7 @@ "target": "com.amazonaws.sagemaker#IdempotencyToken", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than one time.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -14398,7 +14370,7 @@ "ParallelismConfiguration": { "target": "com.amazonaws.sagemaker#ParallelismConfiguration", "traits": { - "smithy.api#documentation": "This is the configuration that controls the parallelism of the pipeline. \n If specified, it applies to all runs of this pipeline by default.
" + "smithy.api#documentation": "This is the configuration that controls the parallelism of the pipeline. If specified, it applies to all runs of this pipeline by default.
" } } }, @@ -14434,7 +14406,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the\n user will be automatically signed in to the domain, and granted access to all of the Apps and\n files associated with the Domain's Amazon Elastic File System volume. This operation can only be\n called when the authentication mode equals IAM.
\nThe IAM role or user passed to this API defines the permissions to access\n the app. Once the presigned URL is created, no additional permission is required to access\n this URL. IAM authorization policies for this API are also enforced for every\n HTTP request and WebSocket frame that attempts to connect to the app.
\nYou can restrict access to this API and to the URL that it returns to a list of IP\n addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more\n information, see Connect to Amazon SageMaker AI\n Studio Through an Interface VPC Endpoint .
\nThe URL that you get from a call to CreatePresignedDomainUrl has a\n default timeout of 5 minutes. You can configure this value using\n ExpiresInSeconds. If you try to use the URL after the timeout limit\n expires, you are directed to the Amazon Web Services console sign-in page.
The JupyterLab session default expiration time is 12 hours. You can configure this\n value using SessionExpirationDurationInSeconds.
\nCreates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to the domain, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System volume. This operation can only be called when the authentication mode equals IAM.
The IAM role or user passed to this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to Amazon SageMaker AI Studio Through an Interface VPC Endpoint .
The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
The JupyterLab session default expiration time is 12 hours. You can configure this value using SessionExpirationDurationInSeconds.
The landing page that the user is directed to when accessing the presigned URL. Using this\n value, users can access Studio or Studio Classic, even if it is not the default experience for\n the domain. The supported values are:
\n\n studio::relative/path: Directs users to the relative path in\n Studio.
\n app:JupyterServer:relative/path: Directs users to the relative path in\n the Studio Classic application.
\n app:JupyterLab:relative/path: Directs users to the relative path in the\n JupyterLab application.
\n app:RStudioServerPro:relative/path: Directs users to the relative path in\n the RStudio application.
\n app:CodeEditor:relative/path: Directs users to the relative path in the\n Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
\n app:Canvas:relative/path: Directs users to the relative path in the\n Canvas application.
The landing page that the user is directed to when accessing the presigned URL. Using this value, users can access Studio or Studio Classic, even if it is not the default experience for the domain. The supported values are:
studio::relative/path: Directs users to the relative path in Studio.
app:JupyterServer:relative/path: Directs users to the relative path in the Studio Classic application.
app:JupyterLab:relative/path: Directs users to the relative path in the JupyterLab application.
app:RStudioServerPro:relative/path: Directs users to the relative path in the RStudio application.
app:CodeEditor:relative/path: Directs users to the relative path in the Code Editor, based on Code-OSS, Visual Studio Code - Open Source application.
app:Canvas:relative/path: Directs users to the relative path in the Canvas application.
Returns a presigned URL that you can use to connect to the MLflow UI attached to your\n tracking server. For more information, see Launch the MLflow UI using a presigned URL.
" + "smithy.api#documentation": "Returns a presigned URL that you can use to connect to the MLflow UI attached to your tracking server. For more information, see Launch the MLflow UI using a presigned URL.
" } }, "com.amazonaws.sagemaker#CreatePresignedMlflowTrackingServerUrlRequest": { @@ -14530,7 +14502,7 @@ "ExpiresInSeconds": { "target": "com.amazonaws.sagemaker#ExpiresInSeconds", "traits": { - "smithy.api#documentation": "The duration in seconds that your presigned URL is valid. The presigned URL can be used\n only once.
" + "smithy.api#documentation": "The duration in seconds that your presigned URL is valid. The presigned URL can be used only once.
" } }, "SessionExpirationDurationInSeconds": { @@ -14567,7 +14539,7 @@ "target": "com.amazonaws.sagemaker#CreatePresignedNotebookInstanceUrlOutput" }, "traits": { - "smithy.api#documentation": "Returns a URL that you can use to connect to the Jupyter server from a notebook\n instance. In the SageMaker AI console, when you choose Open next to a\n notebook instance, SageMaker AI opens a new tab showing the Jupyter server home\n page from the notebook instance. The console uses this API to get the URL and show the\n page.
The IAM role or user used to call this API defines the permissions to\n access the notebook instance. Once the presigned URL is created, no additional\n permission is required to access this URL. IAM authorization policies for\n this API are also enforced for every HTTP request and WebSocket frame that attempts to\n connect to the notebook instance.
\nYou can restrict access to this API and to the URL that it returns to a list of IP\n addresses that you specify. Use the NotIpAddress condition operator and the\n aws:SourceIP condition context key to specify the list of IP addresses\n that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you\n try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
\nReturns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker AI console, when you choose Open next to a notebook instance, SageMaker AI opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
An array of inputs configuring the data to download into the processing\n container.
" + "smithy.api#documentation": "An array of inputs configuring the data to download into the processing container.
" } }, "ProcessingOutputConfig": { @@ -14648,7 +14620,7 @@ "target": "com.amazonaws.sagemaker#ProcessingJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the processing job. The name must be unique within an Amazon Web Services\n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -14656,7 +14628,7 @@ "target": "com.amazonaws.sagemaker#ProcessingResources", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a\n processing job. In distributed training, you specify more than one instance.
", + "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
", "smithy.api#required": {} } }, @@ -14677,27 +14649,27 @@ "Environment": { "target": "com.amazonaws.sagemaker#ProcessingEnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the Docker container. Up to 100 key and values\n entries in the map are supported.
\nDo not include any security-sensitive information including account access IDs, secrets, \n or tokens in any environment fields. As part of the shared responsibility \n model, you are responsible for any potential exposure, unauthorized access, or compromise of \n your sensitive data if caused by security-sensitive information included in the \n request environment variable or plain text fields.
\nThe environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
Networking options for a processing job, such as whether to allow inbound and outbound\n network calls to and from processing containers, and the VPC subnets and security groups\n to use for VPC-enabled processing jobs.
" + "smithy.api#documentation": "Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.
" } }, "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on\n your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and\n Cost Management User Guide.
\nDo not include any security-sensitive information including account access IDs, secrets, \n or tokens in any tags. As part of the shared responsibility \n model, you are responsible for any potential exposure, unauthorized access, or compromise of \n your sensitive data if caused by security-sensitive information included in the \n request tag variable or plain text fields.
\n(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any tags. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request tag variable or plain text fields.
Creates a machine learning (ML) project that can contain one or more templates that set\n up an ML pipeline from training to deploying an approved model.
" + "smithy.api#documentation": "Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
" } }, "com.amazonaws.sagemaker#CreateProjectInput": { @@ -14761,13 +14733,13 @@ "ServiceCatalogProvisioningDetails": { "target": "com.amazonaws.sagemaker#ServiceCatalogProvisioningDetails", "traits": { - "smithy.api#documentation": "The product ID and provisioning artifact ID to provision a service catalog. The provisioning \n artifact ID will default to the latest provisioning artifact ID of the product, if you don't \n provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service\n Catalog.
" + "smithy.api#documentation": "The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs that you want to use to organize and track your Amazon Web Services\n resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" + "smithy.api#documentation": "An array of key-value pairs that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } } }, @@ -14841,7 +14813,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "Tags to associated with the space. Each tag consists of a key and an optional value. Tag\n keys must be unique for each resource. Tags are searchable using the Search\n API.
Tags to associated with the space. Each tag consists of a key and an optional value. Tag keys must be unique for each resource. Tags are searchable using the Search API.
The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This\n content must be base64 encoded.
", + "smithy.api#documentation": "The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This content must be base64 encoded.
", "smithy.api#required": {} } }, @@ -14934,7 +14906,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an\n optional value. Tag keys must be unique per resource. Tags are searchable using the Search\n API.
" + "smithy.api#documentation": "Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
" } } }, @@ -14976,7 +14948,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a model training job. After training completes, SageMaker saves the resulting\n model artifacts to an Amazon S3 location that you specify.
\nIf you choose to host your model using SageMaker hosting services, you can use the\n resulting model artifacts as part of the model. You can also use the artifacts in a\n machine learning service other than SageMaker, provided that you know how to use them for\n inference. \n
\nIn the request body, you provide the following:
\n\n AlgorithmSpecification - Identifies the training algorithm to\n use.\n
\n HyperParameters - Specify these algorithm-specific parameters to\n enable the estimation of model parameters during training. Hyperparameters can\n be tuned to optimize this learning process. For a list of hyperparameters for\n each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets, \n or tokens in any hyperparameter fields. As part of the shared responsibility \n model, you are responsible for any potential exposure, unauthorized access, or compromise of \n your sensitive data if caused by security-sensitive information included in the \n request hyperparameter variable or plain text fields.
\n\n InputDataConfig - Describes the input required by the training\n job and the Amazon S3, EFS, or FSx location where it is stored.
\n OutputDataConfig - Identifies the Amazon S3 bucket where you want\n SageMaker to save the results of model training.
\n ResourceConfig - Identifies the resources, ML compute\n instances, and ML storage volumes to deploy for model training. In distributed\n training, you specify more than one instance.
\n EnableManagedSpotTraining - Optimize the cost of training machine\n learning models by up to 80% by using Amazon EC2 Spot instances. For more\n information, see Managed Spot\n Training.
\n RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on\n your behalf during model training.\n \n You must grant this role the necessary permissions so that SageMaker can successfully\n complete model training.
\n StoppingCondition - To help cap training costs, use\n MaxRuntimeInSeconds to set a time limit for training. Use\n MaxWaitTimeInSeconds to specify how long a managed spot\n training job has to complete.
\n Environment - The environment variables to set in the Docker\n container.
Do not include any security-sensitive information including account access IDs, secrets, \n or tokens in any environment fields. As part of the shared responsibility model, you are \n responsible for any potential exposure, unauthorized access, or compromise of your sensitive\n data if caused by security-sensitive information included in the request environment variable \n or plain text fields.
\n\n RetryStrategy - The number of times to retry the job when the job\n fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
" + "smithy.api#documentation": "Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
In the request body, you provide the following:
AlgorithmSpecification - Identifies the training algorithm to use.
HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request hyperparameter variable or plain text fields.
InputDataConfig - Describes the input required by the training job and the Amazon S3, EFS, or FSx location where it is stored.
OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
Environment - The environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
For more information about SageMaker, see How It Works.
" } }, "com.amazonaws.sagemaker#CreateTrainingJobRequest": { @@ -14986,21 +14958,21 @@ "target": "com.amazonaws.sagemaker#TrainingJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the training job. The name must be unique within an Amazon Web Services\n Region in an Amazon Web Services account.
", + "smithy.api#documentation": "The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
", "smithy.api#required": {} } }, "HyperParameters": { "target": "com.amazonaws.sagemaker#HyperParameters", "traits": { - "smithy.api#documentation": "Algorithm-specific parameters that influence the quality of the model. You set\n hyperparameters before you start the learning process. For a list of hyperparameters for\n each training algorithm provided by SageMaker, see Algorithms.
\nYou can specify a maximum of 100 hyperparameters. Each hyperparameter is a\n key-value pair. Each key and value is limited to 256 characters, as specified by the\n Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets, \n or tokens in any hyperparameter fields. As part of the shared responsibility \n model, you are responsible for any potential exposure, unauthorized access, or compromise \n of your sensitive data if caused by any security-sensitive information included in the \n request hyperparameter variable or plain text fields.
\nAlgorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is limited to 256 characters, as specified by the Length Constraint.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any hyperparameter fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request hyperparameter variable or plain text fields.
The registry path of the Docker image that contains the training algorithm and\n algorithm-specific metadata, including the input mode. For more information about\n algorithms provided by SageMaker, see Algorithms. For information about\n providing your own algorithms, see Using Your Own Algorithms with\n Amazon SageMaker.
", + "smithy.api#documentation": "The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.
", "smithy.api#required": {} } }, @@ -15008,21 +14980,21 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform\n tasks on your behalf.
\nDuring model training, SageMaker needs your permission to read input data from an S3\n bucket, download a Docker image that contains training code, write model artifacts to an\n S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant\n permissions for all of these tasks to an IAM role. For more information, see SageMaker\n Roles.
\nTo be able to pass this role to SageMaker, the caller of this API must have the\n iam:PassRole permission.
The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more information, see SageMaker Roles.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
An array of Channel objects. Each channel is a named input source.\n InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an\n algorithm might have two channels of input data, training_data and\n validation_data. The configuration for each channel provides the S3,\n EFS, or FSx location where the input data is stored. It also provides information about\n the stored data: the MIME type, compression method, and whether the data is wrapped in\n RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input\n data files from an S3 bucket to a local directory in the Docker container, or makes it\n available as input streams. For example, if you specify an EFS location, input data\n files are available as input streams. They do not need to be downloaded.
\nYour input must be in the same Amazon Web Services region as your training\n job.
" + "smithy.api#documentation": "An array of Channel objects. Each channel is a named input source. InputDataConfig describes the input data and its location.
Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of input data, training_data and validation_data. The configuration for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
Your input must be in the same Amazon Web Services region as your training job.
" } }, "OutputDataConfig": { "target": "com.amazonaws.sagemaker#OutputDataConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the path to the S3 location where you want to store model artifacts. SageMaker\n creates subfolders for the artifacts.
", + "smithy.api#documentation": "Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
", "smithy.api#required": {} } }, @@ -15030,52 +15002,52 @@ "target": "com.amazonaws.sagemaker#ResourceConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The resources, including the ML compute instances and ML storage volumes, to use\n for model training.
\nML storage volumes store model artifacts and incremental states. Training\n algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use\n the ML storage volume to store the training data, choose File as the\n TrainingInputMode in the algorithm specification. For distributed\n training algorithms, specify an instance count greater than 1.
The resources, including the ML compute instances and ML storage volumes, to use for model training.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
A VpcConfig object that specifies the VPC that you want your training job to\n connect to. Control access to and from your training container by configuring the VPC.\n For more information, see Protect Training Jobs by Using an Amazon\n Virtual Private Cloud.
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your training job to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
" } }, "StoppingCondition": { "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a limit to how long a model training job can run. It also specifies how long\n a managed Spot training job has to complete. When the job reaches the time limit, SageMaker\n ends the training job. Use this API to cap model training costs.
\nTo stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays\n job termination for 120 seconds. Algorithms can use this 120-second window to save the\n model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
\nDo not include any security-sensitive information including account access IDs, secrets, \n or tokens in any tags. As part of the shared responsibility model, you are \n responsible for any potential exposure, unauthorized access, or compromise \n of your sensitive data if caused by any security-sensitive information included in the \n request tag variable or plain text fields.
\nAn array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any tags. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by any security-sensitive information included in the request tag variable or plain text fields.
Isolates the training container. No inbound or outbound network calls can be made,\n except for calls between peers within a training cluster for distributed training. If\n you enable network isolation for training jobs that are configured to use a VPC, SageMaker\n downloads and uploads customer data and model artifacts through the specified VPC, but\n the training container does not have network access.
" + "smithy.api#documentation": "Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
" } }, "EnableInterContainerTrafficEncryption": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "To encrypt all communications between ML compute instances in distributed training,\n choose True. Encryption provides greater security for distributed training,\n but training might take longer. How long it takes depends on the amount of communication\n between compute instances, especially if you use a deep learning algorithm in\n distributed training. For more information, see Protect Communications Between ML\n Compute Instances in a Distributed Training Job.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between ML Compute Instances in a Distributed Training Job.
To train models using managed spot training, choose True. Managed spot\n training provides a fully managed and scalable infrastructure for training machine\n learning models. this option is useful when training jobs can be interrupted and when\n there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be\n used as a starting point to train models incrementally. Amazon SageMaker provides metrics and\n logs in CloudWatch. They can be used to see when managed spot training jobs are running,\n interrupted, resumed, or completed.
" + "smithy.api#documentation": "To train models using managed spot training, choose True. Managed spot training provides a fully managed and scalable infrastructure for training machine learning models. this option is useful when training jobs can be interrupted and when there is flexibility when the training job is run.
The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
" } }, "CheckpointConfig": { "target": "com.amazonaws.sagemaker#CheckpointConfig", "traits": { - "smithy.api#documentation": "Contains information about the output location for managed spot training checkpoint\n data.
" + "smithy.api#documentation": "Contains information about the output location for managed spot training checkpoint data.
" } }, "DebugHookConfig": { @@ -15099,25 +15071,25 @@ "ProfilerRuleConfigurations": { "target": "com.amazonaws.sagemaker#ProfilerRuleConfigurations", "traits": { - "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework\n metrics.
" + "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
" } }, "Environment": { "target": "com.amazonaws.sagemaker#TrainingEnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the Docker container.
\nDo not include any security-sensitive information including account access IDs, \n secrets, or tokens in any environment fields. As part of the shared responsibility model, \n you are responsible for any potential exposure, unauthorized access, or compromise of your \n sensitive data if caused by security-sensitive information included in the request environment variable\n or plain text fields.
\nThe environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
The number of times to retry the job when the job fails due to an\n InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
Configuration for remote debugging. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" + "smithy.api#documentation": "Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
" } }, "InfraCheckConfig": { @@ -15129,7 +15101,7 @@ "SessionChainingConfig": { "target": "com.amazonaws.sagemaker#SessionChainingConfig", "traits": { - "smithy.api#documentation": "Contains information about attribute-based access control (ABAC) for the training\n job.
" + "smithy.api#documentation": "Contains information about attribute-based access control (ABAC) for the training job.
" } } }, @@ -15173,7 +15145,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a new training plan in SageMaker to reserve compute capacity.
\nAmazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU\n capacity for large-scale AI model training. It provides a way to secure predictable access\n to computational resources within specific timelines and budgets, without the need to\n manage underlying infrastructure.
\n\n How it works\n
\nPlans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod\n clusters, automatically provisioning resources, setting up infrastructure, executing\n workloads, and handling infrastructure failures.
\n\n Plan creation workflow\n
\nUsers search for available plan offerings based on their requirements (e.g.,\n instance type, count, start time, duration) using the \n SearchTrainingPlanOfferings\n API operation.
They create a plan that best matches their needs using the ID of the plan offering\n they want to use.
\nAfter successful upfront payment, the plan's status becomes\n Scheduled.
The plan can be used to:
\nQueue training jobs.
\nAllocate to an instance group of a SageMaker HyperPod cluster.
\nWhen the plan start date arrives, it becomes Active. Based on\n available reserved capacity:
Training jobs are launched.
\nInstance groups are provisioned.
\n\n Plan composition\n
\nA plan can consist of one or more Reserved Capacities, each defined by a specific\n instance type, quantity, Availability Zone, duration, and start and end times. For more\n information about Reserved Capacity, see \n ReservedCapacitySummary\n .
Creates a new training plan in SageMaker to reserve compute capacity.
Amazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU capacity for large-scale AI model training. It provides a way to secure predictable access to computational resources within specific timelines and budgets, without the need to manage underlying infrastructure.
How it works
Plans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod clusters, automatically provisioning resources, setting up infrastructure, executing workloads, and handling infrastructure failures.
Plan creation workflow
Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration) using the SearchTrainingPlanOfferings API operation.
They create a plan that best matches their needs using the ID of the plan offering they want to use.
After successful upfront payment, the plan's status becomes Scheduled.
The plan can be used to:
Queue training jobs.
Allocate to an instance group of a SageMaker HyperPod cluster.
When the plan start date arrives, it becomes Active. Based on available reserved capacity:
Training jobs are launched.
Instance groups are provisioned.
Plan composition
A plan can consist of one or more Reserved Capacities, each defined by a specific instance type, quantity, Availability Zone, duration, and start and end times. For more information about Reserved Capacity, see ReservedCapacitySummary .
The unique identifier of the training plan offering to use for creating this\n plan.
", + "smithy.api#documentation": "The unique identifier of the training plan offering to use for creating this plan.
", "smithy.api#required": {} } }, @@ -15242,7 +15214,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a transform job. A transform job uses a trained model to get inferences on a\n dataset and saves these results to an Amazon S3 location that you specify.
\nTo perform batch transformations, you create a transform job and use the data that you\n have readily available.
\nIn the request body, you provide the following:
\n\n TransformJobName - Identifies the transform job. The name must be\n unique within an Amazon Web Services Region in an Amazon Web Services account.
\n ModelName - Identifies the model to use. ModelName\n must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services\n\t\t account. For information on creating a model, see CreateModel.
\n TransformInput - Describes the dataset to be transformed and the\n Amazon S3 location where it is stored.
\n TransformOutput - Identifies the Amazon S3 location where you want\n Amazon SageMaker to save the results from the transform job.
\n TransformResources - Identifies the ML compute instances and AMI\n image versions for the transform job.
For more information about how batch transformation works, see Batch\n Transform.
" + "smithy.api#documentation": "Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
To perform batch transformations, you create a transform job and use the data that you have readily available.
In the request body, you provide the following:
TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
TransformResources - Identifies the ML compute instances and AMI image versions for the transform job.
For more information about how batch transformation works, see Batch Transform.
" } }, "com.amazonaws.sagemaker#CreateTransformJobRequest": { @@ -15252,7 +15224,7 @@ "target": "com.amazonaws.sagemaker#TransformJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the transform job. The name must be unique within an Amazon Web Services Region in an\n Amazon Web Services account.
", + "smithy.api#documentation": "The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -15260,45 +15232,45 @@ "target": "com.amazonaws.sagemaker#ModelName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the model that you want to use for the transform job.\n ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services\n Region in an Amazon Web Services account.
The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.
The maximum number of parallel requests that can be sent to each instance in a\n transform job. If MaxConcurrentTransforms is set to 0 or left\n unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your\n chosen algorithm. If the execution-parameters endpoint is not enabled, the default value\n is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to\n set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.
Configures the timeout and maximum number of retries for processing a transform job\n invocation.
" + "smithy.api#documentation": "Configures the timeout and maximum number of retries for processing a transform job invocation.
" } }, "MaxPayloadInMB": { "target": "com.amazonaws.sagemaker#MaxPayloadInMB", "traits": { - "smithy.api#documentation": "The maximum allowed size of the payload, in MB. A payload is the\n data portion of a record (without metadata). The value in MaxPayloadInMB\n must be greater than, or equal to, the size of a single record. To estimate the size of\n a record in MB, divide the size of your dataset by the number of records. To ensure that\n the records fit within the maximum payload size, we recommend using a slightly larger\n value. The default value is 6 MB.\n
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify\n the MaxConcurrentTransforms parameter, the value of\n (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100\n MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP\n chunked encoding, set the value to 0.\n This\n feature works only in supported algorithms. Currently, Amazon SageMaker built-in\n algorithms do not support HTTP chunked encoding.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.
The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms * MaxPayloadInMB) also cannot exceed 100 MB.
For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.
Specifies the number of records to include in a mini-batch for an HTTP inference\n request. A record\n is a single unit of input data that\n inference can be made on. For example, a single line in a CSV file is a record.
\nTo enable the batch strategy, you must set the SplitType property to\n Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set\n BatchStrategy to SingleRecord and SplitType\n to Line.
To fit as many records in a mini-batch as can fit within the\n MaxPayloadInMB limit, set BatchStrategy to\n MultiRecord and SplitType to Line.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set the SplitType property to Line, RecordIO, or TFRecord.
To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.
To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.
The environment variables to set in the Docker container. Don't include any\n sensitive data in your environment variables. We support up to 16 key and\n values entries in the map.
" + "smithy.api#documentation": "The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables. We support up to 16 key and values entries in the map.
" } }, "TransformInput": { "target": "com.amazonaws.sagemaker#TransformInput", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Describes the input source and\n the\n way the transform job consumes it.
", + "smithy.api#documentation": "Describes the input source and the way the transform job consumes it.
", "smithy.api#required": {} } }, @@ -15320,20 +15292,20 @@ "target": "com.amazonaws.sagemaker#TransformResources", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Describes the resources, including\n ML\n instance types and ML instance count, to use for the transform\n job.
", + "smithy.api#documentation": "Describes the resources, including ML instance types and ML instance count, to use for the transform job.
", "smithy.api#required": {} } }, "DataProcessing": { "target": "com.amazonaws.sagemaker#DataProcessing", "traits": { - "smithy.api#documentation": "The data structure used to specify the data to be used for inference in a batch\n transform job and to associate the data that is relevant to the prediction results in\n the output. The input filter provided allows you to exclude input data that is not\n needed for inference in a batch transform job. The output filter provided allows you to\n include input data relevant to interpreting the predictions in the output from the job.\n For more information, see Associate Prediction\n Results with their Corresponding Input Records.
" + "smithy.api#documentation": "The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "(Optional)\n An\n array of key-value pairs. For more information, see Using\n Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User\n Guide.
" + "smithy.api#documentation": "(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } }, "ExperimentConfig": { @@ -15377,7 +15349,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates an SageMaker trial. A trial is a set of steps called\n trial components that produce a machine learning model. A trial is part\n of a single SageMaker experiment.
\nWhen you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial\n components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you\n must use the logging APIs provided by the SDK.
\nYou can add tags to a trial and then use the Search API to search for\n the tags.
\nTo get a list of all your trials, call the ListTrials API. To view a\n trial's properties, call the DescribeTrial API. To create a trial component,\n call the CreateTrialComponent API.
" + "smithy.api#documentation": "Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial and then use the Search API to search for the tags.
To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
" } }, "com.amazonaws.sagemaker#CreateTrialComponent": { @@ -15394,7 +15366,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a trial component, which is a stage of a machine learning\n trial. A trial is composed of one or more trial components. A trial\n component can be used in multiple trials.
\nTrial components include pre-processing jobs, training jobs, and batch transform\n jobs.
\nWhen you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial\n components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you\n must use the logging APIs provided by the SDK.
\nYou can add tags to a trial component and then use the Search API to\n search for the tags.
" + "smithy.api#documentation": "Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
Trial components include pre-processing jobs, training jobs, and batch transform jobs.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to a trial component and then use the Search API to search for the tags.
" } }, "com.amazonaws.sagemaker#CreateTrialComponentRequest": { @@ -15404,20 +15376,20 @@ "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the component. The name must be unique in your Amazon Web Services account and is not\n case-sensitive.
", + "smithy.api#documentation": "The name of the component. The name must be unique in your Amazon Web Services account and is not case-sensitive.
", "smithy.api#required": {} } }, "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the component as displayed. The name doesn't need to be unique. If\n DisplayName isn't specified, TrialComponentName is\n displayed.
The name of the component as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
\nInProgress
\nCompleted
\nFailed
\nThe status of the component. States include:
InProgress
Completed
Failed
The input artifacts for the component. Examples of input artifacts are datasets,\n algorithms, hyperparameters, source code, and instance types.
" + "smithy.api#documentation": "The input artifacts for the component. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types.
" } }, "OutputArtifacts": { "target": "com.amazonaws.sagemaker#TrialComponentArtifacts", "traits": { - "smithy.api#documentation": "The output artifacts for the component. Examples of output artifacts are metrics,\n snapshots, logs, and images.
" + "smithy.api#documentation": "The output artifacts for the component. Examples of output artifacts are metrics, snapshots, logs, and images.
" } }, "MetadataProperties": { @@ -15456,7 +15428,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of tags to associate with the component. You can use Search API\n to search on the tags.
" + "smithy.api#documentation": "A list of tags to associate with the component. You can use Search API to search on the tags.
" } } }, @@ -15485,14 +15457,14 @@ "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the trial. The name must be unique in your Amazon Web Services account and is not\n case-sensitive.
", + "smithy.api#documentation": "The name of the trial. The name must be unique in your Amazon Web Services account and is not case-sensitive.
", "smithy.api#required": {} } }, "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the trial as displayed. The name doesn't need to be unique. If\n DisplayName isn't specified, TrialName is displayed.
The name of the trial as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialName is displayed.
A list of tags to associate with the trial. You can use Search API to\n search on the tags.
" + "smithy.api#documentation": "A list of tags to associate with the trial. You can use Search API to search on the tags.
" } } }, @@ -15548,7 +15520,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a user profile. A user profile represents a single user within a domain, and is\n the main way to reference a \"person\" for the purposes of sharing, reporting, and other\n user-oriented features. This entity is created when a user onboards to a domain. If an\n administrator invites a person by email or imports them from IAM Identity Center, a user\n profile is automatically created. A user profile is the primary holder of settings for an\n individual user and has a reference to the user's private Amazon Elastic File System home\n directory.
" + "smithy.api#documentation": "Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a \"person\" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to a domain. If an administrator invites a person by email or imports them from IAM Identity Center, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System home directory.
" } }, "com.amazonaws.sagemaker#CreateUserProfileRequest": { @@ -15573,19 +15545,19 @@ "SingleSignOnUserIdentifier": { "target": "com.amazonaws.sagemaker#SingleSignOnUserIdentifier", "traits": { - "smithy.api#documentation": "A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only\n supported value is \"UserName\". If the Domain's AuthMode is IAM Identity Center, this field is\n required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.\n
" + "smithy.api#documentation": "A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is \"UserName\". If the Domain's AuthMode is IAM Identity Center, this field is required. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
" } }, "SingleSignOnUserValue": { "target": "com.amazonaws.sagemaker#String256", "traits": { - "smithy.api#documentation": "The username of the associated Amazon Web Services Single Sign-On User for this\n UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must\n match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
" + "smithy.api#documentation": "The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain's AuthMode is IAM Identity Center, this field is required, and must match a valid username of a user in your directory. If the Domain's AuthMode is not IAM Identity Center, this field cannot be specified.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per\n resource.
\nTags that you specify for the User Profile are also added to all Apps that the User\n Profile launches.
" + "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per resource.
Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.
" } }, "UserSettings": { @@ -15622,7 +15594,7 @@ "target": "com.amazonaws.sagemaker#CreateWorkforceResponse" }, "traits": { - "smithy.api#documentation": "Use this operation to create a workforce. This operation will return an error\n if a workforce already exists in the Amazon Web Services Region that you specify. You can only\n create one workforce in each Amazon Web Services Region per Amazon Web Services account.
\nIf you want to create a new workforce in an Amazon Web Services Region where \n a workforce already exists, use the DeleteWorkforce API\n operation to delete the existing workforce and then use CreateWorkforce \n to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool\n in CognitoConfig.\n You can also create an Amazon Cognito workforce using the Amazon SageMaker console. \n For more information, see \n \n Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP\n configuration in OidcConfig. Your OIDC IdP must support groups\n because groups are used by Ground Truth and Amazon A2I to create work teams. \n For more information, see \n Create a Private Workforce (OIDC IdP).
Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the DeleteWorkforce API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
Use this parameter to configure an Amazon Cognito private workforce.\n A single Cognito workforce is created using and corresponds to a single\n \n Amazon Cognito user pool.
\nDo not use OidcConfig if you specify values for \n CognitoConfig.
Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
Do not use OidcConfig if you specify values for CognitoConfig.
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
\nDo not use CognitoConfig if you specify values for \n OidcConfig.
Use this parameter to configure a private workforce using your own OIDC Identity Provider.
Do not use CognitoConfig if you specify values for OidcConfig.
An array of key-value pairs that contain metadata to help you categorize and \n organize our workforce. Each tag consists of a key and a value, \n both of which you define.
" + "smithy.api#documentation": "An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.
" } }, "WorkforceVpcConfig": { @@ -15701,7 +15673,7 @@ } ], "traits": { - "smithy.api#documentation": "Creates a new work team for labeling your data. A work team is defined by one or more\n Amazon Cognito user pools. You must first create the user pools before you can create a work\n team.
\nYou cannot create more than 25 work teams in an account and region.
" + "smithy.api#documentation": "Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
You cannot create more than 25 work teams in an account and region.
" } }, "com.amazonaws.sagemaker#CreateWorkteamRequest": { @@ -15725,7 +15697,7 @@ "target": "com.amazonaws.sagemaker#MemberDefinitions", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of MemberDefinition objects that contains objects that identify\n the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For\n private workforces created using Amazon Cognito use CognitoMemberDefinition. For\n workforces created using your own OIDC identity provider (IdP) use\n OidcMemberDefinition. Do not provide input for both of these parameters\n in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito\n user groups within the user pool used to create a workforce. All of the\n CognitoMemberDefinition objects that make up the member definition must\n have the same ClientId and UserPool values. To add a Amazon\n Cognito user group to an existing worker pool, see Adding groups to a User\n Pool. For more information about user pools, see Amazon Cognito User\n Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to \n include in your private work team in OidcMemberDefinition by listing those groups\n in Groups.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups.
An array of key-value pairs.
\nFor more information, see Resource\n Tag and Using\n Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User\n Guide.
" + "smithy.api#documentation": "An array of key-value pairs.
For more information, see Resource Tag and Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, @@ -15766,7 +15738,7 @@ "WorkteamArn": { "target": "com.amazonaws.sagemaker#WorkteamArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the\n work team.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.
" } } }, @@ -15845,7 +15817,7 @@ } }, "traits": { - "smithy.api#documentation": "A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI\n Studio.
" + "smithy.api#documentation": "A file system, created by you, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" } }, "com.amazonaws.sagemaker#CustomFileSystemConfig": { @@ -15865,7 +15837,7 @@ } }, "traits": { - "smithy.api#documentation": "The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI\n Studio.
" + "smithy.api#documentation": "The settings for assigning a custom file system to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" } }, "com.amazonaws.sagemaker#CustomFileSystemConfigs": { @@ -15919,7 +15891,7 @@ } }, "traits": { - "smithy.api#documentation": "A custom SageMaker AI image. For more information, see\n Bring your own SageMaker AI image.
" + "smithy.api#documentation": "A custom SageMaker AI image. For more information, see Bring your own SageMaker AI image.
" } }, "com.amazonaws.sagemaker#CustomImageContainerArguments": { @@ -16077,7 +16049,7 @@ "target": "com.amazonaws.sagemaker#SamplingPercentage", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The percentage of requests SageMaker AI will capture. A lower value is recommended\n for Endpoints with high traffic.
", + "smithy.api#documentation": "The percentage of requests SageMaker AI will capture. A lower value is recommended for Endpoints with high traffic.
", "smithy.api#required": {} } }, @@ -16092,21 +16064,21 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI\n uses to encrypt the captured data at rest using Amazon S3 server-side\n encryption.
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI uses to encrypt the captured data at rest using Amazon S3 server-side encryption.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Specifies data Model Monitor will capture. You can configure whether to collect only\n input, only output, or both
", + "smithy.api#documentation": "Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both
", "smithy.api#required": {} } }, "CaptureContentTypeHeader": { "target": "com.amazonaws.sagemaker#CaptureContentTypeHeader", "traits": { - "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified\n SageMaker AI will by default base64 encode when capturing the data.
" + "smithy.api#documentation": "Configuration specifying how to treat different headers. If no headers are specified SageMaker AI will by default base64 encode when capturing the data.
" } } }, @@ -16191,7 +16163,7 @@ } }, "traits": { - "smithy.api#documentation": "The meta data of the Glue table which serves as data catalog for the\n OfflineStore.
The meta data of the Glue table which serves as data catalog for the OfflineStore.
A JSONPath expression used to select a portion of the input data to pass to\n the algorithm. Use the InputFilter parameter to exclude fields, such as an\n ID column, from the input. If you want SageMaker to pass the entire input dataset to the\n algorithm, accept the default value $.
Examples: \"$\", \"$[1:]\", \"$.features\"\n
A JSONPath expression used to select a portion of the input data to pass to the algorithm. Use the InputFilter parameter to exclude fields, such as an ID column, from the input. If you want SageMaker to pass the entire input dataset to the algorithm, accept the default value $.
Examples: \"$\", \"$[1:]\", \"$.features\"
A JSONPath expression used to select a portion of the joined dataset to save\n in the output file for a batch transform job. If you want SageMaker to store the entire input\n dataset in the output file, leave the default value, $. If you specify\n indexes that aren't within the dimension size of the joined dataset, you get an\n error.
Examples: \"$\", \"$[0,5:]\",\n \"$['id','SageMakerOutput']\"\n
A JSONPath expression used to select a portion of the joined dataset to save in the output file for a batch transform job. If you want SageMaker to store the entire input dataset in the output file, leave the default value, $. If you specify indexes that aren't within the dimension size of the joined dataset, you get an error.
Examples: \"$\", \"$[0,5:]\", \"$['id','SageMakerOutput']\"
Specifies the source of the data to join with the transformed data. The valid values\n are None and Input. The default value is None,\n which specifies not to join the input with the transformed data. If you want the batch\n transform job to join the original input data with the transformed data, set\n JoinSource to Input. You can specify\n OutputFilter as an additional filter to select a portion of the joined\n dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to\n the input JSON object in an attribute called SageMakerOutput. The joined\n result for JSON must be a key-value pair object. If the input is not a key-value pair\n object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored\n under the SageMakerInput key and the results are stored in\n SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with\n the input by appending each transformed row to the end of the input. The joined data has\n the original input data followed by the transformed data and the output is a CSV\n file.
\nFor information on how joining in applied, see Workflow for Associating Inferences with Input Records.
" + "smithy.api#documentation": "Specifies the source of the data to join with the transformed data. The valid values are None and Input. The default value is None, which specifies not to join the input with the transformed data. If you want the batch transform job to join the original input data with the transformed data, set JoinSource to Input. You can specify OutputFilter as an additional filter to select a portion of the joined dataset and store it in the output file.
For JSON or JSONLines objects, such as a JSON array, SageMaker adds the transformed data to the input JSON object in an attribute called SageMakerOutput. The joined result for JSON must be a key-value pair object. If the input is not a key-value pair object, SageMaker creates a new JSON file. In the new JSON file, and the input data is stored under the SageMakerInput key and the results are stored in SageMakerOutput.
For CSV data, SageMaker takes each row as a JSON array and joins the transformed data with the input by appending each transformed row to the end of the input. The joined data has the original input data followed by the transformed data and the output is a CSV file.
For information on how joining in applied, see Workflow for Associating Inferences with Input Records.
" } } }, "traits": { - "smithy.api#documentation": "The data structure used to specify the data to be used for inference in a batch\n transform job and to associate the data that is relevant to the prediction results in\n the output. The input filter provided allows you to exclude input data that is not\n needed for inference in a batch transform job. The output filter provided allows you to\n include input data relevant to interpreting the predictions in the output from the job.\n For more information, see Associate Prediction\n Results with their Corresponding Input Records.
" + "smithy.api#documentation": "The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records.
" } }, "com.amazonaws.sagemaker#DataQualityAppSpecification": { @@ -16281,13 +16253,13 @@ "RecordPreprocessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
" } }, "Environment": { @@ -16318,7 +16290,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
" } }, "com.amazonaws.sagemaker#DataQualityJobInput": { @@ -16335,7 +16307,7 @@ } }, "traits": { - "smithy.api#documentation": "The input for the data quality monitoring job. Currently endpoints are supported for\n input.
" + "smithy.api#documentation": "The input for the data quality monitoring job. Currently endpoints are supported for input.
" } }, "com.amazonaws.sagemaker#DataSource": { @@ -16397,24 +16369,24 @@ "LocalPath": { "target": "com.amazonaws.sagemaker#ProcessingLocalPath", "traits": { - "smithy.api#documentation": "The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a\n processing job. LocalPath is an absolute path to the input data. This is a\n required parameter when AppManaged is False (default).
The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
Whether the generated dataset is FullyReplicated or\n ShardedByS3Key (default).
Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
Whether to use File or Pipe input mode. In File\n (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic\n Block Store (Amazon EBS) volumes before starting your training algorithm. This is the\n most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from\n the source directly to your algorithm without using the EBS volume.
Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
Configuration for Dataset Definition inputs. The Dataset Definition input must specify\n exactly one of either AthenaDatasetDefinition or\n RedshiftDatasetDefinition types.
Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
Path to local storage location for metrics and tensors. Defaults to\n /opt/ml/output/tensors/.
Path to local storage location for metrics and tensors. Defaults to /opt/ml/output/tensors/.
Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about\n how to configure the CollectionConfiguration parameter, \n see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.\n
Configuration information for Amazon SageMaker Debugger tensor collections. To learn more about how to configure the CollectionConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and\n storage paths. To learn more about\n how to configure the DebugHookConfig parameter, \n see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for the Amazon SageMaker Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The name of the rule configuration. It must be unique relative to other rule\n configuration names.
", + "smithy.api#documentation": "The name of the rule configuration. It must be unique relative to other rule configuration names.
", "smithy.api#required": {} } }, "LocalPath": { "target": "com.amazonaws.sagemaker#DirectoryPath", "traits": { - "smithy.api#documentation": "Path to local storage location for output of rules. Defaults to\n /opt/ml/processing/output/rule/.
Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/.
Configuration information for SageMaker Debugger rules for debugging. To learn more about\n how to configure the DebugRuleConfiguration parameter, \n see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
The security group IDs for the Amazon VPC that the space uses for\n communication.
" + "smithy.api#documentation": "The security group IDs for the Amazon VPC that the space uses for communication.
" } }, "JupyterServerAppSettings": { @@ -16650,12 +16622,12 @@ "CustomFileSystemConfigs": { "target": "com.amazonaws.sagemaker#CustomFileSystemConfigs", "traits": { - "smithy.api#documentation": "The settings for assigning a custom file system to a domain. Permitted users can access\n this file system in Amazon SageMaker AI Studio.
" + "smithy.api#documentation": "The settings for assigning a custom file system to a domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" } } }, "traits": { - "smithy.api#documentation": "The default settings for shared spaces that users create in the domain.
\nSageMaker applies these settings only to shared spaces. It doesn't apply them to private\n spaces.
" + "smithy.api#documentation": "The default settings for shared spaces that users create in the domain.
SageMaker applies these settings only to shared spaces. It doesn't apply them to private spaces.
" } }, "com.amazonaws.sagemaker#DefaultSpaceStorageSettings": { @@ -16828,13 +16800,13 @@ "UserProfileName": { "target": "com.amazonaws.sagemaker#UserProfileName", "traits": { - "smithy.api#documentation": "The user profile name. If this value is not set, then SpaceName must be\n set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be\n set.
The name of the space. If this value is not set, then UserProfileName must be set.
Deletes an artifact. Either ArtifactArn or Source must be\n specified.
Deletes an artifact. Either ArtifactArn or Source must be specified.
Deletes the specified compilation job. This action deletes only the compilation job\n resource in Amazon SageMaker AI. It doesn't delete other resources that are related to\n that job, such as the model artifacts that the job creates, the compilation logs in\n CloudWatch, the compiled model, or the IAM role.
\nYou can delete a compilation job only if its current status is COMPLETED,\n FAILED, or STOPPED. If the job status is\n STARTING or INPROGRESS, stop the job, and then delete it\n after its status becomes STOPPED.
Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon SageMaker AI. It doesn't delete other resources that are related to that job, such as the model artifacts that the job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role.
You can delete a compilation job only if its current status is COMPLETED, FAILED, or STOPPED. If the job status is STARTING or INPROGRESS, stop the job, and then delete it after its status becomes STOPPED.
Used to delete a domain. If you onboarded with IAM mode, you will need to delete your\n domain to onboard again using IAM Identity Center. Use with caution. All of the members of the\n domain will lose access to their EFS volume, including data, notebooks, and other artifacts.\n
" + "smithy.api#documentation": "Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using IAM Identity Center. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
" } }, "com.amazonaws.sagemaker#DeleteDomainRequest": { @@ -17296,7 +17268,7 @@ "RetentionPolicy": { "target": "com.amazonaws.sagemaker#RetentionPolicy", "traits": { - "smithy.api#documentation": "The retention policy for this domain, which specifies whether resources will be retained\n after the Domain is deleted. By default, all resources are retained (not automatically\n deleted).
" + "smithy.api#documentation": "The retention policy for this domain, which specifies whether resources will be retained after the Domain is deleted. By default, all resources are retained (not automatically deleted).
" } } }, @@ -17318,7 +17290,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes an edge deployment plan if (and only if) all the stages in the plan are\n inactive or there are no stages in the plan.
" + "smithy.api#documentation": "Deletes an edge deployment plan if (and only if) all the stages in the plan are inactive or there are no stages in the plan.
" } }, "com.amazonaws.sagemaker#DeleteEdgeDeploymentPlanRequest": { @@ -17351,7 +17323,7 @@ } ], "traits": { - "smithy.api#documentation": "Delete a stage in an edge deployment plan if (and only if) the stage is\n inactive.
" + "smithy.api#documentation": "Delete a stage in an edge deployment plan if (and only if) the stage is inactive.
" } }, "com.amazonaws.sagemaker#DeleteEdgeDeploymentStageRequest": { @@ -17387,7 +17359,7 @@ "target": "smithy.api#Unit" }, "traits": { - "smithy.api#documentation": "Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the\n endpoint was created.
\nSageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't\n need to use the RevokeGrant API call.
\nWhen you delete your endpoint, SageMaker asynchronously deletes associated endpoint\n resources such as KMS key grants. You might still see these resources in your account\n for a few minutes after deleting your endpoint. Do not delete or revoke the permissions\n for your \n ExecutionRoleArn\n , otherwise SageMaker cannot delete these\n resources.
Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
Deletes an endpoint configuration. The DeleteEndpointConfig API\n deletes only the specified configuration. It does not delete endpoints created using the\n configuration.
You must not delete an EndpointConfig in use by an endpoint that is\n live or while the UpdateEndpoint or CreateEndpoint operations\n are being performed on the endpoint. If you delete the EndpointConfig of an\n endpoint that is active or being created or updated you may lose visibility into the\n instance type the endpoint is using. The endpoint must be deleted in order to stop\n incurring charges.
Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
Deletes an SageMaker experiment. All trials associated with the experiment must be deleted\n first. Use the ListTrials API to get a list of the trials associated with\n the experiment.
" + "smithy.api#documentation": "Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
" } }, "com.amazonaws.sagemaker#DeleteExperimentRequest": { @@ -17495,7 +17467,7 @@ } ], "traits": { - "smithy.api#documentation": "Delete the FeatureGroup and any data that was written to the\n OnlineStore of the FeatureGroup. Data cannot be accessed from\n the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your\n OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore\n FeatureGroup with the InMemory\n StorageType.
Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
Note that it can take approximately 10-15 minutes to delete an OnlineStore FeatureGroup with the InMemory StorageType.
The name of the FeatureGroup you want to delete. The name must be unique\n within an Amazon Web Services Region in an Amazon Web Services account.
The name of the FeatureGroup you want to delete. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
Use this operation to delete a human task user interface (worker task template).
\n\n To see a list of human task user interfaces\n (work task templates) in your account, use ListHumanTaskUis.\n When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Use this operation to delete a human task user interface (worker task template).
To see a list of human task user interfaces (work task templates) in your account, use ListHumanTaskUis. When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob\n API deletes only the tuning job entry that was created in SageMaker when you called the\n CreateHyperParameterTuningJob API. It does not delete training jobs,\n artifacts, or the IAM role that you specified when creating the model.
Deletes a hyperparameter tuning job. The DeleteHyperParameterTuningJob API deletes only the tuning job entry that was created in SageMaker when you called the CreateHyperParameterTuningJob API. It does not delete training jobs, artifacts, or the IAM role that you specified when creating the model.
Deletes a SageMaker AI image and all versions of the image. The container images aren't\n deleted.
" + "smithy.api#documentation": "Deletes a SageMaker AI image and all versions of the image. The container images aren't deleted.
" } }, "com.amazonaws.sagemaker#DeleteImageRequest": { @@ -17830,7 +17802,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes a version of a SageMaker AI image. The container image the version represents isn't\n deleted.
" + "smithy.api#documentation": "Deletes a version of a SageMaker AI image. The container image the version represents isn't deleted.
" } }, "com.amazonaws.sagemaker#DeleteImageVersionRequest": { @@ -17913,7 +17885,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes an inference experiment.
\n\n This operation does not delete your endpoint, variants, or any underlying resources. This operation only\n deletes the metadata of your experiment.\n
\nDeletes an inference experiment.
This operation does not delete your endpoint, variants, or any underlying resources. This operation only deletes the metadata of your experiment.
A TrackingServerArn object, the ARN of the tracking server that is deleted if\n successfully found.
A TrackingServerArn object, the ARN of the tracking server that is deleted if successfully found.
Deletes a model. The DeleteModel API deletes only the model entry that\n was created in SageMaker when you called the CreateModel API. It does not delete\n model artifacts, inference code, or the IAM role that you specified when creating the\n model.
Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
Deletes a model package.
\nA model package is used to create SageMaker models or list on Amazon Web Services\n Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services\n Marketplace to create models in SageMaker.
" + "smithy.api#documentation": "Deletes a model package.
A model package is used to create SageMaker models or list on Amazon Web Services Marketplace. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
" } }, "com.amazonaws.sagemaker#DeleteModelPackageGroup": { @@ -18210,7 +18182,7 @@ "target": "com.amazonaws.sagemaker#VersionedArnOrName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package to delete.
\nWhen you specify a name, the name must have 1 to 63 characters. Valid characters are\n a-z, A-Z, 0-9, and - (hyphen).
", + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package to delete.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
", "smithy.api#required": {} } } @@ -18266,7 +18238,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes a monitoring schedule. Also stops the schedule had not already been stopped.\n This does not delete the job execution history of the monitoring schedule.
" + "smithy.api#documentation": "Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.
" } }, "com.amazonaws.sagemaker#DeleteMonitoringScheduleRequest": { @@ -18294,7 +18266,7 @@ "target": "smithy.api#Unit" }, "traits": { - "smithy.api#documentation": " Deletes an SageMaker AI notebook instance. Before you can delete a notebook\n instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker AI removes the ML compute instance, and deletes the ML storage volume and the\n network interface associated with the notebook instance.
\n Deletes an SageMaker AI notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API.
When you delete a notebook instance, you lose all of your data. SageMaker AI removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.
Deletes a pipeline if there are no running instances of the pipeline. To delete a\n pipeline, you must stop all running instances of the pipeline using the\n StopPipelineExecution API. When you delete a pipeline, all instances of the\n pipeline are deleted.
Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the StopPipelineExecution API. When you delete a pipeline, all instances of the pipeline are deleted.
A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than one time.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -18584,7 +18556,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes the Amazon SageMaker AI Studio Lifecycle Configuration. In order to delete the\n Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You\n must also remove the Lifecycle Configuration from UserSettings in all Domains and\n UserProfiles.
" + "smithy.api#documentation": "Deletes the Amazon SageMaker AI Studio Lifecycle Configuration. In order to delete the Lifecycle Configuration, there must be no running apps using the Lifecycle Configuration. You must also remove the Lifecycle Configuration from UserSettings in all Domains and UserProfiles.
" } }, "com.amazonaws.sagemaker#DeleteStudioLifecycleConfigRequest": { @@ -18612,7 +18584,7 @@ "target": "com.amazonaws.sagemaker#DeleteTagsOutput" }, "traits": { - "smithy.api#documentation": "Deletes the specified tags from an SageMaker resource.
\nTo list a resource's tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the\n deleted tags are not removed from training jobs that the hyperparameter tuning job\n launched before you called this API.
\nWhen you call this API to delete tags from a SageMaker Domain or User Profile, the\n deleted tags are not removed from Apps that the SageMaker Domain or User Profile\n launched before you called this API.
\nDeletes the specified tags from an SageMaker resource.
To list a resource's tags, use the ListTags API.
When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.
When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.
The Amazon Resource Name (ARN) of the resource whose tags you want to\n delete.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
", "smithy.api#required": {} } }, @@ -18660,7 +18632,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes the specified trial. All trial components that make up the trial must be deleted\n first. Use the DescribeTrialComponent API to get the list of trial\n components.
" + "smithy.api#documentation": "Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.
" } }, "com.amazonaws.sagemaker#DeleteTrialComponent": { @@ -18677,7 +18649,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes the specified trial component. A trial component must be disassociated from all\n trials before the trial component can be deleted. To disassociate a trial component from a\n trial, call the DisassociateTrialComponent API.
" + "smithy.api#documentation": "Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
" } }, "com.amazonaws.sagemaker#DeleteTrialComponentRequest": { @@ -18757,7 +18729,7 @@ } ], "traits": { - "smithy.api#documentation": "Deletes a user profile. When a user profile is deleted, the user loses access to their EFS\n volume, including data, notebooks, and other artifacts.
" + "smithy.api#documentation": "Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.
" } }, "com.amazonaws.sagemaker#DeleteUserProfileRequest": { @@ -18793,7 +18765,7 @@ "target": "com.amazonaws.sagemaker#DeleteWorkforceResponse" }, "traits": { - "smithy.api#documentation": "Use this operation to delete a workforce.
\nIf you want to create a new workforce in an Amazon Web Services Region where\n a workforce already exists, use this operation to delete the \n existing workforce and then use CreateWorkforce\n to create a new workforce.
\nIf a private workforce contains one or more work teams, you must use \n the DeleteWorkteam\n operation to delete all work teams before you delete the workforce.\n If you try to delete a workforce that contains one or more work teams,\n you will receive a ResourceInUse error.
Use this operation to delete a workforce.
If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use this operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
If a private workforce contains one or more work teams, you must use the DeleteWorkteam operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will receive a ResourceInUse error.
Returns true if the work team was successfully deleted; otherwise,\n returns false.
Returns true if the work team was successfully deleted; otherwise, returns false.
The specific digest path of the image hosted in this\n ProductionVariant.
The specific digest path of the image hosted in this ProductionVariant.
The date and time when the image path for the model resolved to the\n ResolvedImage\n
The date and time when the image path for the model resolved to the ResolvedImage
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
\nIf you used the registry/repository[:tag] form to specify the image path\n of the primary container when you created the model hosted in this\n ProductionVariant, the path resolves to a path of the form\n registry/repository[@digest]. A digest is a hash value that identifies\n a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.
Update policy for a blue/green deployment. If this update policy is specified, SageMaker\n creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips\n traffic to the new fleet according to the specified traffic routing configuration. Only\n one update policy should be used in the deployment configuration. If no update policy is\n specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting\n by default.
" + "smithy.api#documentation": "Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.
" } }, "RollingUpdatePolicy": { @@ -18938,12 +18910,12 @@ "AutoRollbackConfiguration": { "target": "com.amazonaws.sagemaker#AutoRollbackConfig", "traits": { - "smithy.api#documentation": "Automatic rollback configuration for handling endpoint deployment failures and\n recovery.
" + "smithy.api#documentation": "Automatic rollback configuration for handling endpoint deployment failures and recovery.
" } } }, "traits": { - "smithy.api#documentation": "The deployment configuration for an endpoint, which contains the desired deployment\n strategy and rollback configurations.
" + "smithy.api#documentation": "The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
" } }, "com.amazonaws.sagemaker#DeploymentConfiguration": { @@ -18979,7 +18951,7 @@ "target": "com.amazonaws.sagemaker#RecommendationStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker\n is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS,\n retry your API call after a few seconds to get a COMPLETED deployment recommendation.
Status of the deployment recommendation. The status NOT_APPLICABLE means that SageMaker is unable to provide a default recommendation for the model using the information provided. If the deployment status is IN_PROGRESS, retry your API call after a few seconds to get a COMPLETED deployment recommendation.
A set of recommended deployment configurations for the model. To get more advanced recommendations, see\n CreateInferenceRecommendationsJob\n to create an inference recommendation job.
" + "smithy.api#documentation": "A set of recommended deployment configurations for the model. To get more advanced recommendations, see CreateInferenceRecommendationsJob to create an inference recommendation job.
" } }, "com.amazonaws.sagemaker#DeploymentStage": { @@ -19126,7 +19098,7 @@ "DerivedDataInputConfig": { "target": "com.amazonaws.sagemaker#DataInputConfig", "traits": { - "smithy.api#documentation": "The data input configuration that SageMaker Neo automatically derived for the model.\n When SageMaker Neo derives this information, you don't need to specify the data input\n configuration when you create a compilation job.
" + "smithy.api#documentation": "The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker Neo derives this information, you don't need to specify the data input configuration when you create a compilation job.
" } } }, @@ -19322,7 +19294,7 @@ "ValidationSpecification": { "target": "com.amazonaws.sagemaker#AlgorithmValidationSpecification", "traits": { - "smithy.api#documentation": "Details about configurations for one or more training jobs that SageMaker runs to test the\n algorithm.
" + "smithy.api#documentation": "Details about configurations for one or more training jobs that SageMaker runs to test the algorithm.
" } }, "AlgorithmStatus": { @@ -19350,7 +19322,7 @@ "CertifyForMarketplace": { "target": "com.amazonaws.sagemaker#CertifyForMarketplace", "traits": { - "smithy.api#documentation": "Whether the algorithm is certified to be listed in Amazon Web Services\n Marketplace.
" + "smithy.api#documentation": "Whether the algorithm is certified to be listed in Amazon Web Services Marketplace.
" } } }, @@ -19472,7 +19444,7 @@ "UserProfileName": { "target": "com.amazonaws.sagemaker#UserProfileName", "traits": { - "smithy.api#documentation": "The user profile name. If this value is not set, then SpaceName must be\n set.
The user profile name. If this value is not set, then SpaceName must be set.
The name of the space. If this value is not set, then UserProfileName must be\n set.
The name of the space. If this value is not set, then UserProfileName must be set.
The timestamp of the last user's activity. LastUserActivityTimestamp is also\n updated when SageMaker AI performs health checks without user activity. As a result, this\n value is set to the same value as LastHealthCheckTimestamp.
The timestamp of the last user's activity. LastUserActivityTimestamp is also updated when SageMaker AI performs health checks without user activity. As a result, this value is set to the same value as LastHealthCheckTimestamp.
The creation time of the application.
\nAfter an application has been shut down for 24 hours, SageMaker AI deletes all\n metadata for the application. To be considered an update and retain application metadata,\n applications must be restarted within 24 hours after the previous application has been shut\n down. After this time window, creation of an application is considered a new application\n rather than an update of the previous application.
\nThe creation time of the application.
After an application has been shut down for 24 hours, SageMaker AI deletes all metadata for the application. To be considered an update and retain application metadata, applications must be restarted within 24 hours after the previous application has been shut down. After this time window, creation of an application is considered a new application rather than an update of the previous application.
The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image\n created on the instance.
" + "smithy.api#documentation": "The instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
" } }, "BuiltInLifecycleConfigArn": { @@ -19706,7 +19678,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns information about an AutoML job created by calling CreateAutoMLJob.
\nAutoML jobs created by calling CreateAutoMLJobV2 cannot be described by\n DescribeAutoMLJob.
Returns information about an AutoML job created by calling CreateAutoMLJob.
AutoML jobs created by calling CreateAutoMLJobV2 cannot be described by DescribeAutoMLJob.
The ARN of the IAM role that has read permission to the input data\n location and write permission to the output data location in Amazon S3.
", + "smithy.api#documentation": "The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -19823,7 +19795,7 @@ "BestCandidate": { "target": "com.amazonaws.sagemaker#AutoMLCandidate", "traits": { - "smithy.api#documentation": "The best model candidate selected by SageMaker AI Autopilot using both the best\n objective metric and lowest InferenceLatency for\n an experiment.
" + "smithy.api#documentation": "The best model candidate selected by SageMaker AI Autopilot using both the best objective metric and lowest InferenceLatency for an experiment.
" } }, "AutoMLJobStatus": { @@ -19845,25 +19817,25 @@ "GenerateCandidateDefinitionsOnly": { "target": "com.amazonaws.sagemaker#GenerateCandidateDefinitionsOnly", "traits": { - "smithy.api#documentation": "Indicates whether the output for an AutoML job generates candidate definitions\n only.
" + "smithy.api#documentation": "Indicates whether the output for an AutoML job generates candidate definitions only.
" } }, "AutoMLJobArtifacts": { "target": "com.amazonaws.sagemaker#AutoMLJobArtifacts", "traits": { - "smithy.api#documentation": "Returns information on the job's artifacts found in\n AutoMLJobArtifacts.
Returns information on the job's artifacts found in AutoMLJobArtifacts.
Contains ProblemType, AutoMLJobObjective, and\n CompletionCriteria. If you do not provide these values, they are\n inferred.
Contains ProblemType, AutoMLJobObjective, and CompletionCriteria. If you do not provide these values, they are inferred.
Indicates whether the model was deployed automatically to an endpoint and the name of\n that endpoint if deployed automatically.
" + "smithy.api#documentation": "Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
" } }, "ModelDeployResult": { @@ -19891,7 +19863,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns information about an AutoML job created by calling CreateAutoMLJobV2\n or CreateAutoMLJob.
" + "smithy.api#documentation": "Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob.
" } }, "com.amazonaws.sagemaker#DescribeAutoMLJobV2Request": { @@ -19949,7 +19921,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ARN of the IAM role that has read permission to the input data\n location and write permission to the output data location in Amazon S3.
", + "smithy.api#documentation": "The ARN of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -20008,7 +19980,7 @@ "BestCandidate": { "target": "com.amazonaws.sagemaker#AutoMLCandidate", "traits": { - "smithy.api#documentation": "Information about the candidate produced by an AutoML training job V2, including its\n status, steps, and other properties.
" + "smithy.api#documentation": "Information about the candidate produced by an AutoML training job V2, including its status, steps, and other properties.
" } }, "AutoMLJobStatus": { @@ -20039,7 +20011,7 @@ "ModelDeployConfig": { "target": "com.amazonaws.sagemaker#ModelDeployConfig", "traits": { - "smithy.api#documentation": "Indicates whether the model was deployed automatically to an endpoint and the name of\n that endpoint if deployed automatically.
" + "smithy.api#documentation": "Indicates whether the model was deployed automatically to an endpoint and the name of that endpoint if deployed automatically.
" } }, "ModelDeployResult": { @@ -20051,13 +20023,13 @@ "DataSplitConfig": { "target": "com.amazonaws.sagemaker#AutoMLDataSplitConfig", "traits": { - "smithy.api#documentation": "Returns the configuration settings of how the data are split into train and validation\n datasets.
" + "smithy.api#documentation": "Returns the configuration settings of how the data are split into train and validation datasets.
" } }, "SecurityConfig": { "target": "com.amazonaws.sagemaker#AutoMLSecurityConfig", "traits": { - "smithy.api#documentation": "Returns the security configuration for traffic encryption or Amazon VPC\n settings.
" + "smithy.api#documentation": "Returns the security configuration for traffic encryption or Amazon VPC settings.
" } }, "AutoMLComputeConfig": { @@ -20102,7 +20074,7 @@ } ], "traits": { - "smithy.api#documentation": "Retrieves information of a node (also called a instance\n interchangeably) of a SageMaker HyperPod cluster.
" + "smithy.api#documentation": "Retrieves information of a node (also called a instance interchangeably) of a SageMaker HyperPod cluster.
" } }, "com.amazonaws.sagemaker#DescribeClusterNodeRequest": { @@ -20240,7 +20212,7 @@ } ], "traits": { - "smithy.api#documentation": "Description of the cluster policy. This policy is used for task prioritization and\n fair-share allocation. This helps prioritize critical workloads and distributes\n idle compute across entities.
" + "smithy.api#documentation": "Description of the cluster policy. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
" } }, "com.amazonaws.sagemaker#DescribeClusterSchedulerConfigRequest": { @@ -20323,7 +20295,7 @@ "SchedulerConfig": { "target": "com.amazonaws.sagemaker#SchedulerConfig", "traits": { - "smithy.api#documentation": "Cluster policy configuration. This policy is used for task prioritization and fair-share\n allocation. This helps prioritize critical workloads and distributes idle compute\n across entities.
" + "smithy.api#documentation": "Cluster policy configuration. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
" } }, "Description": { @@ -20423,7 +20395,7 @@ "GitConfig": { "target": "com.amazonaws.sagemaker#GitConfig", "traits": { - "smithy.api#documentation": "Configuration details about the repository, including the URL where the repository is\n located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the\n repository.
" + "smithy.api#documentation": "Configuration details about the repository, including the URL where the repository is located, the default branch, and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
" } } }, @@ -20445,7 +20417,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns information about a model compilation job.
\nTo create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation\n jobs, use ListCompilationJobs.
" + "smithy.api#documentation": "Returns information about a model compilation job.
To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
" } }, "com.amazonaws.sagemaker#DescribeCompilationJobRequest": { @@ -20494,33 +20466,33 @@ "CompilationStartTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "The time when the model compilation job started the CompilationJob\n instances.
You are billed for the time between this timestamp and the timestamp in the\n CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later\n than this time. That's because it takes time to download the compilation job, which\n depends on the size of the compilation job container.
The time when the model compilation job started the CompilationJob instances.
You are billed for the time between this timestamp and the timestamp in the CompilationEndTime field. In Amazon CloudWatch Logs, the start time might be later than this time. That's because it takes time to download the compilation job, which depends on the size of the compilation job container.
The time when the model compilation job on a compilation job instance ended. For a\n successful or stopped job, this is when the job's model artifacts have finished\n uploading. For a failed job, this is when Amazon SageMaker AI detected that the job failed.
" + "smithy.api#documentation": "The time when the model compilation job on a compilation job instance ended. For a successful or stopped job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker AI detected that the job failed.
" } }, "StoppingCondition": { "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a limit to how long a model compilation job can run. When the job reaches\n the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training\n costs.
", + "smithy.api#documentation": "Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
", "smithy.api#required": {} } }, "InferenceImage": { "target": "com.amazonaws.sagemaker#InferenceImage", "traits": { - "smithy.api#documentation": "The inference image to use when compiling a model. Specify an image only if the target\n device is a cloud instance.
" + "smithy.api#documentation": "The inference image to use when compiling a model. Specify an image only if the target device is a cloud instance.
" } }, "ModelPackageVersionArn": { "target": "com.amazonaws.sagemaker#ModelPackageArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the versioned model package that was \n provided to SageMaker Neo when you initiated a compilation job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when you initiated a compilation job.
" } }, "CreationTime": { @@ -20535,7 +20507,7 @@ "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The time that the status\n of\n the model compilation job was last modified.
", + "smithy.api#documentation": "The time that the status of the model compilation job was last modified.
", "smithy.api#required": {} } }, @@ -20551,21 +20523,21 @@ "target": "com.amazonaws.sagemaker#ModelArtifacts", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Information about the location in Amazon S3 that has been configured for storing the model\n artifacts used in the compilation job.
", + "smithy.api#documentation": "Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.
", "smithy.api#required": {} } }, "ModelDigests": { "target": "com.amazonaws.sagemaker#ModelDigests", "traits": { - "smithy.api#documentation": "Provides a BLAKE2 hash value that identifies the compiled model artifacts in\n Amazon S3.
" + "smithy.api#documentation": "Provides a BLAKE2 hash value that identifies the compiled model artifacts in Amazon S3.
" } }, "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model\n compilation job.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model compilation job.
", "smithy.api#required": {} } }, @@ -20573,7 +20545,7 @@ "target": "com.amazonaws.sagemaker#InputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Information about the location in Amazon S3 of the input model artifacts, the name and\n shape of the expected data inputs, and the framework in which the model was\n trained.
", + "smithy.api#documentation": "Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
", "smithy.api#required": {} } }, @@ -20581,14 +20553,14 @@ "target": "com.amazonaws.sagemaker#OutputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Information about the output location for the compiled model and the target device\n that the model runs on.
", + "smithy.api#documentation": "Information about the output location for the compiled model and the target device that the model runs on.
", "smithy.api#required": {} } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#NeoVpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your compilation job\n to connect to. Control access to your models by configuring the VPC. For more\n information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
" } }, "DerivedInformation": { @@ -20705,7 +20677,7 @@ "ComputeQuotaConfig": { "target": "com.amazonaws.sagemaker#ComputeQuotaConfig", "traits": { - "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing\n option, and the setting to preempt low priority tasks.
" + "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
" } }, "ComputeQuotaTarget": { @@ -20719,7 +20691,7 @@ "ActivationState": { "target": "com.amazonaws.sagemaker#ActivationState", "traits": { - "smithy.api#documentation": "The state of the compute allocation being described. Use to enable or disable compute\n allocation.
\nDefault is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
The list of inputs for the data quality monitoring job. Currently endpoints are\n supported.
", + "smithy.api#documentation": "The list of inputs for the data quality monitoring job. Currently endpoints are supported.
", "smithy.api#required": {} } }, @@ -20954,7 +20926,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -21261,7 +21233,7 @@ "SingleSignOnApplicationArn": { "target": "com.amazonaws.sagemaker#SingleSignOnApplicationArn", "traits": { - "smithy.api#documentation": "The ARN of the application managed by SageMaker AI in IAM Identity Center. This value\n is only returned for domains created after October 1, 2023.
" + "smithy.api#documentation": "The ARN of the application managed by SageMaker AI in IAM Identity Center. This value is only returned for domains created after October 1, 2023.
" } }, "Status": { @@ -21291,7 +21263,7 @@ "SecurityGroupIdForDomainBoundary": { "target": "com.amazonaws.sagemaker#SecurityGroupId", "traits": { - "smithy.api#documentation": "The ID of the security group that authorizes traffic between the\n RSessionGateway apps and the RStudioServerPro app.
The ID of the security group that authorizes traffic between the RSessionGateway apps and the RStudioServerPro app.
Settings which are applied to UserProfiles in this domain if settings are not explicitly\n specified in a given UserProfile.
" + "smithy.api#documentation": "Settings which are applied to UserProfiles in this domain if settings are not explicitly specified in a given UserProfile.
" } }, "DomainSettings": { @@ -21315,7 +21287,7 @@ "AppNetworkAccessType": { "target": "com.amazonaws.sagemaker#AppNetworkAccessType", "traits": { - "smithy.api#documentation": "Specifies the VPC used for non-EFS traffic. The default value is\n PublicInternetOnly.
\n PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
\n VpcOnly - All traffic is through the specified VPC and subnets
Specifies the VPC used for non-EFS traffic. The default value is PublicInternetOnly.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access
VpcOnly - All traffic is through the specified VPC and subnets
The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to\n the domain.
" + "smithy.api#documentation": "The Amazon Web Services KMS customer managed key used to encrypt the EFS volume attached to the domain.
" } }, "AppSecurityGroupManagement": { "target": "com.amazonaws.sagemaker#AppSecurityGroupManagement", "traits": { - "smithy.api#documentation": "The entity that creates and manages the required security groups for inter-app\n communication in VPCOnly mode. Required when\n CreateDomain.AppNetworkAccessType is VPCOnly and\n DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is\n provided.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided.
If the edge deployment plan has enough stages to require tokening, then this is the\n response from the last list of stages returned.
" + "smithy.api#documentation": "If the edge deployment plan has enough stages to require tokening, then this is the response from the last list of stages returned.
" } }, "MaxResults": { @@ -21576,7 +21548,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact Neo.
" } }, "OutputConfig": { @@ -21671,7 +21643,8 @@ } } ], - "minDelay": 30 + "minDelay": 30, + "maxDelay": 1800 }, "EndpointInService": { "acceptors": [ @@ -21702,7 +21675,8 @@ } } ], - "minDelay": 30 + "minDelay": 30, + "maxDelay": 3600 } } } @@ -21716,7 +21690,7 @@ "target": "com.amazonaws.sagemaker#DescribeEndpointConfigOutput" }, "traits": { - "smithy.api#documentation": "Returns the description of an endpoint configuration created using the\n CreateEndpointConfig API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
An array of ProductionVariant objects, one for each model that you\n want to host at this endpoint.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint.
Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML\n storage volume attached to the instance.
" + "smithy.api#documentation": "Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML storage volume attached to the instance.
" } }, "CreationTime": { @@ -21782,7 +21756,7 @@ "AsyncInferenceConfig": { "target": "com.amazonaws.sagemaker#AsyncInferenceConfig", "traits": { - "smithy.api#documentation": "Returns the description of an endpoint configuration created using the \n CreateEndpointConfig\n API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
An array of ProductionVariant objects, one for each model that you want\n to host at this endpoint in shadow mode with production traffic replicated from the\n model specified on ProductionVariants.
An array of ProductionVariant objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
The Amazon Resource Name (ARN) of the IAM role that you assigned to the\n endpoint configuration.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that you assigned to the endpoint configuration.
" } }, "VpcConfig": { @@ -21809,7 +21783,7 @@ "EnableNetworkIsolation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Indicates whether all model containers deployed to the endpoint are isolated. If they\n are, no inbound or outbound network calls can be made to or from the model\n containers.
" + "smithy.api#documentation": "Indicates whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.
" } } }, @@ -21861,7 +21835,7 @@ "ProductionVariants": { "target": "com.amazonaws.sagemaker#ProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "An array of ProductionVariantSummary objects, one for each model hosted behind this\n endpoint.
" + "smithy.api#documentation": "An array of ProductionVariantSummary objects, one for each model hosted behind this endpoint.
" } }, "DataCaptureConfig": { @@ -21871,14 +21845,14 @@ "target": "com.amazonaws.sagemaker#EndpointStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The status of the endpoint.
\n\n OutOfService: Endpoint is not available to take incoming\n requests.
\n Creating: CreateEndpoint is executing.
\n Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
\n SystemUpdating: Endpoint is undergoing maintenance and cannot be\n updated or deleted or re-scaled until it has completed. This maintenance\n operation does not change any customer-specified values such as VPC config, KMS\n encryption, model, instance type, or instance count.
\n RollingBack: Endpoint fails to scale up or down or change its\n variant weight and is in the process of rolling back to its previous\n configuration. Once the rollback completes, endpoint returns to an\n InService status. This transitional status only applies to an\n endpoint that has autoscaling enabled and is undergoing variant weight or\n capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called\n explicitly.
\n InService: Endpoint is available to process incoming\n requests.
\n Deleting: DeleteEndpoint is executing.
\n Failed: Endpoint could not be created, updated, or re-scaled. Use\n the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a\n failed endpoint.
\n UpdateRollbackFailed: Both the rolling deployment and\n auto-rollback failed. Your endpoint is in service with a mix of the old and new\n endpoint configurations. For information about how to remedy this issue and\n restore the endpoint's status to InService, see Rolling\n Deployments.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use the FailureReason value returned by DescribeEndpoint for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
UpdateRollbackFailed: Both the rolling deployment and auto-rollback failed. Your endpoint is in service with a mix of the old and new endpoint configurations. For information about how to remedy this issue and restore the endpoint's status to InService, see Rolling Deployments.
If the status of the endpoint is Failed, the reason why it failed.\n
If the status of the endpoint is Failed, the reason why it failed.
Returns the description of an endpoint configuration created using the \n CreateEndpointConfig\n API.
Returns the description of an endpoint configuration created using the CreateEndpointConfig API.
Returns the summary of an in-progress deployment. This field is only returned when the\n endpoint is creating or updating with a new endpoint configuration.
" + "smithy.api#documentation": "Returns the summary of an in-progress deployment. This field is only returned when the endpoint is creating or updating with a new endpoint configuration.
" } }, "ExplainerConfig": { @@ -21924,7 +21898,7 @@ "ShadowProductionVariants": { "target": "com.amazonaws.sagemaker#ProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "An array of ProductionVariantSummary objects, one for each model that you want to host\n at this endpoint in shadow mode with production traffic replicated from the model\n specified on ProductionVariants.
An array of ProductionVariantSummary objects, one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.
The name of the experiment as displayed. If DisplayName isn't specified,\n ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
Use this operation to describe a FeatureGroup. The response includes\n information on the creation time, FeatureGroup name, the unique identifier for\n each FeatureGroup, and more.
Use this operation to describe a FeatureGroup. The response includes information on the creation time, FeatureGroup name, the unique identifier for each FeatureGroup, and more.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want\n described.
The name or Amazon Resource Name (ARN) of the FeatureGroup you want described.
A token to resume pagination of the list of Features\n (FeatureDefinitions). 2,500 Features are returned by\n default.
A token to resume pagination of the list of Features (FeatureDefinitions). 2,500 Features are returned by default.
The name of the Feature used for RecordIdentifier, whose value\n uniquely identifies a record stored in the feature store.
The name of the Feature used for RecordIdentifier, whose value uniquely identifies a record stored in the feature store.
The name of the feature that stores the EventTime of a Record in a\n FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds\n to the creation or update of a Record in a FeatureGroup. All\n Records in the FeatureGroup have a corresponding\n EventTime.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
An EventTime is a point in time when a new event occurs that corresponds to the creation or update of a Record in a FeatureGroup. All Records in the FeatureGroup have a corresponding EventTime.
A list of the Features in the FeatureGroup. Each feature is\n defined by a FeatureName and FeatureType.
A list of the Features in the FeatureGroup. Each feature is defined by a FeatureName and FeatureType.
The configuration of the offline store. It includes the following configurations:
\nAmazon S3 location of the offline store.
\nConfiguration of the Glue data catalog.
\nTable format of the offline store.
\nOption to disable the automatic creation of a Glue table for the offline\n store.
\nEncryption configuration.
\nThe configuration of the offline store. It includes the following configurations:
Amazon S3 location of the offline store.
Configuration of the Glue data catalog.
Table format of the offline store.
Option to disable the automatic creation of a Glue table for the offline store.
Encryption configuration.
The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the\n OfflineStore if an OfflineStoreConfig is provided.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM execution role used to persist data into the OfflineStore if an OfflineStoreConfig is provided.
" } }, "FeatureGroupStatus": { @@ -22153,7 +22127,7 @@ "OfflineStoreStatus": { "target": "com.amazonaws.sagemaker#OfflineStoreStatus", "traits": { - "smithy.api#documentation": "The status of the OfflineStore. Notifies you if replicating data into the\n OfflineStore has failed. Returns either: Active or\n Blocked\n
The status of the OfflineStore. Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked
The reason that the FeatureGroup failed to be replicated in the\n OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the\n OfflineStore.
The FeatureGroup could not be deleted from the\n OfflineStore.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure can occur because:
The FeatureGroup could not be created in the OfflineStore.
The FeatureGroup could not be deleted from the OfflineStore.
A token to resume pagination of the list of Features\n (FeatureDefinitions).
A token to resume pagination of the list of Features (FeatureDefinitions).
The name or Amazon Resource Name (ARN) of the feature group containing the\n feature.
", + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the feature group containing the feature.
", "smithy.api#required": {} } }, @@ -22281,7 +22255,7 @@ "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A timestamp indicating when the metadata for the feature group was modified. For\n example, if you add a parameter describing the feature, the timestamp changes to reflect\n the last time you
", + "smithy.api#documentation": "A timestamp indicating when the metadata for the feature group was modified. For example, if you add a parameter describing the feature, the timestamp changes to reflect the last time you
", "smithy.api#required": {} } }, @@ -22373,7 +22347,7 @@ "HumanLoopRequestSource": { "target": "com.amazonaws.sagemaker#HumanLoopRequestSource", "traits": { - "smithy.api#documentation": "Container for configuring the source of human task requests. Used to specify if\n Amazon Rekognition or Amazon Textract is used as an integration source.
" + "smithy.api#documentation": "Container for configuring the source of human task requests. Used to specify if Amazon Rekognition or Amazon Textract is used as an integration source.
" } }, "HumanLoopActivationConfig": { @@ -22753,7 +22727,7 @@ "target": "com.amazonaws.sagemaker#HumanTaskUiName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the human task user interface \n (worker task template) you want information about.
", + "smithy.api#documentation": "The name of the human task user interface (worker task template) you want information about.
", "smithy.api#required": {} } } @@ -22821,7 +22795,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns a description of a hyperparameter tuning job, depending on the fields\n selected. These fields can include the name, Amazon Resource Name (ARN), job status of\n your tuning job and more.
" + "smithy.api#documentation": "Returns a description of a hyperparameter tuning job, depending on the fields selected. These fields can include the name, Amazon Resource Name (ARN), job status of your tuning job and more.
" } }, "com.amazonaws.sagemaker#DescribeHyperParameterTuningJobRequest": { @@ -22863,20 +22837,20 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The HyperParameterTuningJobConfig object that specifies the configuration of\n the tuning job.
", + "smithy.api#documentation": "The HyperParameterTuningJobConfig object that specifies the configuration of the tuning job.
", "smithy.api#required": {} } }, "TrainingJobDefinition": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobDefinition", "traits": { - "smithy.api#documentation": "The HyperParameterTrainingJobDefinition object that specifies the definition of\n the training jobs that this tuning job launches.
" + "smithy.api#documentation": "The HyperParameterTrainingJobDefinition object that specifies the definition of the training jobs that this tuning job launches.
" } }, "TrainingJobDefinitions": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobDefinitions", "traits": { - "smithy.api#documentation": "A list of the HyperParameterTrainingJobDefinition objects launched for this tuning\n job.
" + "smithy.api#documentation": "A list of the HyperParameterTrainingJobDefinition objects launched for this tuning job.
" } }, "HyperParameterTuningJobStatus": { @@ -22911,7 +22885,7 @@ "target": "com.amazonaws.sagemaker#TrainingJobStatusCounters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The TrainingJobStatusCounters object that specifies the number of training\n jobs, categorized by status, that this tuning job launched.
", + "smithy.api#documentation": "The TrainingJobStatusCounters object that specifies the number of training jobs, categorized by status, that this tuning job launched.
", "smithy.api#required": {} } }, @@ -22919,26 +22893,26 @@ "target": "com.amazonaws.sagemaker#ObjectiveStatusCounters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ObjectiveStatusCounters object that specifies the number of training jobs,\n categorized by the status of their final objective metric, that this tuning job\n launched.
", + "smithy.api#documentation": "The ObjectiveStatusCounters object that specifies the number of training jobs, categorized by the status of their final objective metric, that this tuning job launched.
", "smithy.api#required": {} } }, "BestTrainingJob": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobSummary", "traits": { - "smithy.api#documentation": "A TrainingJobSummary object that describes the training job that completed\n with the best current HyperParameterTuningJobObjective.
" + "smithy.api#documentation": "A TrainingJobSummary object that describes the training job that completed with the best current HyperParameterTuningJobObjective.
" } }, "OverallBestTrainingJob": { "target": "com.amazonaws.sagemaker#HyperParameterTrainingJobSummary", "traits": { - "smithy.api#documentation": "If the hyperparameter tuning job is an warm start tuning job with a\n WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the\n TrainingJobSummary for the training job with the best objective metric\n value of all training jobs launched by this tuning job and all parent jobs specified for\n the warm start tuning job.
If the hyperparameter tuning job is an warm start tuning job with a WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary for the training job with the best objective metric value of all training jobs launched by this tuning job and all parent jobs specified for the warm start tuning job.
The configuration for starting the hyperparameter parameter tuning job using one or\n more previous tuning jobs as a starting point. The results of previous tuning jobs are\n used to inform which combinations of hyperparameters to search over in the new tuning\n job.
" + "smithy.api#documentation": "The configuration for starting the hyperparameter parameter tuning job using one or more previous tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
" } }, "Autotune": { @@ -22956,7 +22930,7 @@ "TuningJobCompletionDetails": { "target": "com.amazonaws.sagemaker#HyperParameterTuningJobCompletionDetails", "traits": { - "smithy.api#documentation": "Tuning job completion information returned as the response from a hyperparameter\n tuning job. This information tells if your tuning job has or has not converged. It also\n includes the number of training jobs that have not improved model performance as\n evaluated against the objective function.
" + "smithy.api#documentation": "Tuning job completion information returned as the response from a hyperparameter tuning job. This information tells if your tuning job has or has not converged. It also includes the number of training jobs that have not improved model performance as evaluated against the objective function.
" } }, "ConsumedResources": { @@ -23013,7 +22987,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 }, "ImageDeleted": { "acceptors": [ @@ -23040,7 +23015,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 }, "ImageUpdated": { "acceptors": [ @@ -23071,7 +23047,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 } } } @@ -23200,7 +23177,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 }, "ImageVersionDeleted": { "acceptors": [ @@ -23227,7 +23205,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 } } } @@ -23320,13 +23299,13 @@ "VendorGuidance": { "target": "com.amazonaws.sagemaker#VendorGuidance", "traits": { - "smithy.api#documentation": "The stability of the image version specified by the maintainer.
\n\n NOT_PROVIDED: The maintainers did not provide a status for image version stability.
\n STABLE: The image version is stable.
\n TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
\n ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The stability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
\n\n TRAINING: The image version is compatible with SageMaker AI training jobs.
\n INFERENCE: The image version is compatible with SageMaker AI inference jobs.
\n NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
\n\n CPU: The image version is compatible with CPU.
\n GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
If the inference component status is Failed, the reason for the\n failure.
If the inference component status is Failed, the reason for the failure.
Details about the runtime settings for the model that is deployed with the inference\n component.
" + "smithy.api#documentation": "Details about the runtime settings for the model that is deployed with the inference component.
" } }, "CreationTime": { @@ -23476,7 +23455,7 @@ "LastDeploymentConfig": { "target": "com.amazonaws.sagemaker#InferenceComponentDeploymentConfig", "traits": { - "smithy.api#documentation": "The deployment and rollback settings that you assigned to the inference\n component.
" + "smithy.api#documentation": "The deployment and rollback settings that you assigned to the inference component.
" } } }, @@ -23554,14 +23533,14 @@ "target": "com.amazonaws.sagemaker#InferenceExperimentStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The status of the inference experiment. The following are the possible statuses for an inference\n experiment:\n
\n\n Creating - Amazon SageMaker is creating your experiment.\n
\n Created - Amazon SageMaker has finished the creation of your experiment and will begin the\n experiment at the scheduled time.\n
\n Updating - When you make changes to your experiment, your experiment shows as updating.\n
\n Starting - Amazon SageMaker is beginning your experiment.\n
\n Running - Your experiment is in progress.\n
\n Stopping - Amazon SageMaker is stopping your experiment.\n
\n Completed - Your experiment has completed.\n
\n Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows\n as cancelled.\n
The status of the inference experiment. The following are the possible statuses for an inference experiment:
Creating - Amazon SageMaker is creating your experiment.
Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.
Updating - When you make changes to your experiment, your experiment shows as updating.
Starting - Amazon SageMaker is beginning your experiment.
Running - Your experiment is in progress.
Stopping - Amazon SageMaker is stopping your experiment.
Completed - Your experiment has completed.
Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.
\n The error message or client-specified Reason from the StopInferenceExperiment\n API, that explains the status of the inference experiment.\n
The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.
\n The timestamp at which the inference experiment was completed.\n
" + "smithy.api#documentation": "The timestamp at which the inference experiment was completed.
" } }, "LastModifiedTime": { @@ -23591,7 +23570,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "\n The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage\n Amazon SageMaker Inference endpoints for model deployment.\n
" + "smithy.api#documentation": "The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
" } }, "EndpointMetadata": { @@ -23606,7 +23585,7 @@ "target": "com.amazonaws.sagemaker#ModelVariantConfigSummaryList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n An array of ModelVariantConfigSummary objects. There is one for each variant in the inference\n experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure\n configuration for deploying the corresponding variant.\n
An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.
\n The configuration of ShadowMode inference experiment type, which shows the production variant\n that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the\n inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.\n
The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.
\n The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on\n the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see\n CreateInferenceExperiment.\n
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.
" } } }, @@ -23647,7 +23626,7 @@ } ], "traits": { - "smithy.api#documentation": "Provides the results of the Inference Recommender job. \n One or more recommendation jobs are returned.
" + "smithy.api#documentation": "Provides the results of the Inference Recommender job. One or more recommendation jobs are returned.
" } }, "com.amazonaws.sagemaker#DescribeInferenceRecommendationsJobRequest": { @@ -23657,7 +23636,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the job. The name must be unique within an \n Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } } @@ -23673,7 +23652,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the job. The name must be unique within an \n Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -23703,7 +23682,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services \n Identity and Access Management (IAM) role you provided when you initiated the job.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services Identity and Access Management (IAM) role you provided when you initiated the job.
", "smithy.api#required": {} } }, @@ -23747,7 +23726,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobInputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Returns information about the versioned model package Amazon Resource Name (ARN), \n the traffic pattern, and endpoint configurations you provided when you initiated the job.
", + "smithy.api#documentation": "Returns information about the versioned model package Amazon Resource Name (ARN), the traffic pattern, and endpoint configurations you provided when you initiated the job.
", "smithy.api#required": {} } }, @@ -23822,7 +23801,7 @@ "target": "com.amazonaws.sagemaker#LabelCounters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Provides a breakdown of the number of data objects labeled by humans, the number of\n objects labeled by machine, the number of objects than couldn't be labeled, and the\n total number of objects labeled.
", + "smithy.api#documentation": "Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.
", "smithy.api#required": {} } }, @@ -23882,7 +23861,7 @@ "target": "com.amazonaws.sagemaker#LabelingJobInputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Input configuration information for the labeling job, such as the Amazon S3 location of the\n data objects and the location of the manifest file that describes the data\n objects.
", + "smithy.api#documentation": "Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
", "smithy.api#required": {} } }, @@ -23890,7 +23869,7 @@ "target": "com.amazonaws.sagemaker#LabelingJobOutputConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The location of the job's output data and the Amazon Web Services Key Management\n Service key ID for the key used to encrypt the output data, if any.
", + "smithy.api#documentation": "The location of the job's output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
", "smithy.api#required": {} } }, @@ -23898,20 +23877,20 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf\n during data labeling.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during data labeling.
", "smithy.api#required": {} } }, "LabelCategoryConfigS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The S3 location of the JSON file that defines the categories used to label data\n objects. Please note the following label-category limits:
\nSemantic segmentation labeling jobs using automated labeling: 20 labels
\nBox bounding labeling jobs (all): 10 labels
\nThe file is a JSON structure in the following format:
\n\n {\n
\n \"document-version\": \"2018-11-28\"\n
\n \"labels\": [\n
\n {\n
\n \"label\": \"label 1\"\n
\n },\n
\n {\n
\n \"label\": \"label 2\"\n
\n },\n
\n ...\n
\n {\n
\n \"label\": \"label n\"\n
\n }\n
\n ]\n
\n }\n
The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:
Semantic segmentation labeling jobs using automated labeling: 20 labels
Box bounding labeling jobs (all): 10 labels
The file is a JSON structure in the following format:
{
\"document-version\": \"2018-11-28\"
\"labels\": [
{
\"label\": \"label 1\"
},
{
\"label\": \"label 2\"
},
...
{
\"label\": \"label n\"
}
]
}
A set of conditions for stopping a labeling job. If any of the conditions are met, the\n job is automatically stopped.
" + "smithy.api#documentation": "A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.
" } }, "LabelingJobAlgorithmsConfig": { @@ -23924,14 +23903,14 @@ "target": "com.amazonaws.sagemaker#HumanTaskConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Configuration information required for human workers to complete a labeling\n task.
", + "smithy.api#documentation": "Configuration information required for human workers to complete a labeling task.
", "smithy.api#required": {} } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } }, "LabelingJobOutput": { @@ -23959,7 +23938,7 @@ } ], "traits": { - "smithy.api#documentation": "Provides a list of properties for the requested lineage group. \n For more information, see \n Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
" + "smithy.api#documentation": "Provides a list of properties for the requested lineage group. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
" } }, "com.amazonaws.sagemaker#DescribeLineageGroupRequest": { @@ -24079,7 +24058,7 @@ "ArtifactStoreUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The S3 URI of the general purpose bucket used as the MLflow Tracking Server\n artifact store.
" + "smithy.api#documentation": "The S3 URI of the general purpose bucket used as the MLflow Tracking Server artifact store.
" } }, "TrackingServerSize": { @@ -24097,7 +24076,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server\n uses to access the artifact store in Amazon S3.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) for an IAM role in your account that the described MLflow Tracking Server uses to access the artifact store in Amazon S3.
" } }, "TrackingServerStatus": { @@ -24162,7 +24141,7 @@ "target": "com.amazonaws.sagemaker#DescribeModelOutput" }, "traits": { - "smithy.api#documentation": "Describes a model that you created using the CreateModel\n API.
Describes a model that you created using the CreateModel API.
The name of the bias job definition. The name must be unique within an Amazon Web Services \n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the bias job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -24271,7 +24250,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the \n input data location and write permission to the output data location in Amazon S3.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -24356,7 +24335,7 @@ "target": "com.amazonaws.sagemaker#ModelCardExportJobStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The completion status of the model card export job.
\n\n InProgress: The model card export job is in progress.
\n Completed: The model card export job is complete.
\n Failed: The model card export job failed. To see the reason for the failure, see\n the FailureReason field in the response to a\n DescribeModelCardExportJob call.
The completion status of the model card export job.
InProgress: The model card export job is in progress.
Completed: The model card export job is complete.
Failed: The model card export job failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeModelCardExportJob call.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
\n DeletePending: Model card deletion request received.
\n DeleteInProgress: Model card deletion is in progress.
\n ContentDeleted: Deleted model card content.
\n ExportJobsDeleted: Deleted all export jobs associated with the model card.
\n DeleteCompleted: Successfully deleted the model card.
\n DeleteFailed: The model card failed to delete.
The processing status of model card deletion. The ModelCardProcessingStatus updates throughout the different deletion steps.
DeletePending: Model card deletion request received.
DeleteInProgress: Model card deletion is in progress.
ContentDeleted: Deleted model card content.
ExportJobsDeleted: Deleted all export jobs associated with the model card.
DeleteCompleted: Successfully deleted the model card.
DeleteFailed: The model card failed to delete.
The name of the model explainability job definition. The name must be unique within an\n Amazon Web Services Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the model explainability job definition. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } } @@ -24629,7 +24608,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the \n input data location and write permission to the output data location in Amazon S3.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that has read permission to the input data location and write permission to the output data location in Amazon S3.
", "smithy.api#required": {} } }, @@ -24671,7 +24650,7 @@ "PrimaryContainer": { "target": "com.amazonaws.sagemaker#ContainerDefinition", "traits": { - "smithy.api#documentation": "The location of the primary inference code, associated artifacts, and custom\n environment map that the inference code uses when it is deployed in production.\n
" + "smithy.api#documentation": "The location of the primary inference code, associated artifacts, and custom environment map that the inference code uses when it is deployed in production.
" } }, "Containers": { @@ -24689,13 +24668,13 @@ "ExecutionRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that you specified for the\n model.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
" } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this model has access to. For\n more information, see Protect Endpoints by Using an Amazon Virtual\n Private Cloud\n
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this model has access to. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
" } }, "CreationTime": { @@ -24717,7 +24696,7 @@ "EnableNetworkIsolation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "If True, no inbound or outbound network calls can be made to or from the\n model container.
If True, no inbound or outbound network calls can be made to or from the model container.
Returns a description of the specified model package, which is used to create SageMaker\n models or list them on Amazon Web Services Marketplace.
\nIf you provided a KMS Key ID when you created your model package,\n you will see the KMS Decrypt API call in\n your CloudTrail logs when you use this API.
\nTo create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
" + "smithy.api#documentation": "Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
If you provided a KMS Key ID when you created your model package, you will see the KMS Decrypt API call in your CloudTrail logs when you use this API.
To create models in SageMaker, buyers can subscribe to model packages listed on Amazon Web Services Marketplace.
" } }, "com.amazonaws.sagemaker#DescribeModelPackageGroup": { @@ -24831,7 +24810,7 @@ "target": "com.amazonaws.sagemaker#VersionedArnOrName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package to describe.
\nWhen you specify a name, the name must have 1 to 63 characters. Valid characters are\n a-z, A-Z, 0-9, and - (hyphen).
", + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the model package to describe.
When you specify a name, the name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
", "smithy.api#required": {} } } @@ -24854,7 +24833,7 @@ "ModelPackageGroupName": { "target": "com.amazonaws.sagemaker#EntityName", "traits": { - "smithy.api#documentation": "If the model is a versioned model, the name of the model group that the versioned\n model belongs to.
" + "smithy.api#documentation": "If the model is a versioned model, the name of the model group that the versioned model belongs to.
" } }, "ModelPackageVersion": { @@ -24888,7 +24867,7 @@ "InferenceSpecification": { "target": "com.amazonaws.sagemaker#InferenceSpecification", "traits": { - "smithy.api#documentation": "Details about inference jobs that you can run with models based on this model\n package.
" + "smithy.api#documentation": "Details about inference jobs that you can run with models based on this model package.
" } }, "SourceAlgorithmSpecification": { @@ -24900,7 +24879,7 @@ "ValidationSpecification": { "target": "com.amazonaws.sagemaker#ModelPackageValidationSpecification", "traits": { - "smithy.api#documentation": "Configurations for one or more transform jobs that SageMaker runs to test the model\n package.
" + "smithy.api#documentation": "Configurations for one or more transform jobs that SageMaker runs to test the model package.
" } }, "ModelPackageStatus": { @@ -24922,7 +24901,7 @@ "CertifyForMarketplace": { "target": "com.amazonaws.sagemaker#CertifyForMarketplace", "traits": { - "smithy.api#documentation": "Whether the model package is certified for listing on Amazon Web Services\n Marketplace.
" + "smithy.api#documentation": "Whether the model package is certified for listing on Amazon Web Services Marketplace.
" } }, "ModelApprovalStatus": { @@ -24961,19 +24940,19 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of the model package you specified. Common machine\n learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task you specified that your model package accomplishes. Common\n machine learning tasks include object detection and image classification.
" + "smithy.api#documentation": "The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a\n single gzip compressed tar archive (.tar.gz suffix).
" + "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).
" } }, "CustomerMetadataProperties": { @@ -24985,13 +24964,13 @@ "DriftCheckBaselines": { "target": "com.amazonaws.sagemaker#DriftCheckBaselines", "traits": { - "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set\n using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker\n Pipelines in the Amazon SageMaker Developer Guide.
" + "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
" } }, "AdditionalInferenceSpecifications": { "target": "com.amazonaws.sagemaker#AdditionalInferenceSpecifications", "traits": { - "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional Inference\n Specification specifies artifacts based on this model package that can be used on\n inference endpoints. Generally used with SageMaker Neo to store the compiled\n artifacts.
" + "smithy.api#documentation": "An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
" } }, "SkipModelValidation": { @@ -25009,13 +24988,13 @@ "SecurityConfig": { "target": "com.amazonaws.sagemaker#ModelPackageSecurityConfig", "traits": { - "smithy.api#documentation": "The KMS Key ID (KMSKeyId) used for encryption of model\n package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
The model card associated with the model package. Since\n ModelPackageModelCard is tied to a model package, it is a specific\n usage of a model card and its schema is simplified compared to the schema of\n ModelCard. The ModelPackageModelCard schema does not\n include model_package_details, and model_overview is composed\n of the model_creator and model_artifact properties. For more\n information about the model package model card schema, see Model\n package model card schema. For more information about the model card\n associated with the model package, see View the Details of a Model\n Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
The name of the model quality job. The name must be unique within an Amazon Web Services\n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the model quality job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } } @@ -25135,7 +25114,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -25210,13 +25189,13 @@ "MonitoringType": { "target": "com.amazonaws.sagemaker#MonitoringType", "traits": { - "smithy.api#documentation": "The type of the monitoring job that this schedule runs. This is one of the following\n values.
\n\n DATA_QUALITY - The schedule is for a data quality monitoring\n job.
\n MODEL_QUALITY - The schedule is for a model quality monitoring\n job.
\n MODEL_BIAS - The schedule is for a bias monitoring job.
\n MODEL_EXPLAINABILITY - The schedule is for an explainability\n monitoring job.
The type of the monitoring job that this schedule runs. This is one of the following values.
DATA_QUALITY - The schedule is for a data quality monitoring job.
MODEL_QUALITY - The schedule is for a model quality monitoring job.
MODEL_BIAS - The schedule is for a bias monitoring job.
MODEL_EXPLAINABILITY - The schedule is for an explainability monitoring job.
A string, up to one KB in size, that contains the reason a monitoring job failed, if it\n failed.
" + "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a monitoring job failed, if it failed.
" } }, "CreationTime": { @@ -25239,7 +25218,7 @@ "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring job.
", "smithy.api#required": {} } }, @@ -25291,7 +25270,8 @@ } } ], - "minDelay": 30 + "minDelay": 30, + "maxDelay": 1800 }, "NotebookInstanceInService": { "acceptors": [ @@ -25316,7 +25296,8 @@ } } ], - "minDelay": 30 + "minDelay": 30, + "maxDelay": 1800 }, "NotebookInstanceStopped": { "acceptors": [ @@ -25341,7 +25322,8 @@ } } ], - "minDelay": 30 + "minDelay": 30, + "maxDelay": 1800 } } } @@ -25371,7 +25353,7 @@ "target": "com.amazonaws.sagemaker#DescribeNotebookInstanceLifecycleConfigOutput" }, "traits": { - "smithy.api#documentation": "Returns a description of a notebook instance lifecycle configuration.
\nFor information about notebook instance lifestyle configurations, see Step\n 2.1: (Optional) Customize a Notebook Instance.
" + "smithy.api#documentation": "Returns a description of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "com.amazonaws.sagemaker#DescribeNotebookInstanceLifecycleConfigInput": { @@ -25414,7 +25396,7 @@ "OnStart": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigList", "traits": { - "smithy.api#documentation": "The shell script that runs every time you start a notebook instance, including when\n you create the notebook instance.
" + "smithy.api#documentation": "The shell script that runs every time you start a notebook instance, including when you create the notebook instance.
" } }, "LastModifiedTime": { @@ -25464,7 +25446,7 @@ "Url": { "target": "com.amazonaws.sagemaker#NotebookInstanceUrl", "traits": { - "smithy.api#documentation": "The URL that you use to connect to the Jupyter notebook that is running in your\n notebook instance.
" + "smithy.api#documentation": "The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
" } }, "InstanceType": { @@ -25488,43 +25470,43 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role associated with the instance.\n
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role associated with the instance.
" } }, "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services KMS key ID SageMaker AI uses to encrypt data when\n storing it on the ML storage volume attached to the instance.
" + "smithy.api#documentation": "The Amazon Web Services KMS key ID SageMaker AI uses to encrypt data when storing it on the ML storage volume attached to the instance.
" } }, "NetworkInterfaceId": { "target": "com.amazonaws.sagemaker#NetworkInterfaceId", "traits": { - "smithy.api#documentation": "The network interface IDs that SageMaker AI created at the time of creating\n the instance.
" + "smithy.api#documentation": "The network interface IDs that SageMaker AI created at the time of creating the instance.
" } }, "LastModifiedTime": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A timestamp. Use this parameter to retrieve the time when the notebook instance was\n last modified.
" + "smithy.api#documentation": "A timestamp. Use this parameter to retrieve the time when the notebook instance was last modified.
" } }, "CreationTime": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A timestamp. Use this parameter to return the time when the notebook instance was\n created
" + "smithy.api#documentation": "A timestamp. Use this parameter to return the time when the notebook instance was created
" } }, "NotebookInstanceLifecycleConfigName": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigName", "traits": { - "smithy.api#documentation": "Returns the name of a notebook instance lifecycle configuration.
\nFor information about notebook instance lifestyle configurations, see Step\n 2.1: (Optional) Customize a Notebook Instance\n
" + "smithy.api#documentation": "Returns the name of a notebook instance lifecycle configuration.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance
" } }, "DirectInternetAccess": { "target": "com.amazonaws.sagemaker#DirectInternetAccess", "traits": { - "smithy.api#documentation": "Describes whether SageMaker AI provides internet access to the notebook instance.\n If this value is set to Disabled, the notebook instance does not\n have internet access, and cannot connect to SageMaker AI training and endpoint\n services.
\nFor more information, see Notebook Instances Are Internet-Enabled by Default.
" + "smithy.api#documentation": "Describes whether SageMaker AI provides internet access to the notebook instance. If this value is set to Disabled, the notebook instance does not have internet access, and cannot connect to SageMaker AI training and endpoint services.
For more information, see Notebook Instances Are Internet-Enabled by Default.
" } }, "VolumeSizeInGB": { @@ -25536,25 +25518,25 @@ "AcceleratorTypes": { "target": "com.amazonaws.sagemaker#NotebookInstanceAcceleratorTypes", "traits": { - "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify a list of the EI instance types associated with\n this notebook instance.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types associated with this notebook instance.
" } }, "DefaultCodeRepository": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameOrUrl", "traits": { - "smithy.api#documentation": "The Git repository associated with the notebook instance as its default code\n repository. This can be either the name of a Git repository stored as a resource in your\n account, or the URL of a Git repository in Amazon Web Services CodeCommit\n or in any other Git repository. When you open a notebook instance, it opens in the\n directory that contains this repository. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "AdditionalCodeRepositories": { "target": "com.amazonaws.sagemaker#AdditionalCodeRepositoryNamesOrUrls", "traits": { - "smithy.api#documentation": "An array of up to three Git repositories associated with the notebook instance. These\n can be either the names of Git repositories stored as resources in your account, or the\n URL of Git repositories in Amazon Web Services CodeCommit\n or in any other Git repository. These repositories are cloned at the same level as the\n default repository of your notebook instance. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "RootAccess": { "target": "com.amazonaws.sagemaker#RootAccess", "traits": { - "smithy.api#documentation": "Whether root access is enabled or disabled for users of the notebook instance.
\nLifecycle configurations need root access to be able to set up a notebook\n instance. Because of this, lifecycle configurations associated with a notebook\n instance always run with root access even if you disable root access for\n users.
\nWhether root access is enabled or disabled for users of the notebook instance.
Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.
If the optimization job status is FAILED, the reason for the\n failure.
If the optimization job status is FAILED, the reason for the failure.
The name of the processing job. The name must be unique within an Amazon Web Services\n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } } @@ -26247,7 +26230,7 @@ "target": "com.amazonaws.sagemaker#ProcessingJobName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the processing job. The name must be unique within an Amazon Web Services\n Region in the Amazon Web Services account.
", + "smithy.api#documentation": "The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -26255,7 +26238,7 @@ "target": "com.amazonaws.sagemaker#ProcessingResources", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a\n processing job. In distributed training, you specify more than one instance.
", + "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
", "smithy.api#required": {} } }, @@ -26288,7 +26271,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on\n your behalf.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
" } }, "ExperimentConfig": { @@ -26316,13 +26299,13 @@ "ExitMessage": { "target": "com.amazonaws.sagemaker#ExitMessage", "traits": { - "smithy.api#documentation": "An optional string, up to one KB in size, that contains metadata from the processing\n container when the processing job exits.
" + "smithy.api#documentation": "An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
" } }, "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if\n it failed.
" + "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
" } }, "ProcessingEndTime": { @@ -26354,7 +26337,7 @@ "MonitoringScheduleArn": { "target": "com.amazonaws.sagemaker#MonitoringScheduleArn", "traits": { - "smithy.api#documentation": "The ARN of a monitoring schedule for an endpoint associated with this processing\n job.
" + "smithy.api#documentation": "The ARN of a monitoring schedule for an endpoint associated with this processing job.
" } }, "AutoMLJobArn": { @@ -26438,7 +26421,7 @@ "ServiceCatalogProvisioningDetails": { "target": "com.amazonaws.sagemaker#ServiceCatalogProvisioningDetails", "traits": { - "smithy.api#documentation": "Information used to provision a service catalog product. For information, see What is Amazon Web Services Service\n Catalog.
" + "smithy.api#documentation": "Information used to provision a service catalog product. For information, see What is Amazon Web Services Service Catalog.
" } }, "ServiceCatalogProvisionedProductDetails": { @@ -26599,7 +26582,7 @@ "Url": { "target": "com.amazonaws.sagemaker#String1024", "traits": { - "smithy.api#documentation": "Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity\n Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to\n the URL after appending the respective redirect parameter for the application type to be\n federated through Amazon Web Services IAM Identity Center.
\nThe following application types are supported:
\nStudio Classic: &redirect=JupyterServer\n
JupyterLab: &redirect=JupyterLab\n
Code Editor, based on Code-OSS, Visual Studio Code - Open Source:\n &redirect=CodeEditor\n
Returns the URL of the space. If the space is created with Amazon Web Services IAM Identity Center (Successor to Amazon Web Services Single Sign-On) authentication, users can navigate to the URL after appending the respective redirect parameter for the application type to be federated through Amazon Web Services IAM Identity Center.
The following application types are supported:
Studio Classic: &redirect=JupyterServer
JupyterLab: &redirect=JupyterLab
Code Editor, based on Code-OSS, Visual Studio Code - Open Source: &redirect=CodeEditor
The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is\n described.
" + "smithy.api#documentation": "The name of the Amazon SageMaker AI Studio Lifecycle Configuration that is described.
" } }, "CreationTime": { @@ -26664,7 +26647,7 @@ "LastModifiedTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle\n Configurations are immutable.
" + "smithy.api#documentation": "This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.
" } }, "StudioLifecycleConfigContent": { @@ -26693,7 +26676,7 @@ "target": "com.amazonaws.sagemaker#DescribeSubscribedWorkteamResponse" }, "traits": { - "smithy.api#documentation": "Gets information about a work team provided by a vendor. It returns details about the\n subscription with a vendor in the Amazon Web Services Marketplace.
" + "smithy.api#documentation": "Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the Amazon Web Services Marketplace.
" } }, "com.amazonaws.sagemaker#DescribeSubscribedWorkteamRequest": { @@ -26742,7 +26725,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns information about a training job.
\nSome of the attributes below only appear if the training job successfully starts.\n If the training job fails, TrainingJobStatus is Failed and,\n depending on the FailureReason, attributes like\n TrainingStartTime, TrainingTimeInSeconds,\n TrainingEndTime, and BillableTimeInSeconds may not be\n present in the response.
Returns information about a training job.
Some of the attributes below only appear if the training job successfully starts. If the training job fails, TrainingJobStatus is Failed and, depending on the FailureReason, attributes like TrainingStartTime, TrainingTimeInSeconds, TrainingEndTime, and BillableTimeInSeconds may not be present in the response.
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the\n training job was launched by a hyperparameter tuning job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
" } }, "LabelingJobArn": { "target": "com.amazonaws.sagemaker#LabelingJobArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the\n transform or training job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
" } }, "AutoMLJobArn": { @@ -26846,7 +26830,7 @@ "target": "com.amazonaws.sagemaker#ModelArtifacts", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Information about the Amazon S3 location that is configured for storing model artifacts.\n
", + "smithy.api#documentation": "Information about the Amazon S3 location that is configured for storing model artifacts.
", "smithy.api#required": {} } }, @@ -26854,7 +26838,7 @@ "target": "com.amazonaws.sagemaker#TrainingJobStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The status of the training job.
\nSageMaker provides the following training job statuses:
\n\n InProgress - The training is in progress.
\n Completed - The training job has completed.
\n Failed - The training job has failed. To see the reason for the\n failure, see the FailureReason field in the response to a\n DescribeTrainingJobResponse call.
\n Stopping - The training job is stopping.
\n Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
The status of the training job.
SageMaker provides the following training job statuses:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
Provides detailed information about the state of the training job. For detailed\n information on the secondary status of the training job, see StatusMessage\n under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of\n them:
\n\n Starting\n - Starting the training job.
\n Downloading - An optional stage for algorithms that\n support File training input mode. It indicates that\n data is being downloaded to the ML storage volumes.
\n Training - Training is in progress.
\n Interrupted - The job stopped because the managed\n spot training instances were interrupted.
\n Uploading - Training is complete and the model\n artifacts are being uploaded to the S3 location.
\n Completed - The training job has completed.
\n Failed - The training job has failed. The reason for\n the failure is returned in the FailureReason field of\n DescribeTrainingJobResponse.
\n MaxRuntimeExceeded - The job stopped because it\n exceeded the maximum allowed runtime.
\n MaxWaitTimeExceeded - The job stopped because it\n exceeded the maximum allowed wait time.
\n Stopped - The training job has stopped.
\n Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
\n\n LaunchingMLInstances\n
\n PreparingTraining\n
\n DownloadingTrainingImage\n
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Interrupted - The job stopped because the managed spot training instances were interrupted.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
MaxWaitTimeExceeded - The job stopped because it exceeded the maximum allowed wait time.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTraining
DownloadingTrainingImage
Information about the algorithm used for training, and algorithm metadata.\n
", + "smithy.api#documentation": "Information about the algorithm used for training, and algorithm metadata.
", "smithy.api#required": {} } }, "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Web Services Identity and Access Management (IAM) role configured for\n the training job.
" + "smithy.api#documentation": "The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
" } }, "InputDataConfig": { "target": "com.amazonaws.sagemaker#InputDataConfig", "traits": { - "smithy.api#documentation": "An array of Channel objects that describes each data input channel.\n
An array of Channel objects that describes each data input channel.
The S3 path where model artifacts that you configured when creating the job are\n stored. SageMaker creates subfolders for model artifacts.
" + "smithy.api#documentation": "The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
" } }, "ResourceConfig": { "target": "com.amazonaws.sagemaker#ResourceConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Resources, including ML compute instances and ML storage volumes, that are\n configured for model training.
", + "smithy.api#documentation": "Resources, including ML compute instances and ML storage volumes, that are configured for model training.
", "smithy.api#required": {} } }, @@ -26921,14 +26905,14 @@ "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this training job has access\n to. For more information, see Protect Training Jobs by Using an Amazon\n Virtual Private Cloud.
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
" } }, "StoppingCondition": { "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a limit to how long a model training job can run. It also specifies how long\n a managed Spot training job has to complete. When the job reaches the time limit, SageMaker\n ends the training job. Use this API to cap model training costs.
\nTo stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays\n job termination for 120 seconds. Algorithms can use this 120-second window to save the\n model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Indicates the time when the training job starts on training instances. You are\n billed for the time interval between this time and the value of\n TrainingEndTime. The start time in CloudWatch Logs might be later than this time.\n The difference is due to the time it takes to download the training data and to the size\n of the training container.
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed\n for the time interval between the value of TrainingStartTime and this time.\n For successful jobs and stopped jobs, this is the time after model artifacts are\n uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last\n modified.
" + "smithy.api#documentation": "A timestamp that indicates when the status of the training job was last modified.
" } }, "SecondaryStatusTransitions": { "target": "com.amazonaws.sagemaker#SecondaryStatusTransitions", "traits": { - "smithy.api#documentation": "A history of all of the secondary statuses that the training job has transitioned\n through.
" + "smithy.api#documentation": "A history of all of the secondary statuses that the training job has transitioned through.
" } }, "FinalMetricDataList": { "target": "com.amazonaws.sagemaker#FinalMetricDataList", "traits": { - "smithy.api#documentation": "A collection of MetricData objects that specify the names, values, and\n dates and times that the training algorithm emitted to Amazon CloudWatch.
A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
If you want to allow inbound or outbound network calls, except for calls between peers\n within a training cluster for distributed training, choose True. If you\n enable network isolation for training jobs that are configured to use a VPC, SageMaker\n downloads and uploads customer data and model artifacts through the specified VPC, but\n the training container does not have network access.
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose True. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
To encrypt all communications between ML compute instances in distributed training,\n choose True. Encryption provides greater security for distributed training,\n but training might take longer. How long it takes depends on the amount of communication\n between compute instances, especially if you use a deep learning algorithms in\n distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or\n not (False).
A Boolean indicating whether managed spot training is enabled (True) or not (False).
The billable time in seconds. Billable time refers to the absolute wall-clock\n time.
\nMultiply BillableTimeInSeconds by the number of instances\n (InstanceCount) in your training cluster to get the total compute time\n SageMaker bills you if you run distributed training. The formula is as follows:\n BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula\n (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example,\n if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is\n 500, the savings is 80%.
The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply BillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows: BillableTimeInSeconds * InstanceCount .
You can calculate the savings from using managed spot training using the formula (1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
Configuration information for Amazon SageMaker Debugger rules for profiling system and framework\n metrics.
" + "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
" } }, "ProfilerRuleEvaluationStatuses": { @@ -27048,19 +27032,19 @@ "Environment": { "target": "com.amazonaws.sagemaker#TrainingEnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the Docker container.
\nDo not include any security-sensitive information including account access IDs, secrets, \n or tokens in any environment fields. As part of the shared responsibility \n model, you are responsible for any potential exposure, unauthorized access, or compromise of \n your sensitive data if caused by security-sensitive information included in the \n request environment variable or plain text fields.
\nThe environment variables to set in the Docker container.
Do not include any security-sensitive information including account access IDs, secrets, or tokens in any environment fields. As part of the shared responsibility model, you are responsible for any potential exposure, unauthorized access, or compromise of your sensitive data if caused by security-sensitive information included in the request environment variable or plain text fields.
The number of times to retry the job when the job fails due to an\n InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
Configuration for remote debugging. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" + "smithy.api#documentation": "Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
" } }, "InfraCheckConfig": { @@ -27130,14 +27114,14 @@ "target": "com.amazonaws.sagemaker#TrainingPlanStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The current status of the training plan (e.g., Pending, Active, Expired). To see the\n complete list of status values available for a training plan, refer to the\n Status attribute within the \n TrainingPlanSummary\n object.
The current status of the training plan (e.g., Pending, Active, Expired). To see the complete list of status values available for a training plan, refer to the Status attribute within the TrainingPlanSummary object.
A message providing additional information about the current status of the training\n plan.
" + "smithy.api#documentation": "A message providing additional information about the current status of the training plan.
" } }, "DurationHours": { @@ -27149,7 +27133,7 @@ "DurationMinutes": { "target": "com.amazonaws.sagemaker#TrainingPlanDurationMinutes", "traits": { - "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training\n plan.
" + "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training plan.
" } }, "StartTime": { @@ -27197,13 +27181,13 @@ "TargetResources": { "target": "com.amazonaws.sagemaker#SageMakerResourceNames", "traits": { - "smithy.api#documentation": "The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) that can use this training\n plan.
\nTraining plans are specific to their target resource.
\nA training plan designed for SageMaker training jobs can only be used to schedule and\n run training jobs.
\nA training plan for HyperPod clusters can be used exclusively to provide\n compute resources to a cluster's instance group.
\nThe target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) that can use this training plan.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
The list of Reserved Capacity providing the underlying compute resources of the plan.\n
" + "smithy.api#documentation": "The list of Reserved Capacity providing the underlying compute resources of the plan.
" } } }, @@ -27267,7 +27251,8 @@ } } ], - "minDelay": 60 + "minDelay": 60, + "maxDelay": 3600 } } } @@ -27311,14 +27296,14 @@ "target": "com.amazonaws.sagemaker#TransformJobStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The\n status of the transform job. If the transform job failed, the reason\n is returned in the FailureReason field.
The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.
If the transform job failed, FailureReason describes\n why\n it failed. A transform job creates a log file, which includes error\n messages, and stores it\n as\n an Amazon S3 object. For more information, see Log Amazon SageMaker Events with\n Amazon CloudWatch.
If the transform job failed, FailureReason describes why it failed. A transform job creates a log file, which includes error messages, and stores it as an Amazon S3 object. For more information, see Log Amazon SageMaker Events with Amazon CloudWatch.
The\n maximum number\n of\n parallel requests on each instance node\n that can be launched in a transform job. The default value is 1.
" + "smithy.api#documentation": "The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.
" } }, "ModelClientConfig": { "target": "com.amazonaws.sagemaker#ModelClientConfig", "traits": { - "smithy.api#documentation": "The timeout and maximum number of retries for processing a transform job\n invocation.
" + "smithy.api#documentation": "The timeout and maximum number of retries for processing a transform job invocation.
" } }, "MaxPayloadInMB": { "target": "com.amazonaws.sagemaker#MaxPayloadInMB", "traits": { - "smithy.api#documentation": "The\n maximum\n payload size, in MB, used in the\n transform job.
" + "smithy.api#documentation": "The maximum payload size, in MB, used in the transform job.
" } }, "BatchStrategy": { "target": "com.amazonaws.sagemaker#BatchStrategy", "traits": { - "smithy.api#documentation": "Specifies the number of records to include in a mini-batch for an HTTP inference\n request.\n A record\n is a single unit of input data that inference\n can be made on. For example, a single line in a CSV file is a record.
\nTo enable the batch strategy, you must set SplitType\n to\n Line, RecordIO, or\n TFRecord.
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
To enable the batch strategy, you must set SplitType to Line, RecordIO, or TFRecord.
The\n environment variables to set in the Docker container. We support up to 16 key and values\n entries in the map.
" + "smithy.api#documentation": "The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
" } }, "TransformInput": { "target": "com.amazonaws.sagemaker#TransformInput", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Describes the dataset to be transformed and the Amazon S3 location where it is\n stored.
", + "smithy.api#documentation": "Describes the dataset to be transformed and the Amazon S3 location where it is stored.
", "smithy.api#required": {} } }, "TransformOutput": { "target": "com.amazonaws.sagemaker#TransformOutput", "traits": { - "smithy.api#documentation": "Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the\n transform job.
" + "smithy.api#documentation": "Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
" } }, "DataCaptureConfig": { @@ -27383,7 +27368,7 @@ "target": "com.amazonaws.sagemaker#TransformResources", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Describes\n the resources, including ML instance types and ML instance count, to\n use for the transform job.
", + "smithy.api#documentation": "Describes the resources, including ML instance types and ML instance count, to use for the transform job.
", "smithy.api#required": {} } }, @@ -27398,19 +27383,19 @@ "TransformStartTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Indicates when the transform job starts\n on\n ML instances. You are billed for the time interval between this time\n and the value of TransformEndTime.
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been\n \n completed, or has stopped or failed. You are billed for the time\n interval between this time and the value of TransformStartTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the\n transform or training job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
" } }, "AutoMLJobArn": { @@ -27498,7 +27483,7 @@ "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the component as displayed. If DisplayName isn't specified,\n TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
\nInProgress
\nCompleted
\nFailed
\nThe status of the component. States include:
InProgress
Completed
Failed
A list of ARNs and, if applicable, job types for multiple sources of an experiment\n run.
" + "smithy.api#documentation": "A list of ARNs and, if applicable, job types for multiple sources of an experiment run.
" } } }, @@ -27627,7 +27612,7 @@ "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the trial as displayed. If DisplayName isn't specified,\n TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
Lists private workforce information, including workforce name, Amazon Resource Name\n (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address\n ranges are the IP addresses that workers can use to access tasks.
\nThis operation applies only to private workforces.
\nLists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs). Allowable IP address ranges are the IP addresses that workers can use to access tasks.
This operation applies only to private workforces.
The name of the private workforce whose access you want to restrict.\n WorkforceName is automatically set to default when a\n workforce is created and cannot be modified.
The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.
A single private workforce, which is automatically created when you create your first\n private work team. You can create one private work force in each Amazon Web Services Region. By default,\n any workforce-related API operation used in a specific region will apply to the\n workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
", + "smithy.api#documentation": "A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
", "smithy.api#required": {} } } @@ -27845,7 +27830,7 @@ "target": "com.amazonaws.sagemaker#DescribeWorkteamResponse" }, "traits": { - "smithy.api#documentation": "Gets information about a specific work team. You can see information such as the\n creation date, the last updated date, membership information, and the work team's Amazon\n Resource Name (ARN).
" + "smithy.api#documentation": "Gets information about a specific work team. You can see information such as the creation date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).
" } }, "com.amazonaws.sagemaker#DescribeWorkteamRequest": { @@ -27871,7 +27856,7 @@ "target": "com.amazonaws.sagemaker#Workteam", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A Workteam instance that contains information about the work team.\n
A Workteam instance that contains information about the work team.
The model deployment settings for the SageMaker Canvas application.
\nIn order to enable model deployment for Canvas, the SageMaker Domain's or user profile's Amazon Web Services IAM\n execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also\n turn on model deployment permissions through the SageMaker Domain's or user profile's settings in the SageMaker console.
The model deployment settings for the SageMaker Canvas application.
In order to enable model deployment for Canvas, the SageMaker Domain's or user profile's Amazon Web Services IAM execution role must have the AmazonSageMakerCanvasDirectDeployAccess policy attached. You can also turn on model deployment permissions through the SageMaker Domain's or user profile's settings in the SageMaker console.
Disables using Service Catalog in SageMaker. Service Catalog is used to create\n SageMaker projects.
" + "smithy.api#documentation": "Disables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
" } }, "com.amazonaws.sagemaker#DisableSagemakerServicecatalogPortfolioInput": { @@ -28542,7 +28527,7 @@ } ], "traits": { - "smithy.api#documentation": "Disassociates a trial component from a trial. This doesn't effect other trials the\n component is associated with. Before you can delete a component, you must disassociate the\n component from all trials it is associated with. To associate a trial component with a trial,\n call the AssociateTrialComponent API.
\nTo get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter.\n The list appears in the response under Results.TrialComponent.Parents.
Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API.
To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.
The list of Amazon Web Services accounts that are trusted when the domain is created in\n VPC-only mode.
" + "smithy.api#documentation": "The list of Amazon Web Services accounts that are trusted when the domain is created in VPC-only mode.
" } } }, @@ -28732,19 +28717,19 @@ "SecurityGroupIds": { "target": "com.amazonaws.sagemaker#DomainSecurityGroupIds", "traits": { - "smithy.api#documentation": "The security groups for the Amazon Virtual Private Cloud that the Domain uses for\n communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
A collection of settings that configure the RStudioServerPro Domain-level\n app.
A collection of settings that configure the RStudioServerPro Domain-level app.
The configuration for attaching a SageMaker AI user profile name to the execution\n role as a sts:SourceIdentity key.
" + "smithy.api#documentation": "The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key.
" } }, "DockerSettings": { @@ -28756,18 +28741,18 @@ "AmazonQSettings": { "target": "com.amazonaws.sagemaker#AmazonQSettings", "traits": { - "smithy.api#documentation": "A collection of settings that configure the Amazon Q experience within the domain. The\n AuthMode that you use to create the domain must be SSO.
A collection of settings that configure the Amazon Q experience within the domain. The AuthMode that you use to create the domain must be SSO.
The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker\n Unified Studio.
" + "smithy.api#documentation": "The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
" } } }, "traits": { - "smithy.api#documentation": "A collection of settings that apply to the SageMaker Domain. These settings\n are specified through the CreateDomain API call.
A collection of settings that apply to the SageMaker Domain. These settings are specified through the CreateDomain API call.
A collection of RStudioServerPro Domain-level app settings to update. A\n single RStudioServerPro application is created for a domain.
A collection of RStudioServerPro Domain-level app settings to update. A single RStudioServerPro application is created for a domain.
The configuration for attaching a SageMaker AI user profile name to the execution\n role as a sts:SourceIdentity key. This configuration can only be modified if there are no\n apps in the InService or Pending state.
The configuration for attaching a SageMaker AI user profile name to the execution role as a sts:SourceIdentity key. This configuration can only be modified if there are no apps in the InService or Pending state.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for\n communication between Domain-level apps and user apps.
The security groups for the Amazon Virtual Private Cloud that the Domain uses for communication between Domain-level apps and user apps.
The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker\n Unified Studio.
" + "smithy.api#documentation": "The settings that apply to an SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
" } } }, @@ -28873,30 +28858,30 @@ "Bias": { "target": "com.amazonaws.sagemaker#DriftCheckBias", "traits": { - "smithy.api#documentation": "Represents the drift check bias baselines that can be used when the model monitor is\n set using the model package.
" + "smithy.api#documentation": "Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
" } }, "Explainability": { "target": "com.amazonaws.sagemaker#DriftCheckExplainability", "traits": { - "smithy.api#documentation": "Represents the drift check explainability baselines that can be used when the model\n monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
" } }, "ModelQuality": { "target": "com.amazonaws.sagemaker#DriftCheckModelQuality", "traits": { - "smithy.api#documentation": "Represents the drift check model quality baselines that can be used when the model\n monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
" } }, "ModelDataQuality": { "target": "com.amazonaws.sagemaker#DriftCheckModelDataQuality", "traits": { - "smithy.api#documentation": "Represents the drift check model data quality baselines that can be used when the\n model monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
" } } }, "traits": { - "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set\n using the model package.
" + "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set using the model package.
" } }, "com.amazonaws.sagemaker#DriftCheckBias": { @@ -28922,7 +28907,7 @@ } }, "traits": { - "smithy.api#documentation": "Represents the drift check bias baselines that can be used when the model monitor is\n set using the model package.
" + "smithy.api#documentation": "Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
" } }, "com.amazonaws.sagemaker#DriftCheckExplainability": { @@ -28942,7 +28927,7 @@ } }, "traits": { - "smithy.api#documentation": "Represents the drift check explainability baselines that can be used when the model\n monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
" } }, "com.amazonaws.sagemaker#DriftCheckModelDataQuality": { @@ -28962,7 +28947,7 @@ } }, "traits": { - "smithy.api#documentation": "Represents the drift check data quality baselines that can be used when the model\n monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
" } }, "com.amazonaws.sagemaker#DriftCheckModelQuality": { @@ -28982,7 +28967,7 @@ } }, "traits": { - "smithy.api#documentation": "Represents the drift check model quality baselines that can be used when the model\n monitor is set using the model package.
" + "smithy.api#documentation": "Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
" } }, "com.amazonaws.sagemaker#DynamicScalingConfiguration": { @@ -29036,7 +29021,7 @@ } }, "traits": { - "smithy.api#documentation": "A file system, created by you in Amazon EFS, that you assign to a user profile or\n space for an Amazon SageMaker AI Domain. Permitted users can access this file system in\n Amazon SageMaker AI Studio.
" + "smithy.api#documentation": "A file system, created by you in Amazon EFS, that you assign to a user profile or space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" } }, "com.amazonaws.sagemaker#EFSFileSystemConfig": { @@ -29053,12 +29038,12 @@ "FileSystemPath": { "target": "com.amazonaws.sagemaker#FileSystemPath", "traits": { - "smithy.api#documentation": "The path to the file system directory that is accessible in Amazon SageMaker AI Studio.\n Permitted users can access only this directory and below.
" + "smithy.api#documentation": "The path to the file system directory that is accessible in Amazon SageMaker AI Studio. Permitted users can access only this directory and below.
" } } }, "traits": { - "smithy.api#documentation": "The settings for assigning a custom Amazon EFS file system to a user profile or\n space for an Amazon SageMaker AI Domain.
" + "smithy.api#documentation": "The settings for assigning a custom Amazon EFS file system to a user profile or space for an Amazon SageMaker AI Domain.
" } }, "com.amazonaws.sagemaker#EMRStepMetadata": { @@ -29085,7 +29070,7 @@ "LogFilePath": { "target": "com.amazonaws.sagemaker#String1024", "traits": { - "smithy.api#documentation": "The path to the log file where the cluster step's failure root cause \n is recorded.
" + "smithy.api#documentation": "The path to the log file where the cluster step's failure root cause is recorded.
" } } }, @@ -29127,7 +29112,7 @@ "AssociationType": { "target": "com.amazonaws.sagemaker#AssociationEdgeType", "traits": { - "smithy.api#documentation": "The type of the Association(Edge) between the source and destination. For example ContributedTo, \n Produced, or DerivedFrom.
The type of the Association(Edge) between the source and destination. For example ContributedTo, Produced, or DerivedFrom.
Toggle that determines whether to rollback to previous configuration if the current\n deployment fails. By default this is turned on. You may turn this off if you want to\n investigate the errors yourself.
", + "smithy.api#documentation": "Toggle that determines whether to rollback to previous configuration if the current deployment fails. By default this is turned on. You may turn this off if you want to investigate the errors yourself.
", "smithy.api#required": {} } } @@ -29288,7 +29273,7 @@ "target": "com.amazonaws.sagemaker#Integer", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of edge devices yet to pick up the deployment in current stage, or in\n progress.
", + "smithy.api#documentation": "The number of edge devices yet to pick up the deployment in current stage, or in progress.
", "smithy.api#required": {} } }, @@ -29465,19 +29450,19 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. \n If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume after compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
" } }, "PresetDeploymentType": { "target": "com.amazonaws.sagemaker#EdgePresetDeploymentType", "traits": { - "smithy.api#documentation": "The deployment type SageMaker Edge Manager will create. \n Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
" + "smithy.api#documentation": "The deployment type SageMaker Edge Manager will create. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
" } }, "PresetDeploymentConfig": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The configuration used to create deployment artifacts. \n Specify configuration options with a JSON string. The available configuration options for each type are:
\n\n ComponentName (optional) - Name of the GreenGrass V2 component. If not specified,\n the default name generated consists of \"SagemakerEdgeManager\" and the name of your SageMaker Edge Manager\n packaging job.
\n ComponentDescription (optional) - Description of the component.
\n ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a\n major.minor.patch number system. For example, version 1.0.0 represents the first\n major release for a component. For more information, see the semantic version specification.
\n\n PlatformOS (optional) - The name of the operating system for the platform.\n Supported platforms include Windows and Linux.
\n PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
\nSupported architectures for Linux include: Linux x86_64, Linux ARMV8.
\nThe configuration used to create deployment artifacts. Specify configuration options with a JSON string. The available configuration options for each type are:
ComponentName (optional) - Name of the GreenGrass V2 component. If not specified, the default name generated consists of \"SagemakerEdgeManager\" and the name of your SageMaker Edge Manager packaging job.
ComponentDescription (optional) - Description of the component.
ComponentVersion (optional) - The version of the component.
Amazon Web Services IoT Greengrass uses semantic versions for components. Semantic versions follow a major.minor.patch number system. For example, version 1.0.0 represents the first major release for a component. For more information, see the semantic version specification.
PlatformOS (optional) - The name of the operating system for the platform. Supported platforms include Windows and Linux.
PlatformArchitecture (optional) - The processor architecture for the platform.
Supported architectures Windows include: Windows32_x86, Windows64_x64.
Supported architectures for Linux include: Linux x86_64, Linux ARMV8.
The deployment type created by SageMaker Edge Manager. Currently only \n supports Amazon Web Services IoT Greengrass Version 2 components.
", + "smithy.api#documentation": "The deployment type created by SageMaker Edge Manager. Currently only supports Amazon Web Services IoT Greengrass Version 2 components.
", "smithy.api#required": {} } }, @@ -29718,13 +29703,13 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ARN of the IAM role granting the AutoML job V2 the necessary\n permissions access policies to list, connect to, or manage EMR Serverless jobs. For\n detailed information about the required permissions of this role, see \"How to configure\n AutoML to initiate a remote job on EMR Serverless for large datasets\" in Create a regression or classification job for tabular data using the AutoML API\n or Create an AutoML job for time-series forecasting using the API.
", + "smithy.api#documentation": "The ARN of the IAM role granting the AutoML job V2 the necessary permissions access policies to list, connect to, or manage EMR Serverless jobs. For detailed information about the required permissions of this role, see \"How to configure AutoML to initiate a remote job on EMR Serverless for large datasets\" in Create a regression or classification job for tabular data using the AutoML API or Create an AutoML job for time-series forecasting using the API.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "This data type is intended for use exclusively by SageMaker Canvas and cannot be used in\n other contexts at the moment.
\nSpecifies the compute configuration for the EMR Serverless job.
" + "smithy.api#documentation": "This data type is intended for use exclusively by SageMaker Canvas and cannot be used in other contexts at the moment.
Specifies the compute configuration for the EMR Serverless job.
" } }, "com.amazonaws.sagemaker#EmrServerlessSettings": { @@ -29733,13 +29718,13 @@ "ExecutionRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services IAM role that is assumed for\n running Amazon EMR Serverless jobs in SageMaker Canvas. This role should have the necessary\n permissions to read and write data attached and a trust relationship with\n EMR Serverless.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services IAM role that is assumed for running Amazon EMR Serverless jobs in SageMaker Canvas. This role should have the necessary permissions to read and write data attached and a trust relationship with EMR Serverless.
" } }, "Status": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "Describes whether Amazon EMR Serverless job capabilities are enabled or disabled in the SageMaker\n Canvas application.
" + "smithy.api#documentation": "Describes whether Amazon EMR Serverless job capabilities are enabled or disabled in the SageMaker Canvas application.
" } } }, @@ -29753,18 +29738,18 @@ "AssumableRoleArns": { "target": "com.amazonaws.sagemaker#AssumableRoleArns", "traits": { - "smithy.api#documentation": "An array of Amazon Resource Names (ARNs) of the IAM roles that the execution role of\n SageMaker can assume for performing operations or tasks related to Amazon EMR clusters or Amazon EMR\n Serverless applications. These roles define the permissions and access policies required\n when performing Amazon EMR-related operations, such as listing, connecting to, or terminating\n Amazon EMR clusters or Amazon EMR Serverless applications. They are typically used in\n cross-account access scenarios, where the Amazon EMR resources (clusters or serverless\n applications) are located in a different Amazon Web Services account than the SageMaker\n domain.
" + "smithy.api#documentation": "An array of Amazon Resource Names (ARNs) of the IAM roles that the execution role of SageMaker can assume for performing operations or tasks related to Amazon EMR clusters or Amazon EMR Serverless applications. These roles define the permissions and access policies required when performing Amazon EMR-related operations, such as listing, connecting to, or terminating Amazon EMR clusters or Amazon EMR Serverless applications. They are typically used in cross-account access scenarios, where the Amazon EMR resources (clusters or serverless applications) are located in a different Amazon Web Services account than the SageMaker domain.
" } }, "ExecutionRoleArns": { "target": "com.amazonaws.sagemaker#ExecutionRoleArns", "traits": { - "smithy.api#documentation": "An array of Amazon Resource Names (ARNs) of the IAM roles used by the Amazon EMR cluster instances\n or job execution environments to access other Amazon Web Services services and resources needed during the \n runtime of your Amazon EMR or Amazon EMR Serverless workloads, such as Amazon S3 for data access, Amazon CloudWatch for logging, or other\n Amazon Web Services services based on the particular workload requirements.
" + "smithy.api#documentation": "An array of Amazon Resource Names (ARNs) of the IAM roles used by the Amazon EMR cluster instances or job execution environments to access other Amazon Web Services services and resources needed during the runtime of your Amazon EMR or Amazon EMR Serverless workloads, such as Amazon S3 for data access, Amazon CloudWatch for logging, or other Amazon Web Services services based on the particular workload requirements.
" } } }, "traits": { - "smithy.api#documentation": "The configuration parameters that specify the IAM roles assumed by the execution role of \n SageMaker (assumable roles) and the cluster instances or job execution environments \n (execution roles or runtime roles) to manage and access resources required for running Amazon EMR\n clusters or Amazon EMR Serverless applications.
" + "smithy.api#documentation": "The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
" } }, "com.amazonaws.sagemaker#EnableCapture": { @@ -29788,7 +29773,7 @@ "target": "com.amazonaws.sagemaker#EnableSagemakerServicecatalogPortfolioOutput" }, "traits": { - "smithy.api#documentation": "Enables using Service Catalog in SageMaker. Service Catalog is used to create\n SageMaker projects.
" + "smithy.api#documentation": "Enables using Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
" } }, "com.amazonaws.sagemaker#EnableSagemakerServicecatalogPortfolioInput": { @@ -29855,7 +29840,7 @@ "ProductionVariants": { "target": "com.amazonaws.sagemaker#ProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "A list of the production variants hosted on the endpoint. Each production variant is a\n model.
" + "smithy.api#documentation": "A list of the production variants hosted on the endpoint. Each production variant is a model.
" } }, "DataCaptureConfig": { @@ -29894,19 +29879,19 @@ "MonitoringSchedules": { "target": "com.amazonaws.sagemaker#MonitoringScheduleList", "traits": { - "smithy.api#documentation": "A list of monitoring schedules for the endpoint. For information about model\n monitoring, see Amazon SageMaker Model Monitor.
" + "smithy.api#documentation": "A list of monitoring schedules for the endpoint. For information about model monitoring, see Amazon SageMaker Model Monitor.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
" + "smithy.api#documentation": "A list of the tags associated with the endpoint. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } }, "ShadowProductionVariants": { "target": "com.amazonaws.sagemaker#ProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "A list of the shadow variants hosted on the endpoint. Each shadow variant is a model\n in shadow mode with production traffic replicated from the production variant.
" + "smithy.api#documentation": "A list of the shadow variants hosted on the endpoint. Each shadow variant is a model in shadow mode with production traffic replicated from the production variant.
" } } }, @@ -30044,7 +30029,7 @@ "target": "com.amazonaws.sagemaker#EndpointName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An endpoint in customer's account which has enabled DataCaptureConfig\n enabled.
An endpoint in customer's account which has enabled DataCaptureConfig enabled.
Whether the Pipe or File is used as the input mode for\n transferring data for the monitoring job. Pipe mode is recommended for large\n datasets. File mode is useful for small files that fit in memory. Defaults to\n File.
Whether the Pipe or File is used as the input mode for transferring data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
Whether input data distributed in Amazon S3 is fully replicated or sharded by an\n Amazon S3 key. Defaults to FullyReplicated\n
Whether input data distributed in Amazon S3 is fully replicated or sharded by an Amazon S3 key. Defaults to FullyReplicated
If specified, monitoring jobs substract this time from the start time. For information\n about using offsets for scheduling monitoring jobs, see Schedule Model\n Quality Monitoring Jobs.
" + "smithy.api#documentation": "If specified, monitoring jobs substract this time from the start time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
" } }, "EndTimeOffset": { "target": "com.amazonaws.sagemaker#MonitoringTimeOffsetString", "traits": { - "smithy.api#documentation": "If specified, monitoring jobs substract this time from the end time. For information\n about using offsets for scheduling monitoring jobs, see Schedule Model\n Quality Monitoring Jobs.
" + "smithy.api#documentation": "If specified, monitoring jobs substract this time from the end time. For information about using offsets for scheduling monitoring jobs, see Schedule Model Quality Monitoring Jobs.
" } }, "ExcludeFeaturesAttribute": { @@ -30176,13 +30161,13 @@ "EndpointStatus": { "target": "com.amazonaws.sagemaker#EndpointStatus", "traits": { - "smithy.api#documentation": "\n The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.\n
" + "smithy.api#documentation": "The status of the endpoint. For possible values of the status of an endpoint, see EndpointSummary.
" } }, "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "\n If the status of the endpoint is Failed, or the status is InService but update\n operation fails, this provides the reason why it failed.\n
If the status of the endpoint is Failed, or the status is InService but update operation fails, this provides the reason why it failed.
The status of the endpoint.
\n\n OutOfService: Endpoint is not available to take incoming\n requests.
\n Creating: CreateEndpoint is executing.
\n Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
\n SystemUpdating: Endpoint is undergoing maintenance and cannot be\n updated or deleted or re-scaled until it has completed. This maintenance\n operation does not change any customer-specified values such as VPC config, KMS\n encryption, model, instance type, or instance count.
\n RollingBack: Endpoint fails to scale up or down or change its\n variant weight and is in the process of rolling back to its previous\n configuration. Once the rollback completes, endpoint returns to an\n InService status. This transitional status only applies to an\n endpoint that has autoscaling enabled and is undergoing variant weight or\n capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called\n explicitly.
\n InService: Endpoint is available to process incoming\n requests.
\n Deleting: DeleteEndpoint is executing.
\n Failed: Endpoint could not be created, updated, or re-scaled. Use\n DescribeEndpointOutput$FailureReason for information about the\n failure. DeleteEndpoint is the only operation that can be performed on a\n failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals\n filter with a call to ListEndpoints.
The status of the endpoint.
OutOfService: Endpoint is not available to take incoming requests.
Creating: CreateEndpoint is executing.
Updating: UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or deleted or re-scaled until it has completed. This maintenance operation does not change any customer-specified values such as VPC config, KMS encryption, model, instance type, or instance count.
RollingBack: Endpoint fails to scale up or down or change its variant weight and is in the process of rolling back to its previous configuration. Once the rollback completes, endpoint returns to an InService status. This transitional status only applies to an endpoint that has autoscaling enabled and is undergoing variant weight or capacity changes as part of an UpdateEndpointWeightsAndCapacities call or when the UpdateEndpointWeightsAndCapacities operation is called explicitly.
InService: Endpoint is available to process incoming requests.
Deleting: DeleteEndpoint is executing.
Failed: Endpoint could not be created, updated, or re-scaled. Use DescribeEndpointOutput$FailureReason for information about the failure. DeleteEndpoint is the only operation that can be performed on a failed endpoint.
To get a list of endpoints with a specified status, use the StatusEquals filter with a call to ListEndpoints.
The name of the experiment as displayed. If DisplayName isn't specified,\n ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
The properties of an experiment as returned by the Search API.\n For information about experiments, see the \n CreateExperiment API.
" + "smithy.api#documentation": "The properties of an experiment as returned by the Search API. For information about experiments, see the CreateExperiment API.
" } }, "com.amazonaws.sagemaker#ExperimentArn": { @@ -30758,13 +30743,13 @@ "TrialName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of an existing trial to associate the trial component with. If not specified, a\n new trial is created.
" + "smithy.api#documentation": "The name of an existing trial to associate the trial component with. If not specified, a new trial is created.
" } }, "TrialComponentDisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The display name for the trial component. If this key isn't specified, the display name is\n the trial component name.
" + "smithy.api#documentation": "The display name for the trial component. If this key isn't specified, the display name is the trial component name.
" } }, "RunName": { @@ -30775,7 +30760,7 @@ } }, "traits": { - "smithy.api#documentation": "Associates a SageMaker job as a trial component with an experiment and trial. Specified when\n you call the following APIs:
\n\n CreateProcessingJob\n
\n\n CreateTrainingJob\n
\n\n CreateTransformJob\n
\nAssociates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
" } }, "com.amazonaws.sagemaker#ExperimentDescription": { @@ -30864,7 +30849,7 @@ "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the experiment as displayed. If DisplayName isn't specified,\n ExperimentName is displayed.
The name of the experiment as displayed. If DisplayName isn't specified, ExperimentName is displayed.
A summary of the properties of an experiment. To get the complete set of properties, call\n the DescribeExperiment API and provide the\n ExperimentName.
A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.
A member of ExplainerConfig that contains configuration parameters for\n the SageMaker Clarify explainer.
A member of ExplainerConfig that contains configuration parameters for the SageMaker Clarify explainer.
The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted\n users can access only this directory and below.
" + "smithy.api#documentation": "The path to the file system directory that is accessible in Amazon SageMaker Studio. Permitted users can access only this directory and below.
" } } }, "traits": { - "smithy.api#documentation": "The settings for assigning a custom Amazon FSx for Lustre file system to a user profile or space for an\n Amazon SageMaker Domain.
" + "smithy.api#documentation": "The settings for assigning a custom Amazon FSx for Lustre file system to a user profile or space for an Amazon SageMaker Domain.
" } }, "com.amazonaws.sagemaker#FailStepMetadata": { @@ -30976,7 +30961,7 @@ "ErrorMessage": { "target": "com.amazonaws.sagemaker#String3072", "traits": { - "smithy.api#documentation": "A message that you define and then is processed and rendered by \n the Fail step when the error occurs.
" + "smithy.api#documentation": "A message that you define and then is processed and rendered by the Fail step when the error occurs.
" } } }, @@ -31055,7 +31040,7 @@ "target": "com.amazonaws.sagemaker#FeatureName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of a feature. The type must be a string. FeatureName cannot be any\n of the following: is_deleted, write_time,\n api_invocation_time.
The name:
\nMust start with an alphanumeric character.
\nCan only include alphanumeric characters, underscores, and hyphens. Spaces are not\n allowed.
\nThe name of a feature. The type must be a string. FeatureName cannot be any of the following: is_deleted, write_time, api_invocation_time.
The name:
Must start with an alphanumeric character.
Can only include alphanumeric characters, underscores, and hyphens. Spaces are not allowed.
A grouping of elements where each element within the collection must have the same\n feature type (String, Integral, or\n Fractional).
\n List: An ordered collection of elements.
\n Set: An unordered collection of unique elements.
\n Vector: A specialized list that represents a fixed-size array of\n elements. The vector dimension is determined by you. Must have elements with\n fractional feature types.
A grouping of elements where each element within the collection must have the same feature type (String, Integral, or Fractional).
List: An ordered collection of elements.
Set: An unordered collection of unique elements.
Vector: A specialized list that represents a fixed-size array of elements. The vector dimension is determined by you. Must have elements with fractional feature types.
A list of features. You must include FeatureName and\n FeatureType. Valid feature FeatureTypes are\n Integral, Fractional and String.
A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.
The name of the Feature whose value uniquely identifies a\n Record defined in the FeatureGroup\n FeatureDefinitions.
The name of the Feature whose value uniquely identifies a Record defined in the FeatureGroup FeatureDefinitions.
The name of the feature that stores the EventTime of a Record in a\n FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to\n the creation or update of a Record in FeatureGroup. All\n Records in the FeatureGroup must have a corresponding\n EventTime.
The name of the feature that stores the EventTime of a Record in a FeatureGroup.
A EventTime is point in time when a new event occurs that corresponds to the creation or update of a Record in FeatureGroup. All Records in the FeatureGroup must have a corresponding EventTime.
A list of Features. Each Feature must include a\n FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and\n String.
\n FeatureNames cannot be any of the following: is_deleted,\n write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per\n FeatureGroup.
A list of Features. Each Feature must include a FeatureName and a FeatureType.
Valid FeatureTypes are Integral, Fractional and String.
FeatureNames cannot be any of the following: is_deleted, write_time, api_invocation_time.
You can create up to 2,500 FeatureDefinitions per FeatureGroup.
The Amazon Resource Name (ARN) of the IAM execution role used to create the feature\n group.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM execution role used to create the feature group.
" } }, "FeatureGroupStatus": { @@ -31181,7 +31166,7 @@ "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "The reason that the FeatureGroup failed to be replicated in the\n OfflineStore. This is failure may be due to a failure to create a\n FeatureGroup in or delete a FeatureGroup from the\n OfflineStore.
The reason that the FeatureGroup failed to be replicated in the OfflineStore. This is failure may be due to a failure to create a FeatureGroup in or delete a FeatureGroup from the OfflineStore.
Amazon SageMaker Feature Store stores features in a collection called Feature Group. A\n Feature Group can be visualized as a table which has rows, with a unique identifier for\n each row where each column in the table is a feature. In principle, a Feature Group is\n composed of features and values per features.
" + "smithy.api#documentation": "Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
" } }, "com.amazonaws.sagemaker#FeatureGroupArn": { @@ -31359,25 +31344,25 @@ "target": "com.amazonaws.sagemaker#Timestamp", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A timestamp indicating the time of creation time of the\n FeatureGroup.
A timestamp indicating the time of creation time of the FeatureGroup.
The status of a FeatureGroup. The status can be any of the following:\n Creating, Created, CreateFail,\n Deleting or DetailFail.
The status of a FeatureGroup. The status can be any of the following: Creating, Created, CreateFail, Deleting or DetailFail.
Notifies you if replicating data into the OfflineStore has failed. Returns\n either: Active or Blocked.
Notifies you if replicating data into the OfflineStore has failed. Returns either: Active or Blocked.
The name, ARN, CreationTime, FeatureGroup values,\n LastUpdatedTime and EnableOnlineStorage status of a\n FeatureGroup.
The name, ARN, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.
The metadata for a feature. It can either be metadata that you specify, or metadata that\n is updated automatically.
" + "smithy.api#documentation": "The metadata for a feature. It can either be metadata that you specify, or metadata that is updated automatically.
" } }, "com.amazonaws.sagemaker#FeatureName": { @@ -31613,7 +31598,7 @@ "MountPath": { "target": "com.amazonaws.sagemaker#MountPath", "traits": { - "smithy.api#documentation": "The path within the image to mount the user's EFS home directory. The directory\n should be empty. If not specified, defaults to /home/sagemaker-user.
" + "smithy.api#documentation": "The path within the image to mount the user's EFS home directory. The directory should be empty. If not specified, defaults to /home/sagemaker-user.
" } }, "DefaultUid": { @@ -31648,7 +31633,7 @@ "target": "com.amazonaws.sagemaker#FileSystemAccessMode", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The access mode of the mount of the directory associated with the channel. A directory\n can be mounted either in ro (read-only) or rw (read-write)\n mode.
The access mode of the mount of the directory associated with the channel. A directory can be mounted either in ro (read-only) or rw (read-write) mode.
A resource property name. For example, TrainingJobName. For valid property\n names, see SearchRecord. You must\n specify a valid property for the resource.
A resource property name. For example, TrainingJobName. For valid property names, see SearchRecord. You must specify a valid property for the resource.
A Boolean binary operator that is used to evaluate the filter. The operator field contains\n one of the following values:
\nThe value of Name equals Value.
The value of Name doesn't equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for\n text properties.
The value of Name is greater than or equal to Value. Not\n supported for text properties.
The value of Name is less than Value. Not supported for\n text properties.
The value of Name is less than or equal to Value. Not\n supported for text properties.
The value of Name is one of the comma delimited strings in\n Value. Only supported for text properties.
The value of Name contains the string Value. Only\n supported for text properties.
A SearchExpression can include the Contains operator\n multiple times when the value of Name is one of the following:
\n Experiment.DisplayName\n
\n Experiment.ExperimentName\n
\n Experiment.Tags\n
\n Trial.DisplayName\n
\n Trial.TrialName\n
\n Trial.Tags\n
\n TrialComponent.DisplayName\n
\n TrialComponent.TrialComponentName\n
\n TrialComponent.Tags\n
\n TrialComponent.InputArtifacts\n
\n TrialComponent.OutputArtifacts\n
A SearchExpression can include only one Contains operator\n for all other values of Name. In these cases, if you include multiple\n Contains operators in the SearchExpression, the result is\n the following error message: \"'CONTAINS' operator usage limit of 1\n exceeded.\"
A Boolean binary operator that is used to evaluate the filter. The operator field contains one of the following values:
The value of Name equals Value.
The value of Name doesn't equal Value.
The Name property exists.
The Name property does not exist.
The value of Name is greater than Value. Not supported for text properties.
The value of Name is greater than or equal to Value. Not supported for text properties.
The value of Name is less than Value. Not supported for text properties.
The value of Name is less than or equal to Value. Not supported for text properties.
The value of Name is one of the comma delimited strings in Value. Only supported for text properties.
The value of Name contains the string Value. Only supported for text properties.
A SearchExpression can include the Contains operator multiple times when the value of Name is one of the following:
Experiment.DisplayName
Experiment.ExperimentName
Experiment.Tags
Trial.DisplayName
Trial.TrialName
Trial.Tags
TrialComponent.DisplayName
TrialComponent.TrialComponentName
TrialComponent.Tags
TrialComponent.InputArtifacts
TrialComponent.OutputArtifacts
A SearchExpression can include only one Contains operator for all other values of Name. In these cases, if you include multiple Contains operators in the SearchExpression, the result is the following error message: \"'CONTAINS' operator usage limit of 1 exceeded.\"
A value used with Name and Operator to determine which resources\n satisfy the filter's condition. For numerical properties, Value must be an\n integer or floating-point decimal. For timestamp properties, Value must be an ISO\n 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
A value used with Name and Operator to determine which resources satisfy the filter's condition. For numerical properties, Value must be an integer or floating-point decimal. For timestamp properties, Value must be an ISO 8601 date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
A conditional statement for a search expression that includes a resource property, a\n Boolean operator, and a value. Resources that match the statement are returned in the results\n from the Search API.
\nIf you specify a Value, but not an Operator, SageMaker uses the\n equals operator.
In search, there are several property types:
\nTo define a metric filter, enter a value using the form\n \"Metrics., where \"accuracy\" metric greater than \"0.9\":
\n {\n
\n \"Name\": \"Metrics.accuracy\",\n
\n \"Operator\": \"GreaterThan\",\n
\n \"Value\": \"0.9\"\n
\n }\n
To define a hyperparameter filter, enter a value with the form\n \"HyperParameters.. Decimal hyperparameter values are treated\n as a decimal in a comparison if the specified Value is also a decimal\n value. If the specified Value is an integer, the decimal hyperparameter\n values are treated as integers. For example, the following filter is satisfied by\n training jobs with a \"learning_rate\" hyperparameter that is less than\n \"0.5\":
\n {\n
\n \"Name\": \"HyperParameters.learning_rate\",\n
\n \"Operator\": \"LessThan\",\n
\n \"Value\": \"0.5\"\n
\n }\n
To define a tag filter, enter a value with the form\n Tags..
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
If you specify a Value, but not an Operator, SageMaker uses the equals operator.
In search, there are several property types:
To define a metric filter, enter a value using the form \"Metrics.<name>\", where <name> is a metric name. For example, the following filter searches for training jobs with an \"accuracy\" metric greater than \"0.9\":
{
\"Name\": \"Metrics.accuracy\",
\"Operator\": \"GreaterThan\",
\"Value\": \"0.9\"
}
To define a hyperparameter filter, enter a value with the form \"HyperParameters.<name>\". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a \"learning_rate\" hyperparameter that is less than \"0.5\":
{
\"Name\": \"HyperParameters.learning_rate\",
\"Operator\": \"LessThan\",
\"Value\": \"0.5\"
}
To define a tag filter, enter a value with the form Tags.<key>.
The name of the metric with the best result. For a description of the possible objective\n metrics, see AutoMLJobObjective$MetricName.
", + "smithy.api#documentation": "The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.
", "smithy.api#required": {} } }, @@ -31881,7 +31866,7 @@ "StandardMetricName": { "target": "com.amazonaws.sagemaker#AutoMLMetricEnum", "traits": { - "smithy.api#documentation": "The name of the standard metric. For a description of the standard metrics, see Autopilot\n candidate metrics.
" + "smithy.api#documentation": "The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.
" } } }, @@ -31895,14 +31880,14 @@ "Type": { "target": "com.amazonaws.sagemaker#HyperParameterTuningJobObjectiveType", "traits": { - "smithy.api#documentation": "Select if you want to minimize or maximize the objective metric during hyperparameter\n tuning.
" + "smithy.api#documentation": "Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
" } }, "MetricName": { "target": "com.amazonaws.sagemaker#MetricName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the objective metric. For SageMaker built-in algorithms, metrics are defined\n per algorithm. See the metrics for XGBoost as an\n example. You can also use a custom algorithm for training and define your own metrics.\n For more information, see Define metrics and environment variables.
", + "smithy.api#documentation": "The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the metrics for XGBoost as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see Define metrics and environment variables.
", "smithy.api#required": {} } }, @@ -31916,7 +31901,7 @@ } }, "traits": { - "smithy.api#documentation": "Shows the latest objective metric emitted by a training job that was launched by a\n hyperparameter tuning job. You define the objective metric in the\n HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
The Amazon S3 path where the object containing human output will be made available.
\nTo learn more about the format of Amazon A2I output data, see Amazon A2I\n Output Data.
", + "smithy.api#documentation": "The Amazon S3 path where the object containing human output will be made available.
To learn more about the format of Amazon A2I output data, see Amazon A2I Output Data.
", "smithy.api#required": {} } }, @@ -32259,12 +32244,12 @@ "AmazonBedrockRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The ARN of an Amazon Web Services IAM role that allows fine-tuning of large language models (LLMs) in\n Amazon Bedrock. The IAM role should have Amazon S3 read and write permissions, as well as a trust relationship that\n establishes bedrock.amazonaws.com as a service principal.
The ARN of an Amazon Web Services IAM role that allows fine-tuning of large language models (LLMs) in Amazon Bedrock. The IAM role should have Amazon S3 read and write permissions, as well as a trust relationship that establishes bedrock.amazonaws.com as a service principal.
The generative AI settings for the SageMaker Canvas application.
\nConfigure these settings for Canvas users starting chats with generative AI foundation models.\n For more information, see \n Use generative AI with foundation models.
" + "smithy.api#documentation": "The generative AI settings for the SageMaker Canvas application.
Configure these settings for Canvas users starting chats with generative AI foundation models. For more information, see Use generative AI with foundation models.
" } }, "com.amazonaws.sagemaker#GetDeviceFleetReport": { @@ -32417,7 +32402,7 @@ "target": "com.amazonaws.sagemaker#GetModelPackageGroupPolicyOutput" }, "traits": { - "smithy.api#documentation": "Gets a resource policy that manages access for a model group. For information about\n resource policies, see Identity-based\n policies and resource-based policies in the Amazon Web Services\n Identity and Access Management User Guide..
" + "smithy.api#documentation": "Gets a resource policy that manages access for a model group. For information about resource policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
" } }, "com.amazonaws.sagemaker#GetModelPackageGroupPolicyInput": { @@ -32461,7 +32446,7 @@ "target": "com.amazonaws.sagemaker#GetSagemakerServicecatalogPortfolioStatusOutput" }, "traits": { - "smithy.api#documentation": "Gets the status of Service Catalog in SageMaker. Service Catalog is used to create\n SageMaker projects.
" + "smithy.api#documentation": "Gets the status of Service Catalog in SageMaker. Service Catalog is used to create SageMaker projects.
" } }, "com.amazonaws.sagemaker#GetSagemakerServicecatalogPortfolioStatusInput": { @@ -32499,7 +32484,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies\n that you can apply to your SageMaker endpoint.
" + "smithy.api#documentation": "Starts an Amazon SageMaker Inference Recommender autoscaling recommendation job. Returns recommendations for autoscaling policies that you can apply to your SageMaker endpoint.
" } }, "com.amazonaws.sagemaker#GetScalingConfigurationRecommendationRequest": { @@ -32516,13 +32501,13 @@ "RecommendationId": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The recommendation ID of a previously completed inference recommendation. This ID should come from one of the\n recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The recommendation ID of a previously completed inference recommendation. This ID should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the EndpointName field.
The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the\n recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
The name of an endpoint benchmarked during a previously completed inference recommendation job. This name should come from one of the recommendations returned by the job specified in the InferenceRecommendationsJobName field.
Specify either this field or the RecommendationId field.
An auto-complete API for the search functionality in the SageMaker console. It returns\n suggestions of possible matches for the property name to use in Search queries.\n Provides suggestions for HyperParameters, Tags, and\n Metrics.
An auto-complete API for the search functionality in the SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.
A list of property names for a Resource that match a\n SuggestionQuery.
A list of property names for a Resource that match a SuggestionQuery.
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that\n contains the credentials used to access the git repository. The secret must have a\n staging label of AWSCURRENT and must be in the following format:
\n {\"username\": UserName, \"password\":\n Password}\n
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{\"username\": UserName, \"password\": Password}
Specifies configuration details for a Git repository in your Amazon Web Services\n account.
" + "smithy.api#documentation": "Specifies configuration details for a Git repository in your Amazon Web Services account.
" } }, "com.amazonaws.sagemaker#GitConfigForUpdate": { @@ -32683,12 +32668,12 @@ "SecretArn": { "target": "com.amazonaws.sagemaker#SecretArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that\n contains the credentials used to access the git repository. The secret must have a\n staging label of AWSCURRENT and must be in the following format:
\n {\"username\": UserName, \"password\":\n Password}\n
The Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the git repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{\"username\": UserName, \"password\": Password}
Specifies configuration details for a Git repository when the repository is\n updated.
" + "smithy.api#documentation": "Specifies configuration details for a Git repository when the repository is updated.
" } }, "com.amazonaws.sagemaker#GitConfigUrl": { @@ -32779,7 +32764,7 @@ } }, "traits": { - "smithy.api#documentation": "The SageMaker images that are hidden from the Studio user interface. You must specify the SageMaker\n image name and version aliases.
" + "smithy.api#documentation": "The SageMaker images that are hidden from the Studio user interface. You must specify the SageMaker image name and version aliases.
" } }, "com.amazonaws.sagemaker#HiddenSageMakerImageVersionAliasesList": { @@ -32812,12 +32797,12 @@ "CountryCode": { "target": "com.amazonaws.sagemaker#CountryCode", "traits": { - "smithy.api#documentation": "The country code for the holiday calendar.
\nFor the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your\n choice.
" + "smithy.api#documentation": "The country code for the holiday calendar.
For the list of public holiday calendars supported by AutoML job V2, see Country Codes. Use the country code corresponding to the country of your choice.
" } } }, "traits": { - "smithy.api#documentation": "Stores the holiday featurization attributes applicable to each item of time-series\n datasets during the training of a forecasting model. This allows the model to identify\n patterns associated with specific holidays.
" + "smithy.api#documentation": "Stores the holiday featurization attributes applicable to each item of time-series datasets during the training of a forecasting model. This allows the model to identify patterns associated with specific holidays.
" } }, "com.amazonaws.sagemaker#HookParameters": { @@ -32845,13 +32830,13 @@ "target": "com.amazonaws.sagemaker#HubContentArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ARN of your private model hub content. This should be a ModelReference\n resource type that points to a SageMaker JumpStart public hub model.
The ARN of your private model hub content. This should be a ModelReference resource type that points to a SageMaker JumpStart public hub model.
The configuration for a private hub model reference that points to a public SageMaker JumpStart model.
\nFor more information about private hubs, see Private curated hubs for foundation model access control in JumpStart.
" + "smithy.api#documentation": "The configuration for a private hub model reference that points to a public SageMaker JumpStart model.
For more information about private hubs, see Private curated hubs for foundation model access control in JumpStart.
" } }, "com.amazonaws.sagemaker#HubArn": { @@ -33407,20 +33392,30 @@ } } }, + "com.amazonaws.sagemaker#HumanLoopActivationConditions": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 0, + "max": 10240 + }, + "smithy.api#mediaType": "application/json" + } + }, "com.amazonaws.sagemaker#HumanLoopActivationConditionsConfig": { "type": "structure", "members": { "HumanLoopActivationConditions": { - "target": "com.amazonaws.sagemaker#SynthesizedJsonHumanLoopActivationConditions", + "target": "com.amazonaws.sagemaker#HumanLoopActivationConditions", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. \n The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see \n JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI \n in the Amazon SageMaker Developer Guide.
", + "smithy.api#documentation": "JSON expressing use-case specific conditions declaratively. If any condition is matched, atomic tasks are created against the configured work team. The set of conditions is different for Rekognition and Textract. For more information about how to structure the JSON, see JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI in the Amazon SageMaker Developer Guide.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required\n format of activation conditions.
" + "smithy.api#documentation": "Defines under what conditions SageMaker creates a human loop. Used within CreateFlowDefinition. See HumanLoopActivationConditionsConfig for the required format of activation conditions.
" } }, "com.amazonaws.sagemaker#HumanLoopActivationConfig": { @@ -33430,7 +33425,7 @@ "target": "com.amazonaws.sagemaker#HumanLoopActivationConditionsConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Container structure for defining under what conditions SageMaker creates a human\n loop.
", + "smithy.api#documentation": "Container structure for defining under what conditions SageMaker creates a human loop.
", "smithy.api#required": {} } } @@ -33446,7 +33441,7 @@ "target": "com.amazonaws.sagemaker#WorkteamArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Amazon Resource Name (ARN) of a team of workers. To learn more about the types of\n workforces and work teams you can create and use with Amazon A2I, see Create\n and Manage Workforces.
", + "smithy.api#documentation": "Amazon Resource Name (ARN) of a team of workers. To learn more about the types of workforces and work teams you can create and use with Amazon A2I, see Create and Manage Workforces.
", "smithy.api#required": {} } }, @@ -33454,7 +33449,7 @@ "target": "com.amazonaws.sagemaker#HumanTaskUiArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the human task user interface.
\nYou can use standard HTML and Crowd HTML Elements to create a custom worker task\n template. You use this template to create a human task UI.
\nTo learn how to create a custom HTML template, see Create Custom Worker\n Task Template.
\nTo learn how to create a human task UI, which is a worker task template that can be used\n in a flow definition, see Create and Delete a Worker Task Templates.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the human task user interface.
You can use standard HTML and Crowd HTML Elements to create a custom worker task template. You use this template to create a human task UI.
To learn how to create a custom HTML template, see Create Custom Worker Task Template.
To learn how to create a human task UI, which is a worker task template that can be used in a flow definition, see Create and Delete a Worker Task Templates.
", "smithy.api#required": {} } }, @@ -33478,7 +33473,7 @@ "target": "com.amazonaws.sagemaker#FlowDefinitionTaskCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of distinct workers who will perform the same task on each object.\n For example, if TaskCount is set to 3 for an image classification \n labeling job, three workers will classify each input image. \n Increasing TaskCount can improve label accuracy.
The number of distinct workers who will perform the same task on each object. For example, if TaskCount is set to 3 for an image classification labeling job, three workers will classify each input image. Increasing TaskCount can improve label accuracy.
The amount of time that a worker has to complete a task. The default value is 3,600\n seconds (1 hour).
" + "smithy.api#documentation": "The amount of time that a worker has to complete a task. The default value is 3,600 seconds (1 hour).
" } }, "TaskKeywords": { @@ -33515,7 +33510,7 @@ "target": "com.amazonaws.sagemaker#AwsManagedHumanLoopRequestSource", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. \n The default field settings and JSON parsing rules are different based on the integration source. Valid values:
", + "smithy.api#documentation": "Specifies whether Amazon Rekognition or Amazon Textract are used as the integration source. The default field settings and JSON parsing rules are different based on the integration source. Valid values:
", "smithy.api#required": {} } } @@ -33539,20 +33534,20 @@ "target": "com.amazonaws.sagemaker#UiConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Information about the user interface that workers use to complete the labeling\n task.
", + "smithy.api#documentation": "Information about the user interface that workers use to complete the labeling task.
", "smithy.api#required": {} } }, "PreHumanTaskLambdaArn": { "target": "com.amazonaws.sagemaker#LambdaFunctionArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Lambda function that is run before a data object\n is sent to a human worker. Use this function to provide input to a custom labeling\n job.
\nFor built-in\n task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for\n PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
\n Bounding box - Finds the most similar boxes from\n different workers based on the Jaccard index of the boxes.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox\n
\n Image classification - Uses a variant of the Expectation\n Maximization approach to estimate the true class of an image based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass\n
\n Multi-label image classification - Uses a variant of the Expectation\n Maximization approach to estimate the true classes of an image based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel\n
\n Semantic segmentation - Treats each pixel in an image as\n a multi-class classification and treats pixel annotations from workers as\n \"votes\" for the correct label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation\n
\n Text classification - Uses a variant of the Expectation\n Maximization approach to estimate the true class of text based on annotations\n from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass\n
\n Multi-label text classification - Uses a variant of the\n Expectation Maximization approach to estimate the true classes of text based on\n annotations from individual workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel\n
\n Named entity recognition - Groups similar selections and\n calculates aggregate boundaries, resolving to most-assigned label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition\n
\n Video Classification - Use this task type when you need workers to classify videos using\n predefined labels that you specify. Workers are shown videos and are asked to choose one\n label for each video.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass\n
\n Video Frame Object Detection - Use this task type to\n have workers identify and locate objects in a sequence of video frames (images extracted\n from a video) using bounding boxes. For example, you can use this task to ask workers to\n identify and localize various objects in a series of video frames, such as cars, bikes,\n and pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection\n
\n Video Frame Object Tracking - Use this task type to\n have workers track the movement of objects in a sequence of video frames (images\n extracted from a video) using bounding boxes. For example, you can use this task to ask\n workers to track the movement of objects, such as cars, bikes, and pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking\n
\n 3D Point Cloud Modalities\n
\nUse the following pre-annotation lambdas for 3D point cloud labeling modality tasks.\n See 3D Point Cloud Task types\n to learn more.
\n\n 3D Point Cloud Object Detection - \n Use this task type when you want workers to classify objects in a 3D point cloud by \n drawing 3D cuboids around objects. For example, you can use this task type to ask workers \n to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection\n
\n 3D Point Cloud Object Tracking - \n Use this task type when you want workers to draw 3D cuboids around objects\n that appear in a sequence of 3D point cloud frames. \n For example, you can use this task type to ask workers to track \n the movement of vehicles across multiple point cloud frames.\n
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking\n
\n 3D Point Cloud Semantic Segmentation - \n Use this task type when you want workers to create a point-level semantic segmentation masks by \n painting objects in a 3D point cloud using different colors where each color is assigned to one of \n the classes you specify.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation\n
\n Use the following ARNs for Label Verification and Adjustment Jobs\n
\nUse label verification and adjustment jobs to review and adjust labels. To learn more,\n see Verify and Adjust Labels .
\n\n Bounding box verification - Uses a variant of the\n Expectation Maximization approach to estimate the true class of verification\n judgement for bounding box labels based on annotations from individual\n workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox\n
\n Bounding box adjustment - Finds the most similar boxes\n from different workers based on the Jaccard index of the adjusted\n annotations.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox\n
\n Semantic segmentation verification - Uses a variant of\n the Expectation Maximization approach to estimate the true class of verification\n judgment for semantic segmentation labels based on annotations from individual\n workers.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation\n
\n Semantic segmentation adjustment - Treats each pixel in\n an image as a multi-class classification and treats pixel adjusted annotations\n from workers as \"votes\" for the correct label.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation\n
\n Video Frame Object Detection Adjustment - \n Use this task type when you want workers to adjust bounding boxes that workers have added \n to video frames to classify and localize objects in a sequence of video frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection\n
\n Video Frame Object Tracking Adjustment - \n Use this task type when you want workers to adjust bounding boxes that workers have added \n to video frames to track object movement across a sequence of video frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking\n
\n 3D point cloud object detection adjustment - Adjust\n 3D cuboids in a point cloud frame.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection\n
\n 3D point cloud object tracking adjustment - Adjust 3D\n cuboids across a sequence of point cloud frames.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking\n
\n 3D point cloud semantic segmentation adjustment -\n Adjust semantic segmentation masks in a 3D point cloud.
\n\n arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
\n arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation\n
The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.
For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda.
Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.
arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
3D Point Cloud Modalities
Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.
3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.
arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
Use the following ARNs for Label Verification and Adjustment Jobs
Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels .
Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox
Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.
arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as \"votes\" for the correct label.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.
arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
Keywords used to describe the task so that workers on Amazon Mechanical Turk can\n discover the task.
" + "smithy.api#documentation": "Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.
" } }, "TaskTitle": { @@ -33583,20 +33578,20 @@ "target": "com.amazonaws.sagemaker#TaskTimeLimitInSeconds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The amount of time that a worker has to complete a task.
\nIf you create a custom labeling job, the maximum value for this parameter is 8 hours\n (28,800 seconds).
\nIf you create a labeling job using a built-in task type the maximum\n for this parameter depends on the task type you use:
\nFor image and \n text labeling jobs,\n the maximum is 8 hours (28,800 seconds).
\nFor 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
\nThe amount of time that a worker has to complete a task.
If you create a custom labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
If you create a labeling job using a built-in task type the maximum for this parameter depends on the task type you use:
For image and text labeling jobs, the maximum is 8 hours (28,800 seconds).
For 3D point cloud and video frame labeling jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
The length of time that a task remains available for labeling by human workers. The\n default and maximum values for this parameter depend on the type of workforce you\n use.
\nIf you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds).\n The default is 6 hours (21,600 seconds).
\nIf you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
\nThe length of time that a task remains available for labeling by human workers. The default and maximum values for this parameter depend on the type of workforce you use.
If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600 seconds).
If you choose a private or vendor workforce, the default value is 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also 30 days.
Defines the maximum number of data objects that can be labeled by human workers at the\n same time. Also referred to as batch size. Each object may have more than one worker at one time.\n The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
" + "smithy.api#documentation": "Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects. To increase the maximum value to 5000 objects, contact Amazon Web Services Support.
" } }, "AnnotationConsolidationConfig": { @@ -33697,7 +33692,7 @@ "TrainingImage": { "target": "com.amazonaws.sagemaker#AlgorithmImage", "traits": { - "smithy.api#documentation": " The registry path of the Docker image that contains the training algorithm. For\n information about Docker registry paths for built-in algorithms, see Algorithms\n Provided by Amazon SageMaker: Common Parameters. SageMaker supports both\n registry/repository[:tag] and registry/repository[@digest]\n image path formats. For more information, see Using Your Own Algorithms with\n Amazon SageMaker.
The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
The name of the resource algorithm to use for the hyperparameter tuning job. If you\n specify a value for this parameter, do not specify a value for\n TrainingImage.
The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.
An array of MetricDefinition objects that specify the\n metrics\n that the algorithm emits.
" + "smithy.api#documentation": "An array of MetricDefinition objects that specify the metrics that the algorithm emits.
" } } }, "traits": { - "smithy.api#documentation": "Specifies\n which\n training algorithm to use for training jobs that a hyperparameter\n tuning job launches and the metrics to monitor.
" + "smithy.api#documentation": "Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
" } }, "com.amazonaws.sagemaker#HyperParameterKey": { @@ -33784,7 +33779,7 @@ "target": "com.amazonaws.sagemaker#ParameterType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The type of this hyperparameter. The valid types are Integer,\n Continuous, Categorical, and FreeText.
The type of this hyperparameter. The valid types are Integer, Continuous, Categorical, and FreeText.
Indicates whether this hyperparameter is tunable in a hyperparameter tuning\n job.
" + "smithy.api#documentation": "Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
" } }, "IsRequired": { @@ -33809,7 +33804,7 @@ "DefaultValue": { "target": "com.amazonaws.sagemaker#HyperParameterValue", "traits": { - "smithy.api#documentation": "The default value for this hyperparameter. If a default value is specified, a\n hyperparameter cannot be required.
" + "smithy.api#documentation": "The default value for this hyperparameter. If a default value is specified, a hyperparameter cannot be required.
" } } }, @@ -33847,14 +33842,14 @@ "StaticHyperParameters": { "target": "com.amazonaws.sagemaker#HyperParameters", "traits": { - "smithy.api#documentation": "Specifies the values of hyperparameters\n that\n do not change for the tuning job.
" + "smithy.api#documentation": "Specifies the values of hyperparameters that do not change for the tuning job.
" } }, "AlgorithmSpecification": { "target": "com.amazonaws.sagemaker#HyperParameterAlgorithmSpecification", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The HyperParameterAlgorithmSpecification object that\n specifies\n the resource algorithm to use for the training jobs that the tuning\n job launches.
", + "smithy.api#documentation": "The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
", "smithy.api#required": {} } }, @@ -33862,66 +33857,66 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the\n IAM\n role associated with the training jobs that the tuning job\n launches.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
", "smithy.api#required": {} } }, "InputDataConfig": { "target": "com.amazonaws.sagemaker#InputDataConfig", "traits": { - "smithy.api#documentation": "An array of Channel objects that\n specify\n the\n input for the training jobs that the tuning job launches.
" + "smithy.api#documentation": "An array of Channel objects that specify the input for the training jobs that the tuning job launches.
" } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "The VpcConfig object that specifies the VPC that you want the training jobs\n that this hyperparameter tuning job launches to connect to. Control access to and from\n your training container by configuring the VPC. For more information, see Protect Training Jobs\n by Using an Amazon Virtual Private Cloud.
" + "smithy.api#documentation": "The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
" } }, "OutputDataConfig": { "target": "com.amazonaws.sagemaker#OutputDataConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the path to the Amazon S3 bucket where you\n store\n model artifacts from the training jobs that the tuning job\n launches.
", + "smithy.api#documentation": "Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
", "smithy.api#required": {} } }, "ResourceConfig": { "target": "com.amazonaws.sagemaker#ResourceConfig", "traits": { - "smithy.api#documentation": "The resources,\n including\n the compute instances and storage volumes, to use for the training\n jobs that the tuning job launches.
\nStorage volumes store model artifacts and\n incremental\n states. Training algorithms might also use storage volumes for\n scratch\n space. If you want SageMaker to use the storage volume to store the\n training data, choose File as the TrainingInputMode in the\n algorithm specification. For distributed training algorithms, specify an instance count\n greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use\n HyperParameterTuningResourceConfig instead.
The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
The configuration for the hyperparameter tuning resources, including the compute\n instances and storage volumes, used for training jobs launched by the tuning job. By\n default, storage volumes hold model artifacts and incremental states. Choose\n File for TrainingInputMode in the\n AlgorithmSpecification parameter to additionally store training data in\n the storage volume (optional).
The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
Specifies a limit to how long a model hyperparameter training job can run. It also\n specifies how long a managed spot training job has to complete. When the job reaches the\n time limit, SageMaker ends the training job. Use this API to cap model training costs.
", + "smithy.api#documentation": "Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
", "smithy.api#required": {} } }, "EnableNetworkIsolation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Isolates the training container. No inbound or outbound network calls can be made,\n except for calls between peers within a training cluster for distributed training. If\n network isolation is used for training jobs that are configured to use a VPC, SageMaker\n downloads and uploads customer data and model artifacts through the specified VPC, but\n the training container does not have network access.
" + "smithy.api#documentation": "Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
" } }, "EnableInterContainerTrafficEncryption": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "To encrypt all communications between ML compute instances in distributed training,\n choose True. Encryption provides greater security for distributed training,\n but training might take longer. How long it takes depends on the amount of communication\n between compute instances, especially if you use a deep learning algorithm in\n distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
A Boolean indicating whether managed spot training is enabled (True) or\n not (False).
A Boolean indicating whether managed spot training is enabled (True) or not (False).
The number of times to retry the job when the job fails due to an\n InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See\n Define metrics and variables for more information.
\nThe maximum number of items specified for Map Entries refers to the\n maximum number of environment variables for each TrainingJobDefinition\n and also the maximum for the hyperparameter tuning job itself. That is, the sum of\n the number of environment variables for all the training job definitions can't\n exceed the maximum number specified.
An environment variable that you can pass into the SageMaker CreateTrainingJob API. You can use an existing environment variable from the training container or use your own. See Define metrics and variables for more information.
The maximum number of items specified for Map Entries refers to the maximum number of environment variables for each TrainingJobDefinition and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of environment variables for all the training job definitions can't exceed the maximum number specified.
Defines\n the training jobs launched by a hyperparameter tuning job.
" + "smithy.api#documentation": "Defines the training jobs launched by a hyperparameter tuning job.
" } }, "com.amazonaws.sagemaker#HyperParameterTrainingJobDefinitionName": { @@ -34055,14 +34050,14 @@ "TrainingEndTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Specifies the time when the training job ends on training instances. You are billed\n for the time interval between the value of TrainingStartTime and this time.\n For successful jobs and stopped jobs, this is the time after model artifacts are\n uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
The\n status\n of the training job.
", + "smithy.api#documentation": "The status of the training job.
", "smithy.api#required": {} } }, @@ -34070,26 +34065,26 @@ "target": "com.amazonaws.sagemaker#HyperParameters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A\n list of the hyperparameters for which you specified ranges to\n search.
", + "smithy.api#documentation": "A list of the hyperparameters for which you specified ranges to search.
", "smithy.api#required": {} } }, "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "The\n reason that the training job failed.\n
" + "smithy.api#documentation": "The reason that the training job failed.
" } }, "FinalHyperParameterTuningJobObjectiveMetric": { "target": "com.amazonaws.sagemaker#FinalHyperParameterTuningJobObjectiveMetric", "traits": { - "smithy.api#documentation": "The FinalHyperParameterTuningJobObjectiveMetric object that specifies the\n value\n of the\n objective\n metric of the tuning job that launched this training job.
" + "smithy.api#documentation": "The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
" } }, "ObjectiveStatus": { "target": "com.amazonaws.sagemaker#ObjectiveStatus", "traits": { - "smithy.api#documentation": "The status of the objective metric for the training job:
\nSucceeded: The\n final\n objective metric for the training job was evaluated by the\n hyperparameter tuning job and\n used\n in the hyperparameter tuning process.
\nPending: The training job is in progress and evaluation of its final objective\n metric is pending.
\nFailed:\n The final objective metric for the training job was not evaluated, and was not\n used in the hyperparameter tuning process. This typically occurs when the\n training job failed or did not emit an objective\n metric.
\nThe status of the objective metric for the training job:
Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
Pending: The training job is in progress and evaluation of its final objective metric is pending.
Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
The instance type used for processing of hyperparameter optimization jobs. Choose from\n general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge\n or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more\n information about instance types, see instance type\n descriptions.
", + "smithy.api#documentation": "The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.
", "smithy.api#required": {} } }, @@ -34123,7 +34118,7 @@ "target": "com.amazonaws.sagemaker#TrainingInstanceCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of instances of the type specified by InstanceType. Choose an\n instance count larger than 1 for distributed training algorithms. See Step 2:\n Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more\n information.
The number of instances of the type specified by InstanceType. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
The volume size in GB of the data to be processed for hyperparameter optimization\n (optional).
", + "smithy.api#documentation": "The volume size in GB of the data to be processed for hyperparameter optimization (optional).
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The configuration for hyperparameter tuning resources for use in training jobs\n launched by the tuning job. These resources include compute instances and storage\n volumes. Specify one or more compute instance configurations and allocation strategies\n to select resources (optional).
" + "smithy.api#documentation": "The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).
" } }, "com.amazonaws.sagemaker#HyperParameterTuningInstanceConfigs": { @@ -34168,18 +34163,18 @@ "NumberOfTrainingJobsObjectiveNotImproving": { "target": "com.amazonaws.sagemaker#Integer", "traits": { - "smithy.api#documentation": "The number of training jobs launched by a tuning job that are not improving (1% or\n less) as measured by model performance evaluated against an objective function.
" + "smithy.api#documentation": "The number of training jobs launched by a tuning job that are not improving (1% or less) as measured by model performance evaluated against an objective function.
" } }, "ConvergenceDetectedTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "The time in timestamp format that AMT detected model convergence, as defined by a lack\n of significant improvement over time based on criteria developed over a wide range of\n diverse benchmarking tests.
" + "smithy.api#documentation": "The time in timestamp format that AMT detected model convergence, as defined by a lack of significant improvement over time based on criteria developed over a wide range of diverse benchmarking tests.
" } } }, "traits": { - "smithy.api#documentation": "A structure that contains runtime information about both current and completed\n hyperparameter tuning jobs.
" + "smithy.api#documentation": "A structure that contains runtime information about both current and completed hyperparameter tuning jobs.
" } }, "com.amazonaws.sagemaker#HyperParameterTuningJobConfig": { @@ -34189,40 +34184,40 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobStrategyType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies how hyperparameter tuning chooses the combinations of hyperparameter values\n to use for the training job it launches. For information about search strategies, see\n How\n Hyperparameter Tuning Works.
", + "smithy.api#documentation": "Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
", "smithy.api#required": {} } }, "StrategyConfig": { "target": "com.amazonaws.sagemaker#HyperParameterTuningJobStrategyConfig", "traits": { - "smithy.api#documentation": "The configuration for the Hyperband optimization strategy. This parameter\n should be provided only if Hyperband is selected as the strategy for\n HyperParameterTuningJobConfig.
The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.
The HyperParameterTuningJobObjective specifies the objective metric used to\n evaluate the performance of training jobs launched by this tuning job.
" + "smithy.api#documentation": "The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.
" } }, "ResourceLimits": { "target": "com.amazonaws.sagemaker#ResourceLimits", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ResourceLimits\n object that specifies the maximum number of training and parallel training jobs that can\n be used for this hyperparameter tuning job.
", + "smithy.api#documentation": "The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.
", "smithy.api#required": {} } }, "ParameterRanges": { "target": "com.amazonaws.sagemaker#ParameterRanges", "traits": { - "smithy.api#documentation": "The ParameterRanges\n object that specifies the ranges of hyperparameters that this tuning job searches over\n to find the optimal configuration for the highest model performance against your chosen\n objective metric.
" + "smithy.api#documentation": "The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.
" } }, "TrainingJobEarlyStoppingType": { "target": "com.amazonaws.sagemaker#TrainingJobEarlyStoppingType", "traits": { - "smithy.api#documentation": "Specifies whether to use early stopping for training jobs launched by the\n hyperparameter tuning job. Because the Hyperband strategy has its own\n advanced internal early stopping mechanism, TrainingJobEarlyStoppingType\n must be OFF to use Hyperband. This parameter can take on one\n of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early\n stopping.
\nSageMaker stops training jobs launched by the hyperparameter tuning job when\n they are unlikely to perform better than previously completed training jobs.\n For more information, see Stop Training Jobs Early.
\nSpecifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):
Training jobs launched by the hyperparameter tuning job do not use early stopping.
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
A value used to initialize a pseudo-random number generator. Setting a random seed and\n using the same seed later for the same tuning job will allow hyperparameter optimization\n to find more a consistent hyperparameter configuration between the two runs.
" + "smithy.api#documentation": "A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.
" } } }, @@ -34281,13 +34276,13 @@ "target": "com.amazonaws.sagemaker#MetricName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The\n name of the metric to use for the objective metric.
", + "smithy.api#documentation": "The name of the metric to use for the objective metric.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning\n uses the value of this metric to evaluate the training jobs it launches, and returns the\n training job that results in either the highest or lowest value for this metric,\n depending on the value you specify for the Type parameter. If you want to\n define a custom objective metric, see Define metrics and environment variables.
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter. If you want to define a custom objective metric, see Define metrics and environment variables.
An entity returned by the SearchRecord API\n containing the properties of a hyperparameter tuning job.
" + "smithy.api#documentation": "An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
" } }, "com.amazonaws.sagemaker#HyperParameterTuningJobSortByOptions": { @@ -34484,12 +34479,12 @@ "HyperbandStrategyConfig": { "target": "com.amazonaws.sagemaker#HyperbandStrategyConfig", "traits": { - "smithy.api#documentation": "The configuration for the object that specifies the Hyperband strategy.\n This parameter is only supported for the Hyperband selection for\n Strategy within the HyperParameterTuningJobConfig API.
The configuration for the object that specifies the Hyperband strategy. This parameter is only supported for the Hyperband selection for Strategy within the HyperParameterTuningJobConfig API.
The configuration for a training job launched by a hyperparameter tuning job. Choose\n Bayesian for Bayesian optimization, and Random for random\n search optimization. For more advanced use cases, use Hyperband, which\n evaluates objective metrics for training jobs after every epoch. For more information about\n strategies, see How Hyperparameter\n Tuning Works.
The configuration for a training job launched by a hyperparameter tuning job. Choose Bayesian for Bayesian optimization, and Random for random search optimization. For more advanced use cases, use Hyperband, which evaluates objective metrics for training jobs after every epoch. For more information about strategies, see How Hyperparameter Tuning Works.
The strategy hyperparameter tuning uses to find the best combination of\n hyperparameters for your model.
" + "smithy.api#documentation": "The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model.
" } }, "com.amazonaws.sagemaker#HyperParameterTuningJobSummaries": { @@ -34545,7 +34540,7 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The\n Amazon\n Resource Name (ARN) of the tuning job.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the tuning job.
", "smithy.api#required": {} } }, @@ -34553,7 +34548,7 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The status of the\n tuning\n job.
", + "smithy.api#documentation": "The status of the tuning job.
", "smithy.api#required": {} } }, @@ -34561,7 +34556,7 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobStrategyType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the search strategy hyperparameter tuning uses to choose which\n hyperparameters to\n evaluate\n at each iteration.
", + "smithy.api#documentation": "Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to evaluate at each iteration.
", "smithy.api#required": {} } }, @@ -34582,14 +34577,14 @@ "LastModifiedTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "The date and time that the tuning job was\n modified.
" + "smithy.api#documentation": "The date and time that the tuning job was modified.
" } }, "TrainingJobStatusCounters": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The TrainingJobStatusCounters object that specifies the numbers of training\n jobs, categorized by status, that this tuning job launched.
", + "smithy.api#documentation": "The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.
", "smithy.api#required": {} } }, @@ -34597,14 +34592,14 @@ "target": "com.amazonaws.sagemaker#ObjectiveStatusCounters", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ObjectiveStatusCounters object that specifies the numbers of training jobs,\n categorized by objective metric status, that this tuning job launched.
", + "smithy.api#documentation": "The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.
", "smithy.api#required": {} } }, "ResourceLimits": { "target": "com.amazonaws.sagemaker#ResourceLimits", "traits": { - "smithy.api#documentation": "The ResourceLimits\n object that specifies the maximum number of training jobs and parallel training jobs\n allowed for this tuning job.
" + "smithy.api#documentation": "The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.
" } } }, @@ -34619,7 +34614,7 @@ "target": "com.amazonaws.sagemaker#ParentHyperParameterTuningJobs", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of hyperparameter tuning jobs that are used as the starting point for the new\n hyperparameter tuning job. For more information about warm starting a hyperparameter\n tuning job, see Using a Previous\n Hyperparameter Tuning Job as a Starting Point.
\nHyperparameter tuning jobs created before October 1, 2018 cannot be used as parent\n jobs for warm start tuning jobs.
", + "smithy.api#documentation": "An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.
Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.
", "smithy.api#required": {} } }, @@ -34627,13 +34622,13 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobWarmStartType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies one of the following:
\nThe new hyperparameter tuning job uses the same input data and training\n image as the parent tuning jobs. You can change the hyperparameter ranges to\n search and the maximum number of training jobs that the hyperparameter\n tuning job launches. You cannot use a new version of the training algorithm,\n unless the changes in the new version do not affect the algorithm itself.\n For example, changes that improve logging or adding support for a different\n data format are allowed. You can also change hyperparameters from tunable to\n static, and from static to tunable, but the total number of static plus\n tunable hyperparameters must remain the same as it is in all parent jobs.\n The objective metric for the new tuning job must be the same as for all\n parent jobs.
\nThe new hyperparameter tuning job can include input data, hyperparameter\n ranges, maximum number of concurrent training jobs, and maximum number of\n training jobs that are different than those of its parent hyperparameter\n tuning jobs. The training image can also be a different version from the\n version used in the parent hyperparameter tuning job. You can also change\n hyperparameters from tunable to static, and from static to tunable, but the\n total number of static plus tunable hyperparameters must remain the same as\n it is in all parent jobs. The objective metric for the new tuning job must\n be the same as for all parent jobs.
\nSpecifies one of the following:
The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.
Specifies the configuration for a hyperparameter tuning job that uses one or more\n previous hyperparameter tuning jobs as a starting point. The results of previous tuning\n jobs are used to inform which combinations of hyperparameters to search over in the new\n tuning job.
\nAll training jobs launched by the new hyperparameter tuning job are evaluated by using\n the objective metric, and the training job that performs the best is compared to the\n best training jobs from the parent tuning jobs. From these, the training job that\n performs the best as measured by the objective metric is returned as the overall best\n training job.
\nAll training jobs launched by parent hyperparameter tuning jobs and the new\n hyperparameter tuning jobs count against the limit of training jobs for the tuning\n job.
\nSpecifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
The instance type used to run hyperparameter optimization tuning jobs. See descriptions of\n instance types for more information.
" + "smithy.api#documentation": "The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.
" } }, "InstanceCount": { @@ -34680,30 +34675,30 @@ "VolumeSizeInGB": { "target": "com.amazonaws.sagemaker#OptionalVolumeSizeInGB", "traits": { - "smithy.api#documentation": "The volume size in GB for the storage volume to be used in processing hyperparameter\n optimization jobs (optional). These volumes store model artifacts, incremental states\n and optionally, scratch space for training algorithms. Do not provide a value for this\n parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these\n instances for training, VolumeSizeInGB cannot be greater than this total\n size. For a list of instance types with local instance storage and their sizes, see\n instance store volumes.
SageMaker supports only the General Purpose SSD\n (gp2) storage volume type.
\nThe volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.
Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.
SageMaker supports only the General Purpose SSD (gp2) storage volume type.
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume\n attached to the compute instances used to run the training job. You can use either of\n the following formats to specify a key.
\nKMS Key ID:
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
Amazon Resource Name (ARN) of a KMS key:
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
Some instances use local storage, which use a hardware module to\n encrypt storage volumes. If you choose one of these instance types, you\n cannot request a VolumeKmsKeyId. For a list of instance types that use\n local storage, see instance store\n volumes. For more information about Amazon Web Services Key Management Service, see KMS\n encryption for more information.
A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.
KMS Key ID:
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
Amazon Resource Name (ARN) of a KMS key:
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.
The strategy that determines the order of preference for resources specified in\n InstanceConfigs used in hyperparameter optimization.
The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.
A list containing the configuration(s) for one or more resources for processing\n hyperparameter jobs. These resources include compute instances and storage volumes to\n use in model training jobs launched by hyperparameter tuning jobs. The\n AllocationStrategy controls the order in which multiple configurations\n provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the\n HyperParameterTuningResourceConfig API, do not provide a value for\n InstanceConfigs. Instead, use InstanceType,\n VolumeSizeInGB and InstanceCount. If you use\n InstanceConfigs, do not provide values for\n InstanceType, VolumeSizeInGB or\n InstanceCount.
A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.
If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.
The configuration of resources, including compute instances and storage volumes for\n use in training jobs launched by hyperparameter tuning jobs.\n HyperParameterTuningResourceConfig is similar to\n ResourceConfig, but has the additional InstanceConfigs and\n AllocationStrategy fields to allow for flexible instance management.\n Specify one or more instance types, count, and the allocation strategy for instance\n selection.
\n HyperParameterTuningResourceConfig supports the capabilities of\n ResourceConfig with the exception of\n KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools\n by default, which reuse clusters between training jobs.
The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig is similar to ResourceConfig, but has the additional InstanceConfigs and AllocationStrategy fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.
HyperParameterTuningResourceConfig supports the capabilities of ResourceConfig with the exception of KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.
The minimum number of resources (such as epochs) that can be used by a training job\n launched by a hyperparameter tuning job. If the value for MinResource has not\n been reached, the training job is not stopped by Hyperband.
The minimum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. If the value for MinResource has not been reached, the training job is not stopped by Hyperband.
The maximum number of resources (such as epochs) that can be used by a training job\n launched by a hyperparameter tuning job. Once a job reaches the MaxResource\n value, it is stopped. If a value for MaxResource is not provided, and\n Hyperband is selected as the hyperparameter tuning strategy,\n HyperbandTraining attempts to infer MaxResource from the\n following keys (if present) in StaticsHyperParameters:
\n epochs\n
\n numepochs\n
\n n-epochs\n
\n n_epochs\n
\n num_epochs\n
If HyperbandStrategyConfig is unable to infer a value for\n MaxResource, it generates a validation error. The maximum value is 20,000\n epochs. All metrics that correspond to an objective metric are used to derive early stopping\n decisions. For distributed training jobs,\n ensure that duplicate metrics are not printed in the logs across the individual nodes in a\n training job. If multiple nodes are publishing duplicate or incorrect metrics, training\n jobs may make an incorrect stopping decision and stop the job prematurely.
The maximum number of resources (such as epochs) that can be used by a training job launched by a hyperparameter tuning job. Once a job reaches the MaxResource value, it is stopped. If a value for MaxResource is not provided, and Hyperband is selected as the hyperparameter tuning strategy, HyperbandTraining attempts to infer MaxResource from the following keys (if present) in StaticsHyperParameters:
epochs
numepochs
n-epochs
n_epochs
num_epochs
If HyperbandStrategyConfig is unable to infer a value for MaxResource, it generates a validation error. The maximum value is 20,000 epochs. All metrics that correspond to an objective metric are used to derive early stopping decisions. For distributed training jobs, ensure that duplicate metrics are not printed in the logs across the individual nodes in a training job. If multiple nodes are publishing duplicate or incorrect metrics, training jobs may make an incorrect stopping decision and stop the job prematurely.
The configuration for Hyperband, a multi-fidelity based hyperparameter\n tuning strategy. Hyperband uses the final and intermediate results of a\n training job to dynamically allocate resources to utilized hyperparameter configurations\n while automatically stopping under-performing configurations. This parameter should be\n provided only if Hyperband is selected as the StrategyConfig\n under the HyperParameterTuningJobConfig API.
The configuration for Hyperband, a multi-fidelity based hyperparameter tuning strategy. Hyperband uses the final and intermediate results of a training job to dynamically allocate resources to utilized hyperparameter configurations while automatically stopping under-performing configurations. This parameter should be provided only if Hyperband is selected as the StrategyConfig under the HyperParameterTuningJobConfig API.
The IAM Identity details associated with the user. These details are\n associated with model package groups, model packages and project entities only.
" + "smithy.api#documentation": "The IAM Identity details associated with the user. These details are associated with model package groups, model packages and project entities only.
" } }, "com.amazonaws.sagemaker#IamPolicyConstraints": { @@ -34834,18 +34829,18 @@ "Status": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "Describes whether OAuth for a data source is enabled or disabled in the Canvas\n application.
" + "smithy.api#documentation": "Describes whether OAuth for a data source is enabled or disabled in the Canvas application.
" } }, "SecretArn": { "target": "com.amazonaws.sagemaker#SecretArn", "traits": { - "smithy.api#documentation": "The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your\n identity provider, such as the client ID and secret, authorization URL, and token URL.
" + "smithy.api#documentation": "The ARN of an Amazon Web Services Secrets Manager secret that stores the credentials from your identity provider, such as the client ID and secret, authorization URL, and token URL.
" } } }, "traits": { - "smithy.api#documentation": "The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external\n data source, such as Snowflake.
" + "smithy.api#documentation": "The Amazon SageMaker Canvas application setting where you configure OAuth for connecting to an external data source, such as Snowflake.
" } }, "com.amazonaws.sagemaker#IdentityProviderOAuthSettings": { @@ -34872,7 +34867,7 @@ "IdleTimeoutInMinutes": { "target": "com.amazonaws.sagemaker#IdleTimeoutInMinutes", "traits": { - "smithy.api#documentation": "The time that SageMaker waits after the application becomes idle before shutting it\n down.
" + "smithy.api#documentation": "The time that SageMaker waits after the application becomes idle before shutting it down.
" } }, "MinIdleTimeoutInMinutes": { @@ -34964,7 +34959,7 @@ } }, "traits": { - "smithy.api#documentation": "A SageMaker AI image. A SageMaker AI image represents a set of container images that are derived from\n a common base container image. Each of these container images is represented by a SageMaker AI\n ImageVersion.
A SageMaker AI image. A SageMaker AI image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker AI ImageVersion.
How long a job is allowed to run, or how many candidates a job is allowed to\n generate.
" + "smithy.api#documentation": "How long a job is allowed to run, or how many candidates a job is allowed to generate.
" } } }, "traits": { - "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the image classification problem\n type.
" + "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the image classification problem type.
" } }, "com.amazonaws.sagemaker#ImageConfig": { @@ -35008,19 +35003,19 @@ "target": "com.amazonaws.sagemaker#RepositoryAccessMode", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Set this to one of the following values:
\n\n Platform - The model image is hosted in Amazon ECR.
\n Vpc - The model image is hosted in a private Docker registry in\n your VPC.
Set this to one of the following values:
Platform - The model image is hosted in Amazon ECR.
Vpc - The model image is hosted in a private Docker registry in your VPC.
(Optional) Specifies an authentication configuration for the private docker registry\n where your model image is hosted. Specify a value for this property only if you\n specified Vpc as the value for the RepositoryAccessMode field,\n and the private Docker registry where the model image is hosted requires\n authentication.
(Optional) Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field, and the private Docker registry where the model image is hosted requires authentication.
Specifies whether the model container is in Amazon ECR or a private Docker registry\n accessible from your Amazon Virtual Private Cloud (VPC).
" + "smithy.api#documentation": "Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
" } }, "com.amazonaws.sagemaker#ImageContainerImage": { @@ -35260,7 +35255,7 @@ } }, "traits": { - "smithy.api#documentation": "A version of a SageMaker AI Image. A version represents an existing container\n image.
A version of a SageMaker AI Image. A version represents an existing container image.
Specifies the endpoint capacity type.
\nThe endpoint activates based on the number of inference component\n copies.
\nThe endpoint activates based on the specified percentage of capacity.
\nSpecifies the endpoint capacity type.
The endpoint activates based on the number of inference component copies.
The endpoint activates based on the specified percentage of capacity.
Defines the capacity size, either as a number of inference component copies or a\n capacity percentage.
", + "smithy.api#documentation": "Defines the capacity size, either as a number of inference component copies or a capacity percentage.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies the type and size of the endpoint capacity to activate for a rolling\n deployment or a rollback strategy. You can specify your batches as either of the\n following:
\nA count of inference component copies
\nThe overall percentage or your fleet
\nFor a rollback strategy, if you don't specify the fields in this object, or if you set\n the Value parameter to 100%, then SageMaker AI uses a blue/green rollback\n strategy and rolls all traffic back to the blue fleet.
Specifies the type and size of the endpoint capacity to activate for a rolling deployment or a rollback strategy. You can specify your batches as either of the following:
A count of inference component copies
The overall percentage or your fleet
For a rollback strategy, if you don't specify the fields in this object, or if you set the Value parameter to 100%, then SageMaker AI uses a blue/green rollback strategy and rolls all traffic back to the blue fleet.
The number of CPU cores to allocate to run a model that you assign to an inference\n component.
" + "smithy.api#documentation": "The number of CPU cores to allocate to run a model that you assign to an inference component.
" } }, "NumberOfAcceleratorDevicesRequired": { "target": "com.amazonaws.sagemaker#NumberOfAcceleratorDevices", "traits": { - "smithy.api#documentation": "The number of accelerators to allocate to run a model that you assign to an inference\n component. Accelerators include GPUs and Amazon Web Services Inferentia.
" + "smithy.api#documentation": "The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
" } }, "MinMemoryRequiredInMb": { "target": "com.amazonaws.sagemaker#MemoryInMb", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The minimum MB of memory to allocate to run a model that you assign to an inference\n component.
", + "smithy.api#documentation": "The minimum MB of memory to allocate to run a model that you assign to an inference component.
", "smithy.api#required": {} } }, "MaxMemoryRequiredInMb": { "target": "com.amazonaws.sagemaker#MemoryInMb", "traits": { - "smithy.api#documentation": "The maximum MB of memory to allocate to run a model that you assign to an inference\n component.
" + "smithy.api#documentation": "The maximum MB of memory to allocate to run a model that you assign to an inference component.
" } } }, "traits": { - "smithy.api#documentation": "Defines the compute resources to allocate to run a model, plus any adapter models, that\n you assign to an inference component. These resources include CPU cores, accelerators, and\n memory.
" + "smithy.api#documentation": "Defines the compute resources to allocate to run a model, plus any adapter models, that you assign to an inference component. These resources include CPU cores, accelerators, and memory.
" } }, "com.amazonaws.sagemaker#InferenceComponentContainerSpecification": { @@ -35629,18 +35624,18 @@ "ArtifactUrl": { "target": "com.amazonaws.sagemaker#Url", "traits": { - "smithy.api#documentation": "The Amazon S3 path where the model artifacts, which result from model training,\n are stored. This path must point to a single gzip compressed tar archive (.tar.gz\n suffix).
" + "smithy.api#documentation": "The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
" } }, "Environment": { "target": "com.amazonaws.sagemaker#EnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the Docker container. Each key and value in the\n Environment string-to-string map can have length of up to 1024. We support up to 16 entries\n in the map.
" + "smithy.api#documentation": "The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map.
" } } }, "traits": { - "smithy.api#documentation": "Defines a container that provides the runtime environment for a model that you deploy\n with an inference component.
" + "smithy.api#documentation": "Defines a container that provides the runtime environment for a model that you deploy with an inference component.
" } }, "com.amazonaws.sagemaker#InferenceComponentContainerSpecificationSummary": { @@ -35681,7 +35676,7 @@ "target": "com.amazonaws.sagemaker#InferenceComponentRollingUpdatePolicy", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a rolling deployment strategy for updating a SageMaker AI\n endpoint.
", + "smithy.api#documentation": "Specifies a rolling deployment strategy for updating a SageMaker AI endpoint.
", "smithy.api#required": {} } }, @@ -35690,7 +35685,7 @@ } }, "traits": { - "smithy.api#documentation": "The deployment configuration for an endpoint that hosts inference components. The\n configuration includes the desired deployment strategy and rollback settings.
" + "smithy.api#documentation": "The deployment configuration for an endpoint that hosts inference components. The configuration includes the desired deployment strategy and rollback settings.
" } }, "com.amazonaws.sagemaker#InferenceComponentName": { @@ -35720,7 +35715,7 @@ "target": "com.amazonaws.sagemaker#InferenceComponentCapacitySize", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The batch size for each rolling step in the deployment process. For each step, SageMaker AI provisions capacity on the new endpoint fleet, routes traffic to that fleet,\n and terminates capacity on the old endpoint fleet. The value must be between 5% to 50% of\n the copy count of the inference component.
", + "smithy.api#documentation": "The batch size for each rolling step in the deployment process. For each step, SageMaker AI provisions capacity on the new endpoint fleet, routes traffic to that fleet, and terminates capacity on the old endpoint fleet. The value must be between 5% to 50% of the copy count of the inference component.
", "smithy.api#required": {} } }, @@ -35728,7 +35723,7 @@ "target": "com.amazonaws.sagemaker#WaitIntervalInSeconds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The length of the baking period, during which SageMaker AI monitors alarms for each\n batch on the new fleet.
", + "smithy.api#documentation": "The length of the baking period, during which SageMaker AI monitors alarms for each batch on the new fleet.
", "smithy.api#required": {} } }, @@ -35741,12 +35736,12 @@ "RollbackMaximumBatchSize": { "target": "com.amazonaws.sagemaker#InferenceComponentCapacitySize", "traits": { - "smithy.api#documentation": "The batch size for a rollback to the old endpoint fleet. If this field is absent, the\n value is set to the default, which is 100% of the total capacity. When the default is used,\n SageMaker AI provisions the entire capacity of the old fleet at once during\n rollback.
" + "smithy.api#documentation": "The batch size for a rollback to the old endpoint fleet. If this field is absent, the value is set to the default, which is 100% of the total capacity. When the default is used, SageMaker AI provisions the entire capacity of the old fleet at once during rollback.
" } } }, "traits": { - "smithy.api#documentation": "Specifies a rolling deployment strategy for updating a SageMaker AI inference\n component.
" + "smithy.api#documentation": "Specifies a rolling deployment strategy for updating a SageMaker AI inference component.
" } }, "com.amazonaws.sagemaker#InferenceComponentRuntimeConfig": { @@ -35756,7 +35751,7 @@ "target": "com.amazonaws.sagemaker#InferenceComponentCopyCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of runtime copies of the model container to deploy with the inference\n component. Each copy can serve inference requests.
", + "smithy.api#documentation": "The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
", "smithy.api#required": {} } } @@ -35771,7 +35766,7 @@ "DesiredCopyCount": { "target": "com.amazonaws.sagemaker#InferenceComponentCopyCount", "traits": { - "smithy.api#documentation": "The number of runtime copies of the model container that you requested to deploy with\n the inference component.
" + "smithy.api#documentation": "The number of runtime copies of the model container that you requested to deploy with the inference component.
" } }, "CurrentCopyCount": { @@ -35782,7 +35777,7 @@ } }, "traits": { - "smithy.api#documentation": "Details about the runtime settings for the model that is deployed with the inference\n component.
" + "smithy.api#documentation": "Details about the runtime settings for the model that is deployed with the inference component.
" } }, "com.amazonaws.sagemaker#InferenceComponentSortKey": { @@ -35814,13 +35809,13 @@ "ModelName": { "target": "com.amazonaws.sagemaker#ModelName", "traits": { - "smithy.api#documentation": "The name of an existing SageMaker AI model object in your account that you want to\n deploy with the inference component.
" + "smithy.api#documentation": "The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.
" } }, "Container": { "target": "com.amazonaws.sagemaker#InferenceComponentContainerSpecification", "traits": { - "smithy.api#documentation": "Defines a container that provides the runtime environment for a model that you deploy\n with an inference component.
" + "smithy.api#documentation": "Defines a container that provides the runtime environment for a model that you deploy with an inference component.
" } }, "StartupParameters": { @@ -35832,18 +35827,18 @@ "ComputeResourceRequirements": { "target": "com.amazonaws.sagemaker#InferenceComponentComputeResourceRequirements", "traits": { - "smithy.api#documentation": "The compute resources allocated to run the model, plus any \n adapter models, that you assign to the inference component.
\nOmit this parameter if your request is meant to create an adapter inference component.\n An adapter inference component is loaded by a base inference component, and it uses the\n compute resources of the base inference component.
" + "smithy.api#documentation": "The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.
Omit this parameter if your request is meant to create an adapter inference component. An adapter inference component is loaded by a base inference component, and it uses the compute resources of the base inference component.
" } }, "BaseInferenceComponentName": { "target": "com.amazonaws.sagemaker#InferenceComponentName", "traits": { - "smithy.api#documentation": "The name of an existing inference component that is to contain the inference component\n that you're creating with your request.
\nSpecify this parameter only if your request is meant to create an adapter inference\n component. An adapter inference component contains the path to an adapter model. The\n purpose of the adapter model is to tailor the inference output of a base foundation model,\n which is hosted by the base inference component. The adapter inference component uses the\n compute resources that you assigned to the base inference component.
\nWhen you create an adapter inference component, use the Container parameter\n to specify the location of the adapter artifacts. In the parameter value, use the\n ArtifactUrl parameter of the\n InferenceComponentContainerSpecification data type.
Before you can create an adapter inference component, you must have an existing\n inference component that contains the foundation model that you want to adapt.
" + "smithy.api#documentation": "The name of an existing inference component that is to contain the inference component that you're creating with your request.
Specify this parameter only if your request is meant to create an adapter inference component. An adapter inference component contains the path to an adapter model. The purpose of the adapter model is to tailor the inference output of a base foundation model, which is hosted by the base inference component. The adapter inference component uses the compute resources that you assigned to the base inference component.
When you create an adapter inference component, use the Container parameter to specify the location of the adapter artifacts. In the parameter value, use the ArtifactUrl parameter of the InferenceComponentContainerSpecification data type.
Before you can create an adapter inference component, you must have an existing inference component that contains the foundation model that you want to adapt.
" } } }, "traits": { - "smithy.api#documentation": "Details about the resources to deploy with this inference component, including the\n model, container, and compute resources.
" + "smithy.api#documentation": "Details about the resources to deploy with this inference component, including the model, container, and compute resources.
" } }, "com.amazonaws.sagemaker#InferenceComponentSpecificationSummary": { @@ -35852,13 +35847,13 @@ "ModelName": { "target": "com.amazonaws.sagemaker#ModelName", "traits": { - "smithy.api#documentation": "The name of the SageMaker AI model object that is deployed with the inference\n component.
" + "smithy.api#documentation": "The name of the SageMaker AI model object that is deployed with the inference component.
" } }, "Container": { "target": "com.amazonaws.sagemaker#InferenceComponentContainerSpecificationSummary", "traits": { - "smithy.api#documentation": "Details about the container that provides the runtime environment for the model that is\n deployed with the inference component.
" + "smithy.api#documentation": "Details about the container that provides the runtime environment for the model that is deployed with the inference component.
" } }, "StartupParameters": { @@ -35870,7 +35865,7 @@ "ComputeResourceRequirements": { "target": "com.amazonaws.sagemaker#InferenceComponentComputeResourceRequirements", "traits": { - "smithy.api#documentation": "The compute resources allocated to run the model, plus any \n adapter models, that you assign to the inference component.
" + "smithy.api#documentation": "The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.
" } }, "BaseInferenceComponentName": { @@ -35890,13 +35885,13 @@ "ModelDataDownloadTimeoutInSeconds": { "target": "com.amazonaws.sagemaker#ProductionVariantModelDataDownloadTimeoutInSeconds", "traits": { - "smithy.api#documentation": "The timeout value, in seconds, to download and extract the model that you want to host\n from Amazon S3 to the individual inference instance associated with this inference\n component.
" + "smithy.api#documentation": "The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
" } }, "ContainerStartupHealthCheckTimeoutInSeconds": { "target": "com.amazonaws.sagemaker#ProductionVariantContainerStartupHealthCheckTimeoutInSeconds", "traits": { - "smithy.api#documentation": "The timeout value, in seconds, for your inference container to pass health check by\n Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
" + "smithy.api#documentation": "The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
" } } }, @@ -36022,7 +36017,7 @@ "target": "com.amazonaws.sagemaker#InferenceExecutionMode", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "How containers in a multi-container are run. The following values are valid.
\n\n SERIAL - Containers run as a serial pipeline.
\n DIRECT - Only the individual container that you specify is\n run.
How containers in a multi-container are run. The following values are valid.
SERIAL - Containers run as a serial pipeline.
DIRECT - Only the individual container that you specify is run.
\n The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3\n server-side encryption.\n
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service key that Amazon SageMaker uses to encrypt captured data at rest using Amazon S3 server-side encryption.
" } }, "ContentType": { @@ -36126,7 +36121,7 @@ } }, "traits": { - "smithy.api#documentation": "The start and end times of an inference experiment.
\nThe maximum duration that you can set for an inference experiment is 30 days.
" + "smithy.api#documentation": "The start and end times of an inference experiment.
The maximum duration that you can set for an inference experiment is 30 days.
" } }, "com.amazonaws.sagemaker#InferenceExperimentStatus": { @@ -36231,7 +36226,7 @@ "Schedule": { "target": "com.amazonaws.sagemaker#InferenceExperimentSchedule", "traits": { - "smithy.api#documentation": "The duration for which the inference experiment ran or will run.
\nThe maximum duration that you can set for an inference experiment is 30 days.
" + "smithy.api#documentation": "The duration for which the inference experiment ran or will run.
The maximum duration that you can set for an inference experiment is 30 days.
" } }, "Status": { @@ -36279,7 +36274,7 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "\n The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage\n Amazon SageMaker Inference endpoints for model deployment.\n
" + "smithy.api#documentation": "The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
" } } }, @@ -36468,7 +36463,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker \n to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.
", "smithy.api#required": {} } }, @@ -36495,7 +36490,7 @@ "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored.\n This path must point to a single gzip compressed tar archive (.tar.gz suffix).
" + "smithy.api#documentation": "The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
" } }, "ModelPackageVersionArn": { @@ -36516,7 +36511,7 @@ "target": "com.amazonaws.sagemaker#RecommendationStepType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The type of the subtask.
\n\n BENCHMARK: Evaluate the performance of your model on different instance types.
The type of the subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
A returned array object for the Steps response field in the\n ListInferenceRecommendationsJobSteps API command.
A returned array object for the Steps response field in the ListInferenceRecommendationsJobSteps API command.
A list of the instance types on which a transformation job can be run or on which an\n endpoint can be deployed.
\nThis parameter is required for unversioned models, and optional for versioned\n models.
" + "smithy.api#documentation": "A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
This parameter is required for unversioned models, and optional for versioned models.
" } }, "SupportedRealtimeInferenceInstanceTypes": { "target": "com.amazonaws.sagemaker#RealtimeInferenceInstanceTypes", "traits": { - "smithy.api#documentation": "A list of the instance types that are used to generate inferences in real-time.
\nThis parameter is required for unversioned models, and optional for versioned\n models.
" + "smithy.api#documentation": "A list of the instance types that are used to generate inferences in real-time.
This parameter is required for unversioned models, and optional for versioned models.
" } }, "SupportedContentTypes": { @@ -36620,7 +36615,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network \n connectivity.
" + "smithy.api#documentation": "Configuration information for the infrastructure health check of a training job. A SageMaker-provided health check tests the health of instance hardware and cluster network connectivity.
" } }, "com.amazonaws.sagemaker#InitialInstanceCount": { @@ -36654,33 +36649,33 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The S3 path where the model artifacts, which result from model training, are stored.\n This path must point to a single gzip compressed tar archive (.tar.gz suffix).
", + "smithy.api#documentation": "The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
", "smithy.api#required": {} } }, "DataInputConfig": { "target": "com.amazonaws.sagemaker#DataInputConfig", "traits": { - "smithy.api#documentation": "Specifies the name and shape of the expected data inputs for your trained model with a\n JSON dictionary form. The data inputs are Framework specific.
\n TensorFlow: You must specify the name and shape (NHWC format) of\n the expected data inputs using a dictionary format for your trained model. The\n dictionary formats required for the console and CLI are different.
Examples for one input:
\nIf using the console,\n {\"input\":[1,1024,1024,3]}\n
If using the CLI,\n {\\\"input\\\":[1,1024,1024,3]}\n
Examples for two inputs:
\nIf using the console, {\"data1\": [1,28,28,1],\n \"data2\":[1,28,28,1]}\n
If using the CLI, {\\\"data1\\\": [1,28,28,1],\n \\\"data2\\\":[1,28,28,1]}\n
\n KERAS: You must specify the name and shape (NCHW format) of\n expected data inputs using a dictionary format for your trained model. Note that\n while Keras model artifacts should be uploaded in NHWC (channel-last) format,\n DataInputConfig should be specified in NCHW (channel-first)\n format. The dictionary formats required for the console and CLI are\n different.
Examples for one input:
\nIf using the console,\n {\"input_1\":[1,3,224,224]}\n
If using the CLI,\n {\\\"input_1\\\":[1,3,224,224]}\n
Examples for two inputs:
\nIf using the console, {\"input_1\": [1,3,224,224],\n \"input_2\":[1,3,224,224]} \n
If using the CLI, {\\\"input_1\\\": [1,3,224,224],\n \\\"input_2\\\":[1,3,224,224]}\n
\n MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW\n format) of the expected data inputs in order using a dictionary format for your\n trained model. The dictionary formats required for the console and CLI are\n different.
Examples for one input:
\nIf using the console,\n {\"data\":[1,3,1024,1024]}\n
If using the CLI,\n {\\\"data\\\":[1,3,1024,1024]}\n
Examples for two inputs:
\nIf using the console, {\"var1\": [1,1,28,28],\n \"var2\":[1,1,28,28]} \n
If using the CLI, {\\\"var1\\\": [1,1,28,28],\n \\\"var2\\\":[1,1,28,28]}\n
\n PyTorch: You can either specify the name and shape (NCHW format)\n of expected data inputs in order using a dictionary format for your trained\n model or you can specify the shape only using a list format. The dictionary\n formats required for the console and CLI are different. The list formats for the\n console and CLI are the same.
Examples for one input in dictionary format:
\nIf using the console,\n {\"input0\":[1,3,224,224]}\n
If using the CLI,\n {\\\"input0\\\":[1,3,224,224]}\n
Example for one input in list format:\n [[1,3,224,224]]\n
Examples for two inputs in dictionary format:
\nIf using the console, {\"input0\":[1,3,224,224],\n \"input1\":[1,3,224,224]}\n
If using the CLI, {\\\"input0\\\":[1,3,224,224],\n \\\"input1\\\":[1,3,224,224]} \n
Example for two inputs in list format: [[1,3,224,224],\n [1,3,224,224]]\n
\n XGBOOST: input data name and shape are not needed.
\n DataInputConfig supports the following parameters for CoreML\n TargetDevice (ML Model format):
\n shape: Input shape, for example {\"input_1\": {\"shape\":\n [1,224,224,3]}}. In addition to static input shapes, CoreML converter\n supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know\n the input shape will be within some specific interval in that dimension,\n for example: {\"input_1\": {\"shape\": [\"1..10\", 224, 224,\n 3]}}\n
Enumerated shapes. Sometimes, the models are trained to work only on a\n select set of inputs. You can enumerate all supported input shapes, for\n example: {\"input_1\": {\"shape\": [[1, 224, 224, 3], [1, 160, 160,\n 3]]}}\n
\n default_shape: Default input shape. You can set a default shape\n during conversion for both Range Dimension and Enumerated Shapes. For example\n {\"input_1\": {\"shape\": [\"1..10\", 224, 224, 3], \"default_shape\": [1,\n 224, 224, 3]}}\n
\n type: Input type. Allowed values: Image and\n Tensor. By default, the converter generates an ML Model with\n inputs of type Tensor (MultiArray). User can set input type to be Image. Image\n input type requires additional input parameters such as bias and\n scale.
\n bias: If the input type is an Image, you need to provide the bias\n vector.
\n scale: If the input type is an Image, you need to provide a scale\n factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig\n CompilerOptions. CoreML converter supports Tensorflow and PyTorch models.\n CoreML conversion examples:
Tensor type input:
\n\n \"DataInputConfig\": {\"input_1\": {\"shape\": [[1,224,224,3],\n [1,160,160,3]], \"default_shape\": [1,224,224,3]}}\n
Tensor type input without input name (PyTorch):
\n\n \"DataInputConfig\": [{\"shape\": [[1,3,224,224], [1,3,160,160]],\n \"default_shape\": [1,3,224,224]}]\n
Image type input:
\n\n \"DataInputConfig\": {\"input_1\": {\"shape\": [[1,224,224,3],\n [1,160,160,3]], \"default_shape\": [1,224,224,3], \"type\": \"Image\",\n \"bias\": [-1,-1,-1], \"scale\": 0.007843137255}}\n
\n \"CompilerOptions\": {\"class_labels\":\n \"imagenet_labels_1000.txt\"}\n
Image type input without input name (PyTorch):
\n\n \"DataInputConfig\": [{\"shape\": [[1,3,224,224], [1,3,160,160]],\n \"default_shape\": [1,3,224,224], \"type\": \"Image\", \"bias\": [-1,-1,-1],\n \"scale\": 0.007843137255}]\n
\n \"CompilerOptions\": {\"class_labels\":\n \"imagenet_labels_1000.txt\"}\n
Depending on the model format, DataInputConfig requires the following\n parameters for ml_eia2\n OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names\n from signature_def_key and the input model shapes for\n DataInputConfig. Specify the signature_def_key in\n \n OutputConfig:CompilerOptions\n if the model does not\n use TensorFlow's default signature def key. For example:
\n \"DataInputConfig\": {\"inputs\": [1, 224, 224, 3]}\n
\n \"CompilerOptions\": {\"signature_def_key\":\n \"serving_custom\"}\n
For TensorFlow models saved as a frozen graph, specify the input tensor names\n and shapes in DataInputConfig and the output tensor names for\n output_names in \n OutputConfig:CompilerOptions\n . For\n example:
\n \"DataInputConfig\": {\"input_tensor:0\": [1, 224, 224,\n 3]}\n
\n \"CompilerOptions\": {\"output_names\":\n [\"output_tensor:0\"]}\n
Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are Framework specific.
TensorFlow: You must specify the name and shape (NHWC format) of the expected data inputs using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {\"input\":[1,1024,1024,3]}
If using the CLI, {\\\"input\\\":[1,1024,1024,3]}
Examples for two inputs:
If using the console, {\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}
If using the CLI, {\\\"data1\\\": [1,28,28,1], \\\"data2\\\":[1,28,28,1]}
KERAS: You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {\"input_1\":[1,3,224,224]}
If using the CLI, {\\\"input_1\\\":[1,3,224,224]}
Examples for two inputs:
If using the console, {\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}
If using the CLI, {\\\"input_1\\\": [1,3,224,224], \\\"input_2\\\":[1,3,224,224]}
MXNET/ONNX/DARKNET: You must specify the name and shape (NCHW format) of the expected data inputs in order using a dictionary format for your trained model. The dictionary formats required for the console and CLI are different.
Examples for one input:
If using the console, {\"data\":[1,3,1024,1024]}
If using the CLI, {\\\"data\\\":[1,3,1024,1024]}
Examples for two inputs:
If using the console, {\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}
If using the CLI, {\\\"var1\\\": [1,1,28,28], \\\"var2\\\":[1,1,28,28]}
PyTorch: You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.
Examples for one input in dictionary format:
If using the console, {\"input0\":[1,3,224,224]}
If using the CLI, {\\\"input0\\\":[1,3,224,224]}
Example for one input in list format: [[1,3,224,224]]
Examples for two inputs in dictionary format:
If using the console, {\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]}
If using the CLI, {\\\"input0\\\":[1,3,224,224], \\\"input1\\\":[1,3,224,224]}
Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]
XGBOOST: input data name and shape are not needed.
DataInputConfig supports the following parameters for CoreML TargetDevice (ML Model format):
shape: Input shape, for example {\"input_1\": {\"shape\": [1,224,224,3]}}. In addition to static input shapes, CoreML converter supports Flexible input shapes:
Range Dimension. You can use the Range Dimension feature if you know the input shape will be within some specific interval in that dimension, for example: {\"input_1\": {\"shape\": [\"1..10\", 224, 224, 3]}}
Enumerated shapes. Sometimes, the models are trained to work only on a select set of inputs. You can enumerate all supported input shapes, for example: {\"input_1\": {\"shape\": [[1, 224, 224, 3], [1, 160, 160, 3]]}}
default_shape: Default input shape. You can set a default shape during conversion for both Range Dimension and Enumerated Shapes. For example {\"input_1\": {\"shape\": [\"1..10\", 224, 224, 3], \"default_shape\": [1, 224, 224, 3]}}
type: Input type. Allowed values: Image and Tensor. By default, the converter generates an ML Model with inputs of type Tensor (MultiArray). User can set input type to be Image. Image input type requires additional input parameters such as bias and scale.
bias: If the input type is an Image, you need to provide the bias vector.
scale: If the input type is an Image, you need to provide a scale factor.
CoreML ClassifierConfig parameters can be specified using OutputConfig CompilerOptions. CoreML converter supports Tensorflow and PyTorch models. CoreML conversion examples:
Tensor type input:
\"DataInputConfig\": {\"input_1\": {\"shape\": [[1,224,224,3], [1,160,160,3]], \"default_shape\": [1,224,224,3]}}
Tensor type input without input name (PyTorch):
\"DataInputConfig\": [{\"shape\": [[1,3,224,224], [1,3,160,160]], \"default_shape\": [1,3,224,224]}]
Image type input:
\"DataInputConfig\": {\"input_1\": {\"shape\": [[1,224,224,3], [1,160,160,3]], \"default_shape\": [1,224,224,3], \"type\": \"Image\", \"bias\": [-1,-1,-1], \"scale\": 0.007843137255}}
\"CompilerOptions\": {\"class_labels\": \"imagenet_labels_1000.txt\"}
Image type input without input name (PyTorch):
\"DataInputConfig\": [{\"shape\": [[1,3,224,224], [1,3,160,160]], \"default_shape\": [1,3,224,224], \"type\": \"Image\", \"bias\": [-1,-1,-1], \"scale\": 0.007843137255}]
\"CompilerOptions\": {\"class_labels\": \"imagenet_labels_1000.txt\"}
Depending on the model format, DataInputConfig requires the following parameters for ml_eia2 OutputConfig:TargetDevice.
For TensorFlow models saved in the SavedModel format, specify the input names from signature_def_key and the input model shapes for DataInputConfig. Specify the signature_def_key in OutputConfig:CompilerOptions if the model does not use TensorFlow's default signature def key. For example:
\"DataInputConfig\": {\"inputs\": [1, 224, 224, 3]}
\"CompilerOptions\": {\"signature_def_key\": \"serving_custom\"}
For TensorFlow models saved as a frozen graph, specify the input tensor names and shapes in DataInputConfig and the output tensor names for output_names in OutputConfig:CompilerOptions . For example:
\"DataInputConfig\": {\"input_tensor:0\": [1, 224, 224, 3]}
\"CompilerOptions\": {\"output_names\": [\"output_tensor:0\"]}
Identifies the framework in which the model was trained. For example:\n TENSORFLOW.
", + "smithy.api#documentation": "Identifies the framework in which the model was trained. For example: TENSORFLOW.
", "smithy.api#required": {} } }, "FrameworkVersion": { "target": "com.amazonaws.sagemaker#FrameworkVersion", "traits": { - "smithy.api#documentation": "Specifies the framework version to use. This API field is only supported for the\n MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
\nFor information about framework versions supported for cloud targets and edge devices,\n see Cloud\n Supported Instance Types and Frameworks and Edge Supported\n Frameworks.
" + "smithy.api#documentation": "Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite frameworks.
For information about framework versions supported for cloud targets and edge devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
" } } }, "traits": { - "smithy.api#documentation": "Contains information about the location of input model artifacts, the name and\n shape\n of the expected data inputs, and the framework in which the model was trained.
" + "smithy.api#documentation": "Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
" } }, "com.amazonaws.sagemaker#InputDataConfig": { @@ -36760,7 +36755,7 @@ } }, "traits": { - "smithy.api#documentation": "Defines an instance group for heterogeneous cluster training. When requesting a\n training job using the CreateTrainingJob API, you can configure multiple instance groups .
" + "smithy.api#documentation": "Defines an instance group for heterogeneous cluster training. When requesting a training job using the CreateTrainingJob API, you can configure multiple instance groups .
" } }, "com.amazonaws.sagemaker#InstanceGroupName": { @@ -36860,7 +36855,7 @@ "target": "com.amazonaws.sagemaker#MinimumInstanceMetadataServiceVersion", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Indicates the minimum IMDS version that the notebook instance supports. When passed as\n part of CreateNotebookInstance, if no value is selected, then it defaults\n to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of\n UpdateNotebookInstance, there is no default.
Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
The minimum\n value\n of the hyperparameter to search.
", + "smithy.api#documentation": "The minimum value of the hyperparameter to search.
", "smithy.api#required": {} } }, @@ -37932,19 +37927,19 @@ "target": "com.amazonaws.sagemaker#ParameterValue", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The maximum\n value\n of the hyperparameter to search.
", + "smithy.api#documentation": "The maximum value of the hyperparameter to search.
", "smithy.api#required": {} } }, "ScalingType": { "target": "com.amazonaws.sagemaker#HyperParameterScalingType", "traits": { - "smithy.api#documentation": "The scale that hyperparameter tuning uses to search the hyperparameter range. For\n information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
\nSageMaker hyperparameter tuning chooses the best scale for the\n hyperparameter.
\nHyperparameter tuning searches the values in the hyperparameter range by\n using a linear scale.
\nHyperparameter tuning searches the values in the hyperparameter range by\n using a logarithmic scale.
\nLogarithmic scaling works only for ranges that have only values greater\n than 0.
\nThe scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:
SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.
Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.
Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.
Logarithmic scaling works only for ranges that have only values greater than 0.
For a hyperparameter of the integer type, specifies the range\n that\n a hyperparameter tuning job searches.
" + "smithy.api#documentation": "For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
" } }, "com.amazonaws.sagemaker#IntegerParameterRangeSpecification": { @@ -38184,13 +38179,13 @@ "EmrSettings": { "target": "com.amazonaws.sagemaker#EmrSettings", "traits": { - "smithy.api#documentation": "The configuration parameters that specify the IAM roles assumed by the execution role of \n SageMaker (assumable roles) and the cluster instances or job execution environments \n (execution roles or runtime roles) to manage and access resources required for running Amazon EMR\n clusters or Amazon EMR Serverless applications.
" + "smithy.api#documentation": "The configuration parameters that specify the IAM roles assumed by the execution role of SageMaker (assumable roles) and the cluster instances or job execution environments (execution roles or runtime roles) to manage and access resources required for running Amazon EMR clusters or Amazon EMR Serverless applications.
" } }, "BuiltInLifecycleConfigArn": { "target": "com.amazonaws.sagemaker#StudioLifecycleConfigArn", "traits": { - "smithy.api#documentation": "The lifecycle configuration that runs before the default lifecycle configuration. It can\n override changes made in the default lifecycle configuration.
" + "smithy.api#documentation": "The lifecycle configuration that runs before the default lifecycle configuration. It can override changes made in the default lifecycle configuration.
" } } }, @@ -38204,19 +38199,19 @@ "DefaultResourceSpec": { "target": "com.amazonaws.sagemaker#ResourceSpec", "traits": { - "smithy.api#documentation": "The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the JupyterServer app. If you use the\n LifecycleConfigArns parameter, then this parameter is also required.
The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the JupyterServer app. If you use the LifecycleConfigArns parameter, then this parameter is also required.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the\n JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is\n also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty\n list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp. If you use this parameter, the DefaultResourceSpec parameter is also required.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
A list of Git repositories that SageMaker AI automatically displays to users for\n cloning in the JupyterServer application.
" + "smithy.api#documentation": "A list of Git repositories that SageMaker AI automatically displays to users for cloning in the JupyterServer application.
" } } }, @@ -38240,12 +38235,12 @@ "Status": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "Describes whether the document querying feature is enabled\n or disabled in the Canvas application.
" + "smithy.api#documentation": "Describes whether the document querying feature is enabled or disabled in the Canvas application.
" } } }, "traits": { - "smithy.api#documentation": "The Amazon SageMaker Canvas application setting where you configure\n document querying.
" + "smithy.api#documentation": "The Amazon SageMaker Canvas application setting where you configure document querying.
" } }, "com.amazonaws.sagemaker#KernelDisplayName": { @@ -38263,19 +38258,19 @@ "DefaultResourceSpec": { "target": "com.amazonaws.sagemaker#ResourceSpec", "traits": { - "smithy.api#documentation": "The default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the KernelGateway app.
\nThe Amazon SageMaker AI Studio UI does not use the default instance type value set\n here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not\n passed.
\nThe default instance type and the Amazon Resource Name (ARN) of the default SageMaker AI image used by the KernelGateway app.
The Amazon SageMaker AI Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the CLI or CloudFormation and the instance type parameter value is not passed.
A list of custom SageMaker AI images that are configured to run as a KernelGateway\n app.
\nThe maximum number of custom images are as follows.
\nOn a domain level: 200
\nOn a space level: 5
\nOn a user profile level: 5
\nA list of custom SageMaker AI images that are configured to run as a KernelGateway app.
The maximum number of custom images are as follows.
On a domain level: 200
On a space level: 5
On a user profile level: 5
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user\n profile or domain.
\nTo remove a Lifecycle Config, you must set LifecycleConfigArns to an empty\n list.
The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.
To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.
The configuration for the file system and kernels in a SageMaker AI image running as a\n KernelGateway app.
" + "smithy.api#documentation": "The configuration for the file system and kernels in a SageMaker AI image running as a KernelGateway app.
" } }, "com.amazonaws.sagemaker#KernelName": { @@ -38467,14 +38462,14 @@ "target": "com.amazonaws.sagemaker#LabelingJobAlgorithmSpecificationArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You\n must select one of the following ARNs:
\n\n Image classification\n
\n\n arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification\n
\n Text classification\n
\n\n arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification\n
\n Object detection\n
\n\n arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection\n
\n Semantic Segmentation\n
\n\n arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation\n
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
Text classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
Object detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
Semantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final\n model used for auto-labeling. You can use this model as the starting point for\n subsequent similar jobs by providing the ARN of the model here.
" + "smithy.api#documentation": "At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
" } }, "LabelingJobResourceConfig": { @@ -38485,7 +38480,7 @@ } }, "traits": { - "smithy.api#documentation": "Provides configuration information for auto-labeling of your data objects. A\n LabelingJobAlgorithmsConfig object must be supplied in order to use\n auto-labeling.
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
Declares that your content is free of personally identifiable information or adult\n content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task\n based on this information.
" + "smithy.api#documentation": "Declares that your content is free of personally identifiable information or adult content. SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.
" } } }, "traits": { - "smithy.api#documentation": "Attributes of the data specified by the customer. Use these to describe the data to be\n labeled.
" + "smithy.api#documentation": "Attributes of the data specified by the customer. Use these to describe the data to be labeled.
" } }, "com.amazonaws.sagemaker#LabelingJobDataSource": { @@ -38529,7 +38524,7 @@ } }, "traits": { - "smithy.api#documentation": "Provides information about the location of input data.
\nYou must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic\n for a streaming labeling job. If you do not specify \n and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input \n manifest file for both streaming and one-time labeling jobs.\n Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
Provides information about the location of input data.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.
Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.
A unique identifier for a labeling job. You can use this to refer to a specific\n labeling job.
", + "smithy.api#documentation": "A unique identifier for a labeling job. You can use this to refer to a specific labeling job.
", "smithy.api#required": {} } }, @@ -38553,7 +38548,7 @@ "target": "com.amazonaws.sagemaker#AccountId", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Web Services account ID of the account used to start the labeling\n job.
", + "smithy.api#documentation": "The Amazon Web Services account ID of the account used to start the labeling job.
", "smithy.api#required": {} } }, @@ -38634,7 +38629,7 @@ "FinalActiveLearningModelArn": { "target": "com.amazonaws.sagemaker#ModelArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of\n automated data labeling.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) for the most recent SageMaker model trained as part of automated data labeling.
" } } }, @@ -38656,13 +38651,13 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
\nIf you provide your own KMS key ID, you must add the required permissions to your KMS\n key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
\nIf you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your\n role's account to encrypt your output data.
\nIf you use a bucket policy with an s3:PutObject permission that only\n allows objects with server-side encryption, set the condition key of\n s3:x-amz-server-side-encryption to \"aws:kms\". For more\n information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer\n Guide.\n
The Amazon Web Services Key Management Service ID of the key used to encrypt the output data, if any.
If you provide your own KMS key ID, you must add the required permissions to your KMS key described in Encrypt Output Data and Storage Volume with Amazon Web Services KMS.
If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web Services KMS key for Amazon S3 for your role's account to encrypt your output data.
If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to \"aws:kms\". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to\n do real time chaining to another streaming job and receive an Amazon SNS notifications each\n time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers\n complete labeling tasks, Ground Truth will send labeling task output data to the SNS output\n topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling\n Job.
" + "smithy.api#documentation": "An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a SnsTopicArn if you want to do real time chaining to another streaming job and receive an Amazon SNS notifications each time a data object is submitted by a worker.
If you provide an SnsTopicArn in OutputConfig, when workers complete labeling tasks, Ground Truth will send labeling task output data to the SNS output topic you specify here.
To learn more, see Receive Output Data from a Streaming Labeling Job.
" } } }, @@ -38676,7 +38671,7 @@ "VolumeKmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume\n attached to the ML compute instance(s) that run the training and inference jobs used for\n automated data labeling.
\nYou can only specify a VolumeKmsKeyId when you create a labeling job with\n automated data labeling enabled using the API operation CreateLabelingJob.\n You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for\n automated data labeling model training and inference when you create a labeling job\n using the console. To learn more, see Output Data and Storage Volume\n Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training and inference jobs used for automated data labeling.
You can only specify a VolumeKmsKeyId when you create a labeling job with automated data labeling enabled using the API operation CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt the storage volume used for automated data labeling model training and inference when you create a labeling job using the console. To learn more, see Output Data and Storage Volume Encryption.
The VolumeKmsKeyId can be any of the following formats:
KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
Configure encryption on the storage volume attached to the ML compute instance used to\n run automated data labeling model training and inference.
" + "smithy.api#documentation": "Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
" } }, "com.amazonaws.sagemaker#LabelingJobS3DataSource": { @@ -38694,7 +38689,7 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon S3 location of the manifest file that describes the input data objects.
\nThe input manifest file referenced in ManifestS3Uri must contain one of\n the following keys: source-ref or source. The value of the\n keys are interpreted as follows:
\n source-ref: The source of the object is the Amazon S3 object\n specified in the value. Use this value when the object is a binary object, such\n as an image.
\n source: The source of the object is the value. Use this\n value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to\n create an input manifest file.
", + "smithy.api#documentation": "The Amazon S3 location of the manifest file that describes the input data objects.
The input manifest file referenced in ManifestS3Uri must contain one of the following keys: source-ref or source. The value of the keys are interpreted as follows:
source-ref: The source of the object is the Amazon S3 object specified in the value. Use this value when the object is a binary object, such as an image.
source: The source of the object is the value. Use this value when the object is a text value.
If you are a new user of Ground Truth, it is recommended you review Use an Input Manifest File in the Amazon SageMaker Developer Guide to learn how to create an input manifest file.
", "smithy.api#required": {} } } @@ -38710,7 +38705,7 @@ "target": "com.amazonaws.sagemaker#SnsTopicArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic\n you will use to send new data objects to a streaming labeling job.
", + "smithy.api#documentation": "The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the input topic you will use to send new data objects to a streaming labeling job.
", "smithy.api#required": {} } } @@ -38777,7 +38772,7 @@ } }, "traits": { - "smithy.api#documentation": "A set of conditions for stopping a labeling job. If any of the conditions are met, the\n job is automatically stopped. You can use these conditions to control the cost of data\n labeling.
\nLabeling jobs fail after 30 days with an appropriate client error message.
\nA set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Labeling jobs fail after 30 days with an appropriate client error message.
The Amazon Resource Name (ARN) assigned to the labeling job when it was\n created.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
", "smithy.api#required": {} } }, @@ -38842,19 +38837,19 @@ "PreHumanTaskLambdaArn": { "target": "com.amazonaws.sagemaker#LambdaFunctionArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Lambda function. The function is run before each\n data object is sent to a worker.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.
" } }, "AnnotationConsolidationLambdaArn": { "target": "com.amazonaws.sagemaker#LambdaFunctionArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Lambda function used to consolidate the\n annotations from individual workers into a label for a data object. For more\n information, see Annotation\n Consolidation.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.
" } }, "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "If the LabelingJobStatus field is Failed, this field\n contains a description of the error.
If the LabelingJobStatus field is Failed, this field contains a description of the error.
Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity \n resources.
" + "smithy.api#documentation": "Lists a summary of the properties of a lineage group. A lineage group provides a group of shareable lineage entity resources.
" } }, "com.amazonaws.sagemaker#LineageType": { @@ -39163,7 +39158,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListActions didn't return the full set of actions,\n the call returns a token for getting the next set of actions.
If the previous call to ListActions didn't return the full set of actions, the call returns a token for getting the next set of actions.
A filter that returns only algorithms created after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only algorithms created after the specified time (timestamp).
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only algorithms created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only algorithms created before the specified time (timestamp).
" } }, "MaxResults": { @@ -39239,19 +39234,19 @@ "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the algorithm name. This filter returns only algorithms whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the algorithm name. This filter returns only algorithms whose name contains the specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListAlgorithms request was truncated, the\n response includes a NextToken. To retrieve the next set of algorithms, use\n the token in the next request.
If the response to a previous ListAlgorithms request was truncated, the response includes a NextToken. To retrieve the next set of algorithms, use the token in the next request.
The parameter by which to sort the results. The default is\n CreationTime.
The parameter by which to sort the results. The default is CreationTime.
>An array of AlgorithmSummary objects, each of which lists an\n algorithm.
>An array of AlgorithmSummary objects, each of which lists an algorithm.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n algorithms, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
" } } }, @@ -39342,7 +39337,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListAliases didn't return the full set of\n aliases, the call returns a token for retrieving the next set of aliases.
If the previous call to ListAliases didn't return the full set of aliases, the call returns a token for retrieving the next set of aliases.
Lists the AppImageConfigs in your account and their properties. The list can be\n filtered by creation time or modified time, and whether the AppImageConfig name contains\n a specified string.
", + "smithy.api#documentation": "Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -39394,13 +39389,13 @@ "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The total number of items to return in the response. If the total\n number of items available is more than the value specified, a NextToken\n is provided in the response. To resume pagination, provide the NextToken\n value in the as part of a subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
If the previous call to ListImages didn't return the full set of\n AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
If the previous call to ListImages didn't return the full set of AppImageConfigs, the call returns a token for getting the next set of AppImageConfigs.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "This parameter defines the maximum number of results that can be return in a single\n response. The MaxResults parameter is an upper bound, not a target. If there are\n more results available than the value specified, a NextToken is provided in the\n response. The NextToken indicates that the user should get the next set of\n results by providing this token as a part of a subsequent call. The default value for\n MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
A parameter to search by user profile name. If SpaceNameEquals is set, then\n this value cannot be set.
A parameter to search by user profile name. If SpaceNameEquals is set, then this value cannot be set.
A parameter to search by space name. If UserProfileNameEquals is set, then\n this value cannot be set.
A parameter to search by space name. If UserProfileNameEquals is set, then this value cannot be set.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -39623,7 +39618,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListArtifacts didn't return the full set of artifacts,\n the call returns a token for getting the next set of artifacts.
If the previous call to ListArtifacts didn't return the full set of artifacts, the call returns a token for getting the next set of artifacts.
If the previous call to ListAssociations didn't return the full set of associations,\n the call returns a token for getting the next set of associations.
If the previous call to ListAssociations didn't return the full set of associations, the call returns a token for getting the next set of associations.
If the previous response was truncated, you receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -39874,7 +39869,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -39937,7 +39932,7 @@ "SortBy": { "target": "com.amazonaws.sagemaker#CandidateSortBy", "traits": { - "smithy.api#documentation": "The parameter by which to sort the results. The default is\n Descending.
The parameter by which to sort the results. The default is Descending.
If the previous response was truncated, you receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -39971,7 +39966,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -39993,7 +39988,7 @@ } ], "traits": { - "smithy.api#documentation": "Retrieves the list of instances (also called nodes interchangeably)\n in a SageMaker HyperPod cluster.
", + "smithy.api#documentation": "Retrieves the list of instances (also called nodes interchangeably) in a SageMaker HyperPod cluster.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -40009,20 +40004,20 @@ "target": "com.amazonaws.sagemaker#ClusterNameOrArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the\n list of nodes.
", + "smithy.api#documentation": "The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster in which you want to retrieve the list of nodes.
", "smithy.api#required": {} } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time.\n Timestamps are formatted according to the ISO 8601 standard.
\nAcceptable formats include:
\n\n YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example,\n 2014-10-01T20:30:00.000Z\n
\n YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example,\n 2014-10-01T12:30:00.000-08:00\n
\n YYYY-MM-DD, for example, 2014-10-01\n
Unix time in seconds, for example, 1412195400. This is also referred\n to as Unix Epoch time and represents the number of seconds since midnight, January 1,\n 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User\n Guide.
" + "smithy.api#documentation": "A filter that returns nodes in a SageMaker HyperPod cluster created after the specified time. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD, for example, 2014-10-01
Unix time in seconds, for example, 1412195400. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The\n acceptable formats are the same as the timestamp formats for\n CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User\n Guide.
A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
If the result of the previous ListClusterNodes request was truncated, the\n response includes a NextToken. To retrieve the next set of cluster nodes, use\n the token in the next request.
If the result of the previous ListClusterNodes request was truncated, the response includes a NextToken. To retrieve the next set of cluster nodes, use the token in the next request.
The field by which to sort results. The default value is\n CREATION_TIME.
The field by which to sort results. The default value is CREATION_TIME.
Filter for after this creation time. The input for this parameter is a Unix timestamp.\n To convert a date and time into a Unix timestamp, see EpochConverter.
" + "smithy.api#documentation": "Filter for after this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
" } }, "CreatedBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filter for before this creation time. The input for this parameter is a Unix timestamp.\n To convert a date and time into a Unix timestamp, see EpochConverter.
" + "smithy.api#documentation": "Filter for before this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
" } }, "NameContains": { @@ -40136,19 +40131,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#SortClusterSchedulerConfigBy", "traits": { - "smithy.api#documentation": "Filter for sorting the list by a given value. For example, sort by name, creation time,\n or status.
" + "smithy.api#documentation": "Filter for sorting the list by a given value. For example, sort by name, creation time, or status.
" } }, "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "The order of the list. By default, listed in Descending order according to\n by SortBy. To change the list order, you can specify SortOrder to\n be Ascending.
The order of the list. By default, listed in Descending order according to by SortBy. To change the list order, you can specify SortOrder to be Ascending.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { @@ -40174,7 +40169,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -40206,13 +40201,13 @@ "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Set a start time for the time range during which you want to list SageMaker HyperPod clusters.\n Timestamps are formatted according to the ISO 8601 standard.
\nAcceptable formats include:
\n\n YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example,\n 2014-10-01T20:30:00.000Z\n
\n YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example,\n 2014-10-01T12:30:00.000-08:00\n
\n YYYY-MM-DD, for example, 2014-10-01\n
Unix time in seconds, for example, 1412195400. This is also referred\n to as Unix Epoch time and represents the number of seconds since midnight, January 1,\n 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User\n Guide.
" + "smithy.api#documentation": "Set a start time for the time range during which you want to list SageMaker HyperPod clusters. Timestamps are formatted according to the ISO 8601 standard.
Acceptable formats include:
YYYY-MM-DDThh:mm:ss.sssTZD (UTC), for example, 2014-10-01T20:30:00.000Z
YYYY-MM-DDThh:mm:ss.sssTZD (with offset), for example, 2014-10-01T12:30:00.000-08:00
YYYY-MM-DD, for example, 2014-10-01
Unix time in seconds, for example, 1412195400. This is also referred to as Unix Epoch time and represents the number of seconds since midnight, January 1, 1970 UTC.
For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A\n filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The\n acceptable formats are the same as the timestamp formats for\n CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User\n Guide.
Set an end time for the time range during which you want to list SageMaker HyperPod clusters. A filter that returns nodes in a SageMaker HyperPod cluster created before the specified time. The acceptable formats are the same as the timestamp formats for CreationTimeAfter. For more information about the timestamp format, see Timestamp in the Amazon Web Services Command Line Interface User Guide.
The field by which to sort results. The default value is\n CREATION_TIME.
The field by which to sort results. The default value is CREATION_TIME.
The Amazon Resource Name (ARN); of the training plan to filter clusters by. For more information about\n reserving GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
The Amazon Resource Name (ARN); of the training plan to filter clusters by. For more information about reserving GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
If the result of the previous ListClusters request was truncated, the\n response includes a NextToken. To retrieve the next set of clusters, use the\n token in the next request.
If the result of the previous ListClusters request was truncated, the response includes a NextToken. To retrieve the next set of clusters, use the token in the next request.
A filter that returns only Git repositories that were created after the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Git repositories that were created after the specified time.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only Git repositories that were created before the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Git repositories that were created before the specified time.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Git repositories that were last modified after the\n specified time.
" + "smithy.api#documentation": "A filter that returns only Git repositories that were last modified after the specified time.
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Git repositories that were last modified before the\n specified time.
" + "smithy.api#documentation": "A filter that returns only Git repositories that were last modified before the specified time.
" } }, "MaxResults": { @@ -40332,13 +40327,13 @@ "NameContains": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameContains", "traits": { - "smithy.api#documentation": "A string in the Git repositories name. This filter returns only repositories whose\n name contains the specified string.
" + "smithy.api#documentation": "A string in the Git repositories name. This filter returns only repositories whose name contains the specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of a ListCodeRepositoriesOutput request was truncated, the\n response includes a NextToken. To get the next set of Git repositories, use\n the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
Gets a list of summaries of the Git repositories. Each summary specifies the following\n values for the repository:
\nName
\nAmazon Resource Name (ARN)
\nCreation time
\nLast modified time
\nConfiguration information, including the URL location of the repository and\n the ARN of the Amazon Web Services Secrets Manager secret that contains the\n credentials used to access the repository.
\nGets a list of summaries of the Git repositories. Each summary specifies the following values for the repository:
Name
Amazon Resource Name (ARN)
Creation time
Last modified time
Configuration information, including the URL location of the repository and the ARN of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository.
If the result of a ListCodeRepositoriesOutput request was truncated, the\n response includes a NextToken. To get the next set of Git repositories, use\n the token in the next request.
If the result of a ListCodeRepositoriesOutput request was truncated, the response includes a NextToken. To get the next set of Git repositories, use the token in the next request.
Lists model compilation jobs that satisfy various filters.
\nTo create a model compilation job, use CreateCompilationJob. To get information about a particular model\n compilation job you have created, use DescribeCompilationJob.
", + "smithy.api#documentation": "Lists model compilation jobs that satisfy various filters.
To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -40404,7 +40399,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListCompilationJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of model\n compilation jobs, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
A filter that returns the model compilation jobs that were created after a specified\n time.
" + "smithy.api#documentation": "A filter that returns the model compilation jobs that were created after a specified time.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns the model compilation jobs that were created before a specified\n time.
" + "smithy.api#documentation": "A filter that returns the model compilation jobs that were created before a specified time.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns the model compilation jobs that were modified after a specified\n time.
" + "smithy.api#documentation": "A filter that returns the model compilation jobs that were modified after a specified time.
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns the model compilation jobs that were modified before a specified\n time.
" + "smithy.api#documentation": "A filter that returns the model compilation jobs that were modified before a specified time.
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A filter that returns the model compilation jobs whose name contains a specified\n string.
" + "smithy.api#documentation": "A filter that returns the model compilation jobs whose name contains a specified string.
" } }, "StatusEquals": { "target": "com.amazonaws.sagemaker#CompilationJobStatus", "traits": { - "smithy.api#documentation": "A filter that retrieves model compilation jobs with a specific\n CompilationJobStatus status.
A filter that retrieves model compilation jobs with a specific CompilationJobStatus status.
An array of CompilationJobSummary objects, each describing a model compilation job.\n
", + "smithy.api#documentation": "An array of CompilationJobSummary objects, each describing a model compilation job.
", "smithy.api#required": {} } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve\n the next set of model compilation jobs, use this token in the next request.
If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve the next set of model compilation jobs, use this token in the next request.
Filter for after this creation time. The input for this parameter is a Unix timestamp.\n To convert a date and time into a Unix timestamp, see EpochConverter.
" + "smithy.api#documentation": "Filter for after this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
" } }, "CreatedBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filter for before this creation time. The input for this parameter is a Unix timestamp.\n To convert a date and time into a Unix timestamp, see EpochConverter.
" + "smithy.api#documentation": "Filter for before this creation time. The input for this parameter is a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
" } }, "NameContains": { @@ -40565,19 +40560,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#SortQuotaBy", "traits": { - "smithy.api#documentation": "Filter for sorting the list by a given value. For example, sort by name, creation time,\n or status.
" + "smithy.api#documentation": "Filter for sorting the list by a given value. For example, sort by name, creation time, or status.
" } }, "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "The order of the list. By default, listed in Descending order according to\n by SortBy. To change the list order, you can specify SortOrder to\n be Ascending.
The order of the list. By default, listed in Descending order according to by SortBy. To change the list order, you can specify SortOrder to be Ascending.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { @@ -40603,7 +40598,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -40676,7 +40671,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListContexts didn't return the full set of contexts,\n the call returns a token for getting the next set of contexts.
If the previous call to ListContexts didn't return the full set of contexts, the call returns a token for getting the next set of contexts.
A filter that lists the data quality job definitions associated with the specified\n endpoint.
" + "smithy.api#documentation": "A filter that lists the data quality job definitions associated with the specified endpoint.
" } }, "SortBy": { @@ -40746,37 +40741,37 @@ "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
If the result of the previous ListDataQualityJobDefinitions request was\n truncated, the response includes a NextToken. To retrieve the next set of\n transform jobs, use the token in the next request.>
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.>
The maximum number of data quality monitoring job definitions to return in the\n response.
" + "smithy.api#documentation": "The maximum number of data quality monitoring job definitions to return in the response.
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the data quality monitoring job definition name. This filter returns only\n data quality monitoring job definitions whose name contains the specified string.
" + "smithy.api#documentation": "A string in the data quality monitoring job definition name. This filter returns only data quality monitoring job definitions whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only data quality monitoring job definitions created before the\n specified time.
" + "smithy.api#documentation": "A filter that returns only data quality monitoring job definitions created before the specified time.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only data quality monitoring job definitions created after the\n specified time.
" + "smithy.api#documentation": "A filter that returns only data quality monitoring job definitions created after the specified time.
" } } }, @@ -40798,7 +40793,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListDataQualityJobDefinitions request was\n truncated, the response includes a NextToken. To retrieve the next set of data\n quality monitoring job definitions, use the token in the next request.
If the result of the previous ListDataQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of data quality monitoring job definitions, use the token in the next request.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "This parameter defines the maximum number of results that can be return in a single\n response. The MaxResults parameter is an upper bound, not a target. If there are\n more results available than the value specified, a NextToken is provided in the\n response. The NextToken indicates that the user should get the next set of\n results by providing this token as a part of a subsequent call. The default value for\n MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -41091,7 +41086,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The response from the last list when returning a list large enough to need\n tokening.
" + "smithy.api#documentation": "The response from the last list when returning a list large enough to need tokening.
" } }, "MaxResults": { @@ -41139,7 +41134,7 @@ "SortBy": { "target": "com.amazonaws.sagemaker#ListEdgeDeploymentPlansSortBy", "traits": { - "smithy.api#documentation": "The column by which to sort the edge deployment plans. Can be one of\n NAME, DEVICEFLEETNAME, CREATIONTIME,\n LASTMODIFIEDTIME.
The column by which to sort the edge deployment plans. Can be one of NAME, DEVICEFLEETNAME, CREATIONTIME, LASTMODIFIEDTIME.
If the result of the previous ListEndpointConfig request was\n truncated, the response includes a NextToken. To retrieve the next set of\n endpoint configurations, use the token in the next request.
If the result of the previous ListEndpointConfig request was truncated, the response includes a NextToken. To retrieve the next set of endpoint configurations, use the token in the next request.
A string in the endpoint configuration name. This filter returns only endpoint\n configurations whose name contains the specified string.
" + "smithy.api#documentation": "A string in the endpoint configuration name. This filter returns only endpoint configurations whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoint configurations created before the specified\n time (timestamp).
" + "smithy.api#documentation": "A filter that returns only endpoint configurations created before the specified time (timestamp).
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoint configurations with a creation time greater\n than or equal to the specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only endpoint configurations with a creation time greater than or equal to the specified time (timestamp).
" } } }, @@ -41435,7 +41430,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#PaginationToken", "traits": { - "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of\n endpoint configurations, use it in the subsequent request
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of endpoint configurations, use it in the subsequent request
" } } }, @@ -41479,43 +41474,43 @@ "NextToken": { "target": "com.amazonaws.sagemaker#PaginationToken", "traits": { - "smithy.api#documentation": "If the result of a ListEndpoints request was truncated, the response\n includes a NextToken. To retrieve the next set of endpoints, use the token\n in the next request.
If the result of a ListEndpoints request was truncated, the response includes a NextToken. To retrieve the next set of endpoints, use the token in the next request.
The maximum number of endpoints to return in the response. This value defaults to\n 10.
" + "smithy.api#documentation": "The maximum number of endpoints to return in the response. This value defaults to 10.
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#EndpointNameContains", "traits": { - "smithy.api#documentation": "A string in endpoint names. This filter returns only endpoints whose name contains\n the specified string.
" + "smithy.api#documentation": "A string in endpoint names. This filter returns only endpoints whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoints that were created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only endpoints that were created before the specified time (timestamp).
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoints with a creation time greater than or equal to\n the specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only endpoints with a creation time greater than or equal to the specified time (timestamp).
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoints that were modified before the specified\n timestamp.
" + "smithy.api#documentation": "A filter that returns only endpoints that were modified before the specified timestamp.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only endpoints that were modified after the specified\n timestamp.
" + "smithy.api#documentation": "A filter that returns only endpoints that were modified after the specified timestamp.
" } }, "StatusEquals": { @@ -41543,7 +41538,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#PaginationToken", "traits": { - "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of\n training jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
" } } }, @@ -41560,7 +41555,7 @@ "target": "com.amazonaws.sagemaker#ListExperimentsResponse" }, "traits": { - "smithy.api#documentation": "Lists all the experiments in your account. The list can be filtered to show only\n experiments that were created in a specific time range. The list can be sorted by experiment\n name or creation time.
", + "smithy.api#documentation": "Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -41599,13 +41594,13 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListExperiments didn't return the full set of\n experiments, the call returns a token for getting the next set of experiments.
If the previous call to ListExperiments didn't return the full set of experiments, the call returns a token for getting the next set of experiments.
The maximum number of experiments to return in the response. The default value is\n 10.
" + "smithy.api#documentation": "The maximum number of experiments to return in the response. The default value is 10.
" } } }, @@ -41657,7 +41652,7 @@ "NameContains": { "target": "com.amazonaws.sagemaker#FeatureGroupNameContains", "traits": { - "smithy.api#documentation": "A string that partially matches one or more FeatureGroups names. Filters\n FeatureGroups by name.
A string that partially matches one or more FeatureGroups names. Filters FeatureGroups by name.
An OfflineStore status. Filters by OfflineStore status.\n
An OfflineStore status. Filters by OfflineStore status.
Use this parameter to search for FeatureGroupss created after a specific\n date and time.
Use this parameter to search for FeatureGroupss created after a specific date and time.
Use this parameter to search for FeatureGroupss created before a specific\n date and time.
Use this parameter to search for FeatureGroupss created before a specific date and time.
Gets a list of HyperParameterTuningJobSummary objects that\n describe\n the hyperparameter tuning jobs launched in your account.
", + "smithy.api#documentation": "Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -42241,13 +42236,13 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListHyperParameterTuningJobs request was\n truncated, the response includes a NextToken. To retrieve the next set of\n tuning jobs, use the token in the next request.
If the result of the previous ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
The\n maximum number of tuning jobs to return. The default value is\n 10.
" + "smithy.api#documentation": "The maximum number of tuning jobs to return. The default value is 10.
" } }, "SortBy": { @@ -42265,31 +42260,31 @@ "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the tuning job name. This filter returns only tuning jobs whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the tuning job name. This filter returns only tuning jobs whose name contains the specified string.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only tuning jobs that were created after the specified\n time.
" + "smithy.api#documentation": "A filter that returns only tuning jobs that were created after the specified time.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only tuning jobs that were created before the specified\n time.
" + "smithy.api#documentation": "A filter that returns only tuning jobs that were created before the specified time.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only tuning jobs that were modified after the specified\n time.
" + "smithy.api#documentation": "A filter that returns only tuning jobs that were modified after the specified time.
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only tuning jobs that were modified before the specified\n time.
" + "smithy.api#documentation": "A filter that returns only tuning jobs that were modified before the specified time.
" } }, "StatusEquals": { @@ -42310,14 +42305,14 @@ "target": "com.amazonaws.sagemaker#HyperParameterTuningJobSummaries", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of HyperParameterTuningJobSummary objects that\n describe\n the tuning jobs that the ListHyperParameterTuningJobs\n request returned.
A list of HyperParameterTuningJobSummary objects that describe the tuning jobs that the ListHyperParameterTuningJobs request returned.
If the result of this ListHyperParameterTuningJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of tuning jobs,\n use the token in the next request.
If the result of this ListHyperParameterTuningJobs request was truncated, the response includes a NextToken. To retrieve the next set of tuning jobs, use the token in the next request.
Lists the versions of a specified image and their properties. The list can be filtered\n by creation time or modified time.
", + "smithy.api#documentation": "Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -42392,7 +42387,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListImageVersions didn't return the full set of\n versions, the call returns a token for getting the next set of versions.
If the previous call to ListImageVersions didn't return the full set of versions, the call returns a token for getting the next set of versions.
Lists the images in your account and their properties. The list can be filtered by\n creation time or modified time, and whether the image name contains a specified string.
", + "smithy.api#documentation": "Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -42492,7 +42487,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListImages didn't return the full set of images,\n the call returns a token for getting the next set of images.
If the previous call to ListImages didn't return the full set of images, the call returns a token for getting the next set of images.
The field by which to sort the inference components in the response. The default is\n CreationTime.
The field by which to sort the inference components in the response. The default is CreationTime.
A token that you use to get the next set of results following a truncated response. If\n the response to the previous request was truncated, that response provides the value for\n this token.
" + "smithy.api#documentation": "A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The maximum number of inference components to return in the response. This value\n defaults to 10.
" + "smithy.api#documentation": "The maximum number of inference components to return in the response. This value defaults to 10.
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#InferenceComponentNameContains", "traits": { - "smithy.api#documentation": "Filters the results to only those inference components with a name that contains the\n specified string.
" + "smithy.api#documentation": "Filters the results to only those inference components with a name that contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filters the results to only those inference components that were created before the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those inference components that were created before the specified time.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filters the results to only those inference components that were created after the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those inference components that were created after the specified time.
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filters the results to only those inference components that were updated before the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those inference components that were updated before the specified time.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Filters the results to only those inference components that were updated after the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those inference components that were updated after the specified time.
" } }, "StatusEquals": { @@ -42616,13 +42611,13 @@ "EndpointNameEquals": { "target": "com.amazonaws.sagemaker#EndpointName", "traits": { - "smithy.api#documentation": "An endpoint name to filter the listed inference components. The response includes only\n those inference components that are hosted at the specified endpoint.
" + "smithy.api#documentation": "An endpoint name to filter the listed inference components. The response includes only those inference components that are hosted at the specified endpoint.
" } }, "VariantNameEquals": { "target": "com.amazonaws.sagemaker#VariantName", "traits": { - "smithy.api#documentation": "A production variant name to filter the listed inference components. The response\n includes only those inference components that are hosted at the specified variant.
" + "smithy.api#documentation": "A production variant name to filter the listed inference components. The response includes only those inference components that are hosted at the specified variant.
" } } }, @@ -42637,14 +42632,14 @@ "target": "com.amazonaws.sagemaker#InferenceComponentSummaryList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of inference components and their properties that matches any of the filters you\n specified in the request.
", + "smithy.api#documentation": "A list of inference components and their properties that matches any of the filters you specified in the request.
", "smithy.api#required": {} } }, "NextToken": { "target": "com.amazonaws.sagemaker#PaginationToken", "traits": { - "smithy.api#documentation": "The token to use in a subsequent request to get the next set of results following a\n truncated response.
" + "smithy.api#documentation": "The token to use in a subsequent request to get the next set of results following a truncated response.
" } } }, @@ -42682,13 +42677,13 @@ "Type": { "target": "com.amazonaws.sagemaker#InferenceExperimentType", "traits": { - "smithy.api#documentation": "\n Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.\n
" + "smithy.api#documentation": "Selects inference experiments of this type. For the possible types of inference experiments, see CreateInferenceExperiment.
" } }, "StatusEquals": { "target": "com.amazonaws.sagemaker#InferenceExperimentStatus", "traits": { - "smithy.api#documentation": "\n Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.\n
" + "smithy.api#documentation": "Selects inference experiments which are in this status. For the possible statuses, see DescribeInferenceExperiment.
" } }, "CreationTimeAfter": { @@ -42730,7 +42725,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "\n The response from the last list when returning a list large enough to need tokening.\n
" + "smithy.api#documentation": "The response from the last list when returning a list large enough to need tokening.
" } }, "MaxResults": { @@ -42778,7 +42773,7 @@ } ], "traits": { - "smithy.api#documentation": "Returns a list of the subtasks for an Inference Recommender job.
\nThe supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
", + "smithy.api#documentation": "Returns a list of the subtasks for an Inference Recommender job.
The supported subtasks are benchmarks, which evaluate the performance of your model on different instance types.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -42807,7 +42802,7 @@ "StepType": { "target": "com.amazonaws.sagemaker#RecommendationStepType", "traits": { - "smithy.api#documentation": "A filter to return details about the specified type of subtask.
\n\n BENCHMARK: Evaluate the performance of your model on different instance types.
A filter to return details about the specified type of subtask.
BENCHMARK: Evaluate the performance of your model on different instance types.
If the response to a previous ListInferenceRecommendationsJobsRequest request \n was truncated, the response includes a NextToken. To retrieve the next set \n of recommendations, use the token in the next request.
If the response to a previous ListInferenceRecommendationsJobsRequest request was truncated, the response includes a NextToken. To retrieve the next set of recommendations, use the token in the next request.
The Amazon Resource Name (ARN) of the work team for which you want to see labeling\n jobs for.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the work team for which you want to see labeling jobs for.
", "smithy.api#required": {} } }, @@ -43051,25 +43046,25 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListLabelingJobsForWorkteam request was\n truncated, the response includes a NextToken. To retrieve the next set of\n labeling jobs, use the token in the next request.
If the result of the previous ListLabelingJobsForWorkteam request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
A filter that returns only labeling jobs created after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs created after the specified time (timestamp).
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only labeling jobs created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs created before the specified time (timestamp).
" } }, "JobReferenceCodeContains": { "target": "com.amazonaws.sagemaker#JobReferenceCodeContains", "traits": { - "smithy.api#documentation": "A filter the limits jobs to only the ones whose job reference code contains the\n specified string.
" + "smithy.api#documentation": "A filter the limits jobs to only the ones whose job reference code contains the specified string.
" } }, "SortBy": { @@ -43096,14 +43091,14 @@ "target": "com.amazonaws.sagemaker#LabelingJobForWorkteamSummaryList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of LabelingJobSummary objects, each describing a labeling\n job.
An array of LabelingJobSummary objects, each describing a labeling job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n labeling jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
" } } }, @@ -43128,25 +43123,25 @@ "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only labeling jobs created after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs created after the specified time (timestamp).
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only labeling jobs created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs created before the specified time (timestamp).
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only labeling jobs modified after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs modified after the specified time (timestamp).
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only labeling jobs modified before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only labeling jobs modified before the specified time (timestamp).
" } }, "MaxResults": { @@ -43158,13 +43153,13 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListLabelingJobs request was truncated, the\n response includes a NextToken. To retrieve the next set of labeling jobs,\n use the token in the next request.
If the result of the previous ListLabelingJobs request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
A string in the labeling job name. This filter returns only labeling jobs whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.
" } }, "SortBy": { @@ -43196,13 +43191,13 @@ "LabelingJobSummaryList": { "target": "com.amazonaws.sagemaker#LabelingJobSummaryList", "traits": { - "smithy.api#documentation": "An array of LabelingJobSummary objects, each describing a labeling\n job.
An array of LabelingJobSummary objects, each describing a labeling job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n labeling jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.
" } } }, @@ -43225,7 +43220,7 @@ "target": "com.amazonaws.sagemaker#ListLineageGroupsResponse" }, "traits": { - "smithy.api#documentation": "A list of lineage groups shared with your Amazon Web Services account. \n For more information, see \n Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
", + "smithy.api#documentation": "A list of lineage groups shared with your Amazon Web Services account. For more information, see Cross-Account Lineage Tracking in the Amazon SageMaker Developer Guide.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -43252,7 +43247,7 @@ "SortBy": { "target": "com.amazonaws.sagemaker#SortLineageGroupsBy", "traits": { - "smithy.api#documentation": "The parameter by which to sort the results. The default is\n CreationTime.
The parameter by which to sort the results. The default is CreationTime.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n algorithms, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The maximum number of endpoints to return in the response. This value defaults to\n 10.
" + "smithy.api#documentation": "The maximum number of endpoints to return in the response. This value defaults to 10.
" } } }, @@ -43290,7 +43285,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of\n algorithms, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of algorithms, use it in the subsequent request.
" } } }, @@ -43330,13 +43325,13 @@ "CreatedAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Use the CreatedAfter filter to only list tracking servers created after a\n specific date and time. Listed tracking servers are shown with a date and time such as\n \"2024-03-16T01:46:56+00:00\". The CreatedAfter parameter takes in a\n Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedAfter filter to only list tracking servers created after a specific date and time. Listed tracking servers are shown with a date and time such as \"2024-03-16T01:46:56+00:00\". The CreatedAfter parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedBefore filter to only list tracking servers created before a\n specific date and time. Listed tracking servers are shown with a date and time such as\n \"2024-03-16T01:46:56+00:00\". The CreatedBefore parameter takes in\n a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Use the CreatedBefore filter to only list tracking servers created before a specific date and time. Listed tracking servers are shown with a date and time such as \"2024-03-16T01:46:56+00:00\". The CreatedBefore parameter takes in a Unix timestamp. To convert a date and time into a Unix timestamp, see EpochConverter.
Change the order of the listed tracking servers. By default, tracking servers are listed in Descending order by creation time. \n To change the list order, you can specify SortOrder to be Ascending.
Change the order of the listed tracking servers. By default, tracking servers are listed in Descending order by creation time. To change the list order, you can specify SortOrder to be Ascending.
Whether to sort results by the Name or CreationTime field. \n The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The maximum number of model bias jobs to return in the response. The default value is\n 10.
" + "smithy.api#documentation": "The maximum number of model bias jobs to return in the response. The default value is 10.
" } }, "NameContains": { @@ -43488,7 +43483,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } } }, @@ -43570,7 +43565,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListModelCardExportJobs request was\n truncated, the response includes a NextToken. To retrieve the next set of\n model card export jobs, use the token in the next request.
If the response to a previous ListModelCardExportJobs request was truncated, the response includes a NextToken. To retrieve the next set of model card export jobs, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model\n card export jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of model card export jobs, use it in the subsequent request.
" } } }, @@ -43667,7 +43662,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListModelCardVersions request was truncated,\n the response includes a NextToken. To retrieve the next set of model card\n versions, use the token in the next request.
If the response to a previous ListModelCardVersions request was truncated, the response includes a NextToken. To retrieve the next set of model card versions, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model\n card versions, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of model card versions, use it in the subsequent request.
" } } }, @@ -43763,7 +43758,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListModelCards request was truncated, the\n response includes a NextToken. To retrieve the next set of model cards, use\n the token in the next request.
If the response to a previous ListModelCards request was truncated, the response includes a NextToken. To retrieve the next set of model cards, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of model\n cards, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of model cards, use it in the subsequent request.
" } } }, @@ -43835,19 +43830,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionSortKey", "traits": { - "smithy.api#documentation": "Whether to sort results by the Name or CreationTime field. \n The default is CreationTime.
Whether to sort results by the Name or CreationTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } }, "MaxResults": { @@ -43865,13 +43860,13 @@ "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only model explainability jobs created before a specified\n time.
" + "smithy.api#documentation": "A filter that returns only model explainability jobs created before a specified time.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only model explainability jobs created after a specified\n time.
" + "smithy.api#documentation": "A filter that returns only model explainability jobs created after a specified time.
" } } }, @@ -43893,7 +43888,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } } }, @@ -43910,7 +43905,7 @@ "target": "com.amazonaws.sagemaker#ListModelMetadataResponse" }, "traits": { - "smithy.api#documentation": "Lists the domain, framework, task, and model name of standard \n machine learning models found in common model zoos.
", + "smithy.api#documentation": "Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -43925,13 +43920,13 @@ "SearchExpression": { "target": "com.amazonaws.sagemaker#ModelMetadataSearchExpression", "traits": { - "smithy.api#documentation": "One or more filters that searches for the specified resource or resources \n in a search. All resource objects that satisfy the expression's condition are \n included in the search results. Specify the Framework, FrameworkVersion, Domain \n or Task to filter supported. Filter names and values are case-sensitive.
" + "smithy.api#documentation": "One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. Specify the Framework, FrameworkVersion, Domain or Task to filter supported. Filter names and values are case-sensitive.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListModelMetadataResponse request was truncated, \n the response includes a NextToken. To retrieve the next set of model metadata, \n use the token in the next request.
If the response to a previous ListModelMetadataResponse request was truncated, the response includes a NextToken. To retrieve the next set of model metadata, use the token in the next request.
A string in the model group name. This filter returns only model groups whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the model group name. This filter returns only model groups whose name contains the specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListModelPackageGroups request was\n truncated, the response includes a NextToken. To retrieve the next set of\n model groups, use the token in the next request.
If the result of the previous ListModelPackageGroups request was truncated, the response includes a NextToken. To retrieve the next set of model groups, use the token in the next request.
A filter that returns either model groups shared with you or model groups in your own\n account. When the value is CrossAccount, the results show the resources\n made discoverable to you from other accounts. When the value is SameAccount\n or null, the results show resources from your account. The default is\n SameAccount.
A filter that returns either model groups shared with you or model groups in your own account. When the value is CrossAccount, the results show the resources made discoverable to you from other accounts. When the value is SameAccount or null, the results show resources from your account. The default is SameAccount.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n model groups, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of model groups, use it in the subsequent request.
" } } }, @@ -44087,13 +44082,13 @@ "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only model packages created after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only model packages created after the specified time (timestamp).
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only model packages created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only model packages created before the specified time (timestamp).
" } }, "MaxResults": { @@ -44105,37 +44100,37 @@ "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the model package name. This filter returns only model packages whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the model package name. This filter returns only model packages whose name contains the specified string.
" } }, "ModelApprovalStatus": { "target": "com.amazonaws.sagemaker#ModelApprovalStatus", "traits": { - "smithy.api#documentation": "A filter that returns only the model packages with the specified approval\n status.
" + "smithy.api#documentation": "A filter that returns only the model packages with the specified approval status.
" } }, "ModelPackageGroupName": { "target": "com.amazonaws.sagemaker#ArnOrName", "traits": { - "smithy.api#documentation": "A filter that returns only model versions that belong to the specified model\n group.
" + "smithy.api#documentation": "A filter that returns only model versions that belong to the specified model group.
" } }, "ModelPackageType": { "target": "com.amazonaws.sagemaker#ModelPackageType", "traits": { - "smithy.api#documentation": "A filter that returns only the model packages of the specified type. This can be one\n of the following values.
\n\n UNVERSIONED - List only unversioined models. This is the default\n value if no ModelPackageType is specified.
\n VERSIONED - List only versioned models.
\n BOTH - List both versioned and unversioned models.
A filter that returns only the model packages of the specified type. This can be one of the following values.
UNVERSIONED - List only unversioined models. This is the default value if no ModelPackageType is specified.
VERSIONED - List only versioned models.
BOTH - List both versioned and unversioned models.
If the response to a previous ListModelPackages request was truncated,\n the response includes a NextToken. To retrieve the next set of model\n packages, use the token in the next request.
If the response to a previous ListModelPackages request was truncated, the response includes a NextToken. To retrieve the next set of model packages, use the token in the next request.
The parameter by which to sort the results. The default is\n CreationTime.
The parameter by which to sort the results. The default is CreationTime.
An array of ModelPackageSummary objects, each of which lists a model\n package.
An array of ModelPackageSummary objects, each of which lists a model package.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n model packages, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of model packages, use it in the subsequent request.
" } } }, @@ -44195,7 +44190,7 @@ "EndpointName": { "target": "com.amazonaws.sagemaker#EndpointName", "traits": { - "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions that are associated\n with the specified endpoint.
" + "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions that are associated with the specified endpoint.
" } }, "SortBy": { @@ -44207,37 +44202,37 @@ "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
If the result of the previous ListModelQualityJobDefinitions request was\n truncated, the response includes a NextToken. To retrieve the next set of\n model quality monitoring job definitions, use the token in the next request.
If the result of the previous ListModelQualityJobDefinitions request was truncated, the response includes a NextToken. To retrieve the next set of model quality monitoring job definitions, use the token in the next request.
The maximum number of results to return in a call to\n ListModelQualityJobDefinitions.
The maximum number of results to return in a call to ListModelQualityJobDefinitions.
A string in the transform job name. This filter returns only model quality monitoring\n job definitions whose name contains the specified string.
" + "smithy.api#documentation": "A string in the transform job name. This filter returns only model quality monitoring job definitions whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions created before the\n specified time.
" + "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions created before the specified time.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions created after the\n specified time.
" + "smithy.api#documentation": "A filter that returns only model quality monitoring job definitions created after the specified time.
" } } }, @@ -44259,7 +44254,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, Amazon SageMaker AI returns this token. To retrieve the\n next set of model quality monitoring job definitions, use it in the next request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker AI returns this token. To retrieve the next set of model quality monitoring job definitions, use it in the next request.
" } } }, @@ -44303,7 +44298,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#PaginationToken", "traits": { - "smithy.api#documentation": "If the response to a previous ListModels request was truncated, the\n response includes a NextToken. To retrieve the next set of models, use the\n token in the next request.
If the response to a previous ListModels request was truncated, the response includes a NextToken. To retrieve the next set of models, use the token in the next request.
A string in the model name. This filter returns only models whose name contains the\n specified string.
" + "smithy.api#documentation": "A string in the model name. This filter returns only models whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only models created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only models created before the specified time (timestamp).
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only models with a creation time greater than or equal to the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only models with a creation time greater than or equal to the specified time (timestamp).
" } } }, @@ -44342,14 +44337,14 @@ "target": "com.amazonaws.sagemaker#ModelSummaryList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of ModelSummary objects, each of which lists a\n model.
An array of ModelSummary objects, each of which lists a model.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n models, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of models, use it in the subsequent request.
" } } }, @@ -44404,13 +44399,13 @@ "SortOrder": { "target": "com.amazonaws.sagemaker#SortOrder", "traits": { - "smithy.api#documentation": "The sort order, whether Ascending or Descending, of the alert\n history. The default is Descending.
The sort order, whether Ascending or Descending, of the alert history. The default is Descending.
If the result of the previous ListMonitoringAlertHistory request was\n truncated, the response includes a NextToken. To retrieve the next set of\n alerts in the history, use the token in the next request.
If the result of the previous ListMonitoringAlertHistory request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n alerts, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
" } } }, @@ -44499,7 +44494,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListMonitoringAlerts request was truncated,\n the response includes a NextToken. To retrieve the next set of alerts in the\n history, use the token in the next request.
If the result of the previous ListMonitoringAlerts request was truncated, the response includes a NextToken. To retrieve the next set of alerts in the history, use the token in the next request.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n alerts, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of alerts, use it in the subsequent request.
" } } }, @@ -44569,19 +44564,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringExecutionSortKey", "traits": { - "smithy.api#documentation": "Whether to sort the results by the Status, CreationTime, or \n ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } }, "MaxResults": { @@ -44635,13 +44630,13 @@ "MonitoringJobDefinitionName": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionName", "traits": { - "smithy.api#documentation": "Gets a list of the monitoring job runs of the specified monitoring job\n definitions.
" + "smithy.api#documentation": "Gets a list of the monitoring job runs of the specified monitoring job definitions.
" } }, "MonitoringTypeEquals": { "target": "com.amazonaws.sagemaker#MonitoringType", "traits": { - "smithy.api#documentation": "A filter that returns only the monitoring job runs of the specified monitoring\n type.
" + "smithy.api#documentation": "A filter that returns only the monitoring job runs of the specified monitoring type.
" } } }, @@ -44663,7 +44658,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } } }, @@ -44701,19 +44696,19 @@ "SortBy": { "target": "com.amazonaws.sagemaker#MonitoringScheduleSortKey", "traits": { - "smithy.api#documentation": "Whether to sort the results by the Status, CreationTime, or \n ScheduledTime field. The default is CreationTime.
Whether to sort the results by the Status, CreationTime, or ScheduledTime field. The default is CreationTime.
Whether to sort the results in Ascending or Descending order. \n The default is Descending.
Whether to sort the results in Ascending or Descending order. The default is Descending.
The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } }, "MaxResults": { @@ -44761,13 +44756,13 @@ "MonitoringJobDefinitionName": { "target": "com.amazonaws.sagemaker#MonitoringJobDefinitionName", "traits": { - "smithy.api#documentation": "Gets a list of the monitoring schedules for the specified monitoring job\n definition.
" + "smithy.api#documentation": "Gets a list of the monitoring schedules for the specified monitoring job definition.
" } }, "MonitoringTypeEquals": { "target": "com.amazonaws.sagemaker#MonitoringType", "traits": { - "smithy.api#documentation": "A filter that returns only the monitoring schedules for the specified monitoring\n type.
" + "smithy.api#documentation": "A filter that returns only the monitoring schedules for the specified monitoring type.
" } } }, @@ -44789,7 +44784,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use \n it in the next request.
" + "smithy.api#documentation": "The token returned if the response is truncated. To retrieve the next set of job executions, use it in the next request.
" } } }, @@ -44821,7 +44816,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of a ListNotebookInstanceLifecycleConfigs request was\n truncated, the response includes a NextToken. To get the next set of\n lifecycle configurations, use the token in the next request.
If the result of a ListNotebookInstanceLifecycleConfigs request was truncated, the response includes a NextToken. To get the next set of lifecycle configurations, use the token in the next request.
A string in the lifecycle configuration name. This filter returns only lifecycle\n configurations whose name contains the specified string.
" + "smithy.api#documentation": "A string in the lifecycle configuration name. This filter returns only lifecycle configurations whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only lifecycle configurations that were created before the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only lifecycle configurations that were created before the specified time (timestamp).
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only lifecycle configurations that were created after the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only lifecycle configurations that were created after the specified time (timestamp).
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns only lifecycle configurations that were modified before the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only lifecycle configurations that were modified before the specified time (timestamp).
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns only lifecycle configurations that were modified after the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only lifecycle configurations that were modified after the specified time (timestamp).
" } } }, @@ -44883,13 +44878,13 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response is truncated, SageMaker AI returns this token. To get the next\n set of lifecycle configurations, use it in the next request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker AI returns this token. To get the next set of lifecycle configurations, use it in the next request.
" } }, "NotebookInstanceLifecycleConfigs": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigSummaryList", "traits": { - "smithy.api#documentation": "An array of NotebookInstanceLifecycleConfiguration objects, each listing\n a lifecycle configuration.
An array of NotebookInstanceLifecycleConfiguration objects, each listing a lifecycle configuration.
Returns a list of the SageMaker AI notebook instances in the requester's\n account in an Amazon Web Services Region.
", + "smithy.api#documentation": "Returns a list of the SageMaker AI notebook instances in the requester's account in an Amazon Web Services Region.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -44921,7 +44916,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": " If the previous call to the ListNotebookInstances is truncated, the\n response includes a NextToken. You can use this token in your subsequent\n ListNotebookInstances request to fetch the next set of notebook\n instances.
You might specify a filter or a sort order in your request. When response is\n truncated, you must use the same values for the filer and sort order in the next\n request.
\n If the previous call to the ListNotebookInstances is truncated, the response includes a NextToken. You can use this token in your subsequent ListNotebookInstances request to fetch the next set of notebook instances.
You might specify a filter or a sort order in your request. When response is truncated, you must use the same values for the filer and sort order in the next request.
A string in the notebook instances' name. This filter returns only notebook\n instances whose name contains the specified string.
" + "smithy.api#documentation": "A string in the notebook instances' name. This filter returns only notebook instances whose name contains the specified string.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only notebook instances that were created before the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only notebook instances that were created before the specified time (timestamp).
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "A filter that returns only notebook instances that were created after the specified\n time (timestamp).
" + "smithy.api#documentation": "A filter that returns only notebook instances that were created after the specified time (timestamp).
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns only notebook instances that were modified before the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only notebook instances that were modified before the specified time (timestamp).
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "A filter that returns only notebook instances that were modified after the\n specified time (timestamp).
" + "smithy.api#documentation": "A filter that returns only notebook instances that were modified after the specified time (timestamp).
" } }, "StatusEquals": { @@ -44981,19 +44976,19 @@ "NotebookInstanceLifecycleConfigNameContains": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigName", "traits": { - "smithy.api#documentation": "A string in the name of a notebook instances lifecycle configuration associated with\n this notebook instance. This filter returns only notebook instances associated with a\n lifecycle configuration with a name that contains the specified string.
" + "smithy.api#documentation": "A string in the name of a notebook instances lifecycle configuration associated with this notebook instance. This filter returns only notebook instances associated with a lifecycle configuration with a name that contains the specified string.
" } }, "DefaultCodeRepositoryContains": { "target": "com.amazonaws.sagemaker#CodeRepositoryContains", "traits": { - "smithy.api#documentation": "A string in the name or URL of a Git repository associated with this notebook\n instance. This filter returns only notebook instances associated with a git repository\n with a name that contains the specified string.
" + "smithy.api#documentation": "A string in the name or URL of a Git repository associated with this notebook instance. This filter returns only notebook instances associated with a git repository with a name that contains the specified string.
" } }, "AdditionalCodeRepositoryEquals": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameOrUrl", "traits": { - "smithy.api#documentation": "A filter that returns only notebook instances with associated with the specified git\n repository.
" + "smithy.api#documentation": "A filter that returns only notebook instances with associated with the specified git repository.
" } } }, @@ -45007,13 +45002,13 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the response to the previous ListNotebookInstances request was\n truncated, SageMaker AI returns this token. To retrieve the next set of notebook\n instances, use the token in the next request.
If the response to the previous ListNotebookInstances request was truncated, SageMaker AI returns this token. To retrieve the next set of notebook instances, use the token in the next request.
An array of NotebookInstanceSummary objects, one for each notebook\n instance.
An array of NotebookInstanceSummary objects, one for each notebook instance.
A token that you use to get the next set of results following a truncated response. If\n the response to the previous request was truncated, that response provides the value for\n this token.
" + "smithy.api#documentation": "A token that you use to get the next set of results following a truncated response. If the response to the previous request was truncated, that response provides the value for this token.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The maximum number of optimization jobs to return in the response. The default is\n 50.
" + "smithy.api#documentation": "The maximum number of optimization jobs to return in the response. The default is 50.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "Filters the results to only those optimization jobs that were created after the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those optimization jobs that were created after the specified time.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#CreationTime", "traits": { - "smithy.api#documentation": "Filters the results to only those optimization jobs that were created before the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those optimization jobs that were created before the specified time.
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "Filters the results to only those optimization jobs that were updated after the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those optimization jobs that were updated after the specified time.
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#LastModifiedTime", "traits": { - "smithy.api#documentation": "Filters the results to only those optimization jobs that were updated before the\n specified time.
" + "smithy.api#documentation": "Filters the results to only those optimization jobs that were updated before the specified time.
" } }, "OptimizationContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "Filters the results to only those optimization jobs that apply the specified\n optimization techniques. You can specify either Quantization or\n Compilation.
Filters the results to only those optimization jobs that apply the specified optimization techniques. You can specify either Quantization or Compilation.
Filters the results to only those optimization jobs with a name that contains the\n specified string.
" + "smithy.api#documentation": "Filters the results to only those optimization jobs with a name that contains the specified string.
" } }, "StatusEquals": { @@ -45099,13 +45094,13 @@ "SortBy": { "target": "com.amazonaws.sagemaker#ListOptimizationJobsSortBy", "traits": { - "smithy.api#documentation": "The field by which to sort the optimization jobs in the response. The default is\n CreationTime\n
The field by which to sort the optimization jobs in the response. The default is CreationTime
The sort order for results. The default is Ascending\n
The sort order for results. The default is Ascending
A list of optimization jobs and their properties that matches any of the filters you\n specified in the request.
", + "smithy.api#documentation": "A list of optimization jobs and their properties that matches any of the filters you specified in the request.
", "smithy.api#required": {} } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The token to use in a subsequent request to get the next set of results following a\n truncated response.
" + "smithy.api#documentation": "The token to use in a subsequent request to get the next set of results following a truncated response.
" } } }, @@ -45182,13 +45177,13 @@ "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "This parameter defines the maximum number of results that can be returned in a single\n response. The MaxResults parameter is an upper bound, not a target. If there are\n more results available than the value specified, a NextToken is provided in the\n response. The NextToken indicates that the user should get the next set of\n results by providing this token as a part of a subsequent call. The default value for\n MaxResults is 10.
This parameter defines the maximum number of results that can be returned in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -45208,7 +45203,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -45251,7 +45246,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListPipelineExecutionSteps request was truncated,\n the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
A list of PipeLineExecutionStep objects. Each\n PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus,\n and Metadata. Metadata is an object with properties for each job that contains relevant\n information about the job created by the step.
A list of PipeLineExecutionStep objects. Each PipeLineExecutionStep consists of StepName, StartTime, EndTime, StepStatus, and Metadata. Metadata is an object with properties for each job that contains relevant information about the job created by the step.
If the result of the previous ListPipelineExecutionSteps request was truncated,\n the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
If the result of the previous ListPipelineExecutionSteps request was truncated, the response includes a NextToken. To retrieve the next set of pipeline execution steps, use the token in the next request.
A filter that returns the pipeline executions that were created after a specified\n time.
" + "smithy.api#documentation": "A filter that returns the pipeline executions that were created after a specified time.
" } }, "CreatedBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns the pipeline executions that were created before a specified\n time.
" + "smithy.api#documentation": "A filter that returns the pipeline executions that were created before a specified time.
" } }, "SortBy": { @@ -45352,7 +45347,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListPipelineExecutions request was truncated,\n the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
Contains a sorted list of pipeline execution summary objects matching the specified\n filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date,\n and the status. This list can be empty.
" + "smithy.api#documentation": "Contains a sorted list of pipeline execution summary objects matching the specified filters. Each run summary includes the Amazon Resource Name (ARN) of the pipeline execution, the run date, and the status. This list can be empty.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListPipelineExecutions request was truncated,\n the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineExecutions request was truncated, the response includes a NextToken. To retrieve the next set of pipeline executions, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated,\n the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated,\n the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
If the result of the previous ListPipelineParametersForExecution request was truncated, the response includes a NextToken. To retrieve the next set of parameters, use the token in the next request.
A filter that returns the pipelines that were created after a specified\n time.
" + "smithy.api#documentation": "A filter that returns the pipelines that were created after a specified time.
" } }, "CreatedBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns the pipelines that were created before a specified\n time.
" + "smithy.api#documentation": "A filter that returns the pipelines that were created before a specified time.
" } }, "SortBy": { @@ -45511,7 +45506,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListPipelines request was truncated,\n the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
Contains a sorted list of PipelineSummary objects matching the specified\n filters. Each PipelineSummary consists of PipelineArn, PipelineName,\n ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and\n RoleArn. This list can be empty.
Contains a sorted list of PipelineSummary objects matching the specified filters. Each PipelineSummary consists of PipelineArn, PipelineName, ExperimentName, PipelineDescription, CreationTime, LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
If the result of the previous ListPipelines request was truncated,\n the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
If the result of the previous ListPipelines request was truncated, the response includes a NextToken. To retrieve the next set of pipelines, use the token in the next request.
A string in the processing job name. This filter returns only processing jobs whose\n name contains the specified string.
" + "smithy.api#documentation": "A string in the processing job name. This filter returns only processing jobs whose name contains the specified string.
" } }, "StatusEquals": { @@ -45617,7 +45612,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListProcessingJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of processing\n jobs, use the token in the next request.
If the result of the previous ListProcessingJobs request was truncated, the response includes a NextToken. To retrieve the next set of processing jobs, use the token in the next request.
An array of ProcessingJobSummary objects, each listing a processing\n job.
An array of ProcessingJobSummary objects, each listing a processing job.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of\n processing jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of processing jobs, use it in the subsequent request.
" } } }, @@ -45676,13 +45671,13 @@ "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns the projects that were created after a specified\n time.
" + "smithy.api#documentation": "A filter that returns the projects that were created after a specified time.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns the projects that were created before a specified\n time.
" + "smithy.api#documentation": "A filter that returns the projects that were created before a specified time.
" } }, "MaxResults": { @@ -45694,13 +45689,13 @@ "NameContains": { "target": "com.amazonaws.sagemaker#ProjectEntityName", "traits": { - "smithy.api#documentation": "A filter that returns the projects whose name contains a specified\n string.
" + "smithy.api#documentation": "A filter that returns the projects whose name contains a specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListProjects request was truncated,\n the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListProjects request was truncated, the response includes a NextToken. To retrieve the next set of projects, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of model\n compilation jobs, use the token in the next request.
If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken. To retrieve the next set of model compilation jobs, use the token in the next request.
Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of\n ResourceCatalogs viewable is 1000.
Lists Amazon SageMaker Catalogs based on given filters and orders. The maximum number of ResourceCatalogs viewable is 1000.
A string that partially matches one or more ResourceCatalogs names.\n Filters ResourceCatalog by name.
A string that partially matches one or more ResourceCatalogs names. Filters ResourceCatalog by name.
Use this parameter to search for ResourceCatalogs created after a\n specific date and time.
Use this parameter to search for ResourceCatalogs created after a specific date and time.
Use this parameter to search for ResourceCatalogs created before a\n specific date and time.
Use this parameter to search for ResourceCatalogs created before a specific date and time.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "This parameter defines the maximum number of results that can be return in a single\n response. The MaxResults parameter is an upper bound, not a target. If there are\n more results available than the value specified, a NextToken is provided in the\n response. The NextToken indicates that the user should get the next set of\n results by providing this token as a part of a subsequent call. The default value for\n MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
The parameter by which to sort the results. The default is\n CreationTime.
The parameter by which to sort the results. The default is CreationTime.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -45921,7 +45916,7 @@ "target": "com.amazonaws.sagemaker#ListStageDevicesResponse" }, "traits": { - "smithy.api#documentation": "Lists devices allocated to the stage, containing detailed device information and\n deployment status.
", + "smithy.api#documentation": "Lists devices allocated to the stage, containing detailed device information and deployment status.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -45936,7 +45931,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "The response from the last list when returning a list large enough to neeed\n tokening.
" + "smithy.api#documentation": "The response from the last list when returning a list large enough to neeed tokening.
" } }, "MaxResults": { @@ -46008,7 +46003,7 @@ } ], "traits": { - "smithy.api#documentation": "Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services\n Account.
", + "smithy.api#documentation": "Lists the Amazon SageMaker AI Studio Lifecycle Configurations in your Amazon Web Services Account.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -46023,49 +46018,49 @@ "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "The total number of items to return in the response. If the total number of items\n available is more than the value specified, a NextToken is provided in the\n response. To resume pagination, provide the NextToken value in the as part of a\n subsequent call. The default value is 10.
The total number of items to return in the response. If the total number of items available is more than the value specified, a NextToken is provided in the response. To resume pagination, provide the NextToken value in the as part of a subsequent call. The default value is 10.
If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle\n Configurations, the call returns a token for getting the next set of Lifecycle\n Configurations.
" + "smithy.api#documentation": "If the previous call to ListStudioLifecycleConfigs didn't return the full set of Lifecycle Configurations, the call returns a token for getting the next set of Lifecycle Configurations.
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#StudioLifecycleConfigName", "traits": { - "smithy.api#documentation": "A string in the Lifecycle Configuration name. This filter returns only Lifecycle\n Configurations whose name contains the specified string.
" + "smithy.api#documentation": "A string in the Lifecycle Configuration name. This filter returns only Lifecycle Configurations whose name contains the specified string.
" } }, "AppTypeEquals": { "target": "com.amazonaws.sagemaker#StudioLifecycleConfigAppType", "traits": { - "smithy.api#documentation": "A parameter to search for the App Type to which the Lifecycle Configuration is\n attached.
" + "smithy.api#documentation": "A parameter to search for the App Type to which the Lifecycle Configuration is attached.
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Lifecycle Configurations created on or before the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Lifecycle Configurations created on or before the specified time.
" } }, "CreationTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Lifecycle Configurations created on or after the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Lifecycle Configurations created on or after the specified time.
" } }, "ModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Lifecycle Configurations modified before the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Lifecycle Configurations modified before the specified time.
" } }, "ModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only Lifecycle Configurations modified after the specified\n time.
" + "smithy.api#documentation": "A filter that returns only Lifecycle Configurations modified after the specified time.
" } }, "SortBy": { @@ -46091,7 +46086,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "StudioLifecycleConfigs": { @@ -46114,7 +46109,7 @@ "target": "com.amazonaws.sagemaker#ListSubscribedWorkteamsResponse" }, "traits": { - "smithy.api#documentation": "Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The\n list may be empty if no work team satisfies the filter specified in the\n NameContains parameter.
Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
A string in the work team name. This filter returns only work teams whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the work team name. This filter returns only work teams whose name contains the specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListSubscribedWorkteams request was\n truncated, the response includes a NextToken. To retrieve the next set of\n labeling jobs, use the token in the next request.
If the result of the previous ListSubscribedWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of\n work teams, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
" } } }, @@ -46196,14 +46191,14 @@ "target": "com.amazonaws.sagemaker#ResourceArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the resource whose tags you want to\n retrieve.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
", "smithy.api#required": {} } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": " If the response to the previous ListTags request is truncated, SageMaker\n returns this token. To retrieve the next set of tags, use it in the subsequent request.\n
If the response to the previous ListTags request is truncated, SageMaker returns this token. To retrieve the next set of tags, use it in the subsequent request.
If response is truncated, SageMaker includes a token in the response. You can use this\n token in your subsequent request to fetch next set of tokens.
" + "smithy.api#documentation": "If response is truncated, SageMaker includes a token in the response. You can use this token in your subsequent request to fetch next set of tokens.
" } } }, @@ -46254,7 +46249,7 @@ "target": "com.amazonaws.sagemaker#ListTrainingJobsResponse" }, "traits": { - "smithy.api#documentation": "Lists training jobs.
\nWhen StatusEquals and MaxResults are set at the same\n time, the MaxResults number of training jobs are first retrieved\n ignoring the StatusEquals parameter and then they are filtered by the\n StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following\n parameters:
\n { ... MaxResults: 100, StatusEquals: InProgress ... }\n
First, 100 trainings jobs with any status, including those other than\n InProgress, are selected (sorted according to the creation time,\n from the most current to the oldest). Next, those with a status of\n InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI\n code.
\n\n aws sagemaker list-training-jobs --max-results 100 --status-equals\n InProgress\n
Lists training jobs.
When StatusEquals and MaxResults are set at the same time, the MaxResults number of training jobs are first retrieved ignoring the StatusEquals parameter and then they are filtered by the StatusEquals parameter, which is returned as a response.
For example, if ListTrainingJobs is invoked with the following parameters:
{ ... MaxResults: 100, StatusEquals: InProgress ... }
First, 100 trainings jobs with any status, including those other than InProgress, are selected (sorted according to the creation time, from the most current to the oldest). Next, those with a status of InProgress are returned.
You can quickly test the API using the following Amazon Web Services CLI code.
aws sagemaker list-training-jobs --max-results 100 --status-equals InProgress
Gets a list of TrainingJobSummary objects that describe the training jobs that a\n hyperparameter tuning job launched.
", + "smithy.api#documentation": "Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -46300,7 +46295,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListTrainingJobsForHyperParameterTuningJob\n request was truncated, the response includes a NextToken. To retrieve the\n next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training\n jobs that did not return an objective metric are not listed.
The field to sort results by. The default is Name.
If the value of this field is FinalObjectiveMetricValue, any training jobs that did not return an objective metric are not listed.
A list of TrainingJobSummary objects that\n describe\n the training jobs that the\n ListTrainingJobsForHyperParameterTuningJob request returned.
A list of TrainingJobSummary objects that describe the training jobs that the ListTrainingJobsForHyperParameterTuningJob request returned.
If the result of this ListTrainingJobsForHyperParameterTuningJob request\n was truncated, the response includes a NextToken. To retrieve the next set\n of training jobs, use the token in the next request.
If the result of this ListTrainingJobsForHyperParameterTuningJob request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
If the result of the previous ListTrainingJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of training\n jobs, use the token in the next request.
If the result of the previous ListTrainingJobs request was truncated, the response includes a NextToken. To retrieve the next set of training jobs, use the token in the next request.
A filter that returns only training jobs created after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only training jobs created after the specified time (timestamp).
" } }, "CreationTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only training jobs created before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only training jobs created before the specified time (timestamp).
" } }, "LastModifiedTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only training jobs modified after the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only training jobs modified after the specified time (timestamp).
" } }, "LastModifiedTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter that returns only training jobs modified before the specified time\n (timestamp).
" + "smithy.api#documentation": "A filter that returns only training jobs modified before the specified time (timestamp).
" } }, "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the training job name. This filter returns only training jobs whose\n name contains the specified string.
" + "smithy.api#documentation": "A string in the training job name. This filter returns only training jobs whose name contains the specified string.
" } }, "StatusEquals": { @@ -46426,7 +46421,7 @@ "TrainingPlanArnEquals": { "target": "com.amazonaws.sagemaker#TrainingPlanArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN); of the training plan to filter training jobs by. For more information\n about reserving GPU capacity for your SageMaker training jobs using Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
The Amazon Resource Name (ARN); of the training plan to filter training jobs by. For more information about reserving GPU capacity for your SageMaker training jobs using Amazon SageMaker Training Plan, see CreateTrainingPlan .
An array of TrainingJobSummary objects, each listing a training\n job.
An array of TrainingJobSummary objects, each listing a training job.
If the response is truncated, SageMaker returns this token. To retrieve the next set of\n training jobs, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, SageMaker returns this token. To retrieve the next set of training jobs, use it in the subsequent request.
" } } }, @@ -46594,7 +46589,7 @@ "NameContains": { "target": "com.amazonaws.sagemaker#NameContains", "traits": { - "smithy.api#documentation": "A string in the transform job name. This filter returns only transform jobs whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the transform job name. This filter returns only transform jobs whose name contains the specified string.
" } }, "StatusEquals": { @@ -46618,7 +46613,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListTransformJobs request was truncated,\n the response includes a NextToken. To retrieve the next set of transform\n jobs, use the token in the next request.
If the result of the previous ListTransformJobs request was truncated, the response includes a NextToken. To retrieve the next set of transform jobs, use the token in the next request.
An array of\n TransformJobSummary\n objects.
An array of TransformJobSummary objects.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of\n transform jobs, use it in the next request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of transform jobs, use it in the next request.
" } } }, @@ -46674,7 +46669,7 @@ } ], "traits": { - "smithy.api#documentation": "Lists the trial components in your account. You can sort the list by trial component name\n or creation time. You can filter the list to show only components that were created in a\n specific time range. You can also filter on one of the following:
\n\n ExperimentName\n
\n SourceArn\n
\n TrialName\n
Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:
ExperimentName
SourceArn
TrialName
A filter that returns only components that are part of the specified experiment. If you\n specify ExperimentName, you can't filter by SourceArn or\n TrialName.
A filter that returns only components that are part of the specified experiment. If you specify ExperimentName, you can't filter by SourceArn or TrialName.
A filter that returns only components that are part of the specified trial. If you specify\n TrialName, you can't filter by ExperimentName or\n SourceArn.
A filter that returns only components that are part of the specified trial. If you specify TrialName, you can't filter by ExperimentName or SourceArn.
A filter that returns only components that have the specified source Amazon Resource Name (ARN). \n If you specify SourceArn, you can't filter by ExperimentName\n or TrialName.
A filter that returns only components that have the specified source Amazon Resource Name (ARN). If you specify SourceArn, you can't filter by ExperimentName or TrialName.
The maximum number of components to return in the response. The default value is\n 10.
" + "smithy.api#documentation": "The maximum number of components to return in the response. The default value is 10.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListTrialComponents didn't return the full set of\n components, the call returns a token for getting the next set of components.
If the previous call to ListTrialComponents didn't return the full set of components, the call returns a token for getting the next set of components.
Lists the trials in your account. Specify an experiment name to limit the list to the\n trials that are part of that experiment. Specify a trial component name to limit the list to\n the trials that associated with that trial component. The list can be filtered to show only\n trials that were created in a specific time range. The list can be sorted by trial name or\n creation time.
", + "smithy.api#documentation": "Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -46800,7 +46795,7 @@ "TrialComponentName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "A filter that returns only trials that are associated with the specified trial\n component.
" + "smithy.api#documentation": "A filter that returns only trials that are associated with the specified trial component.
" } }, "CreatedAfter": { @@ -46836,7 +46831,7 @@ "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the previous call to ListTrials didn't return the full set of trials, the\n call returns a token for getting the next set of trials.
If the previous call to ListTrials didn't return the full set of trials, the call returns a token for getting the next set of trials.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } }, "MaxResults": { "target": "com.amazonaws.sagemaker#MaxResults", "traits": { - "smithy.api#documentation": "This parameter defines the maximum number of results that can be return in a single\n response. The MaxResults parameter is an upper bound, not a target. If there are\n more results available than the value specified, a NextToken is provided in the\n response. The NextToken indicates that the user should get the next set of\n results by providing this token as a part of a subsequent call. The default value for\n MaxResults is 10.
This parameter defines the maximum number of results that can be return in a single response. The MaxResults parameter is an upper bound, not a target. If there are more results available than the value specified, a NextToken is provided in the response. The NextToken indicates that the user should get the next set of results by providing this token as a part of a subsequent call. The default value for MaxResults is 10.
If the previous response was truncated, you will receive this token. Use it in your next\n request to receive the next set of results.
" + "smithy.api#documentation": "If the previous response was truncated, you will receive this token. Use it in your next request to receive the next set of results.
" } } }, @@ -46955,7 +46950,7 @@ "target": "com.amazonaws.sagemaker#ListWorkforcesResponse" }, "traits": { - "smithy.api#documentation": "Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only \n have one private workforce per Amazon Web Services Region.
", + "smithy.api#documentation": "Use this operation to list all private and vendor workforces in an Amazon Web Services Region. Note that you can only have one private workforce per Amazon Web Services Region.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -47050,7 +47045,7 @@ "target": "com.amazonaws.sagemaker#ListWorkteamsResponse" }, "traits": { - "smithy.api#documentation": "Gets a list of private work teams that you have defined in a region. The list may be empty if\n no work team satisfies the filter specified in the NameContains\n parameter.
Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.
A string in the work team's name. This filter returns only work teams whose name\n contains the specified string.
" + "smithy.api#documentation": "A string in the work team's name. This filter returns only work teams whose name contains the specified string.
" } }, "NextToken": { "target": "com.amazonaws.sagemaker#NextToken", "traits": { - "smithy.api#documentation": "If the result of the previous ListWorkteams request was truncated, the\n response includes a NextToken. To retrieve the next set of labeling jobs,\n use the token in the next request.
If the result of the previous ListWorkteams request was truncated, the response includes a NextToken. To retrieve the next set of labeling jobs, use the token in the next request.
If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of\n work teams, use it in the subsequent request.
" + "smithy.api#documentation": "If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.
" } } }, @@ -47381,7 +47376,7 @@ "OidcMemberDefinition": { "target": "com.amazonaws.sagemaker#OidcMemberDefinition", "traits": { - "smithy.api#documentation": "A list user groups that exist in your OIDC Identity Provider (IdP). \n One to ten groups can be used to create a single private work team. \n When you add a user group to the list of Groups, you can add that user group to one or more\n private work teams. If you add a user group to a private work team, all workers in that user group \n are added to the work team.
A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
The name of the standard metric.
\nFor definitions of the standard metrics, see \n Autopilot candidate metrics\n .
The name of the standard metric.
For definitions of the standard metrics, see Autopilot candidate metrics .
A regular expression that searches the output of a training job and gets the value of\n the metric. For more information about using regular expressions to define metrics, see\n Defining metrics and environment variables.
", + "smithy.api#documentation": "A regular expression that searches the output of a training job and gets the value of the metric. For more information about using regular expressions to define metrics, see Defining metrics and environment variables.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies a metric that the training algorithm writes to stderr or\n stdout. You can view these logs to understand how your training job\n performs and check for any errors encountered during training. SageMaker hyperparameter\n tuning captures all defined metrics. Specify one of the defined metrics to use as an\n objective metric using the TuningObjective parameter in the\n HyperParameterTrainingJobDefinition API to evaluate job performance\n during hyperparameter tuning.
Specifies a metric that the training algorithm writes to stderr or stdout. You can view these logs to understand how your training job performs and check for any errors encountered during training. SageMaker hyperparameter tuning captures all defined metrics. Specify one of the defined metrics to use as an objective metric using the TuningObjective parameter in the HyperParameterTrainingJobDefinition API to evaluate job performance during hyperparameter tuning.
The Amazon Resource Name (ARN) of the IAM role that you specified for the\n model.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
" } }, "VpcConfig": { @@ -47843,13 +47838,13 @@ "EnableNetworkIsolation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Isolates the model container. No inbound or outbound network calls can be made to or\n from the model container.
" + "smithy.api#documentation": "Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of key-value pairs associated with the model. For more information, see\n Tagging Amazon Web Services\n resources in the Amazon Web Services General Reference Guide.
" + "smithy.api#documentation": "A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } }, "DeploymentRecommendation": { @@ -47870,13 +47865,13 @@ "target": "com.amazonaws.sagemaker#AcceptEula", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies agreement to the model end-user license agreement (EULA). The\n AcceptEula value must be explicitly defined as True in order\n to accept the EULA that this model requires. You are responsible for reviewing and\n complying with any applicable license terms and making sure they are acceptable for your\n use case before downloading or using a model.
Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The access configuration file to control access to the ML model. You can explicitly accept the model\n end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
\nIf you are an AutoML user, see the Optional Parameters section of\n Create an AutoML job to fine-tune text generation models using the\n API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML\n API.
\nThe access configuration file to control access to the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig.
If you are a Jumpstart user, see the End-user license agreements section for more details on accepting the EULA.
If you are an AutoML user, see the Optional Parameters section of Create an AutoML job to fine-tune text generation models using the API for details on How to set the EULA acceptance when fine-tuning a model using the AutoML API.
The path of the S3 object that contains the model artifacts. For example,\n s3://bucket-name/keynameprefix/model.tar.gz.
The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
Provides information about the location that is configured for storing model\n artifacts.
\nModel artifacts are outputs that result from training a model. They typically consist\n of trained parameters, a model definition that describes how to compute inferences, and\n other metadata. A SageMaker container stores your trained model artifacts in the\n /opt/ml/model directory. After training has completed, by default,\n these artifacts are uploaded to your Amazon S3 bucket as compressed files.
Provides information about the location that is configured for storing model artifacts.
Model artifacts are outputs that result from training a model. They typically consist of trained parameters, a model definition that describes how to compute inferences, and other metadata. A SageMaker container stores your trained model artifacts in the /opt/ml/model directory. After training has completed, by default, these artifacts are uploaded to your Amazon S3 bucket as compressed files.
JSON formatted S3 file that defines bias parameters. For more information on this JSON\n configuration file, see Configure\n bias parameters.
", + "smithy.api#documentation": "JSON formatted S3 file that defines bias parameters. For more information on this JSON configuration file, see Configure bias parameters.
", "smithy.api#required": {} } }, @@ -48047,7 +48042,7 @@ "ModelCardStatus": { "target": "com.amazonaws.sagemaker#ModelCardStatus", "traits": { - "smithy.api#documentation": "The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.\n
" + "smithy.api#documentation": "The model package group that contains the model package. Only relevant for model cards created for model packages in the Amazon SageMaker Model Registry.
" } } }, @@ -48359,7 +48354,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "A Key Management Service\n key\n ID to use for encrypting a model card.
" + "smithy.api#documentation": "A Key Management Service key ID to use for encrypting a model card.
" } } }, @@ -48453,7 +48448,7 @@ "target": "com.amazonaws.sagemaker#ModelCardStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card version within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
The timeout value in seconds for an invocation request. The default value is\n 600.
" + "smithy.api#documentation": "The timeout value in seconds for an invocation request. The default value is 600.
" } }, "InvocationsMaxRetries": { "target": "com.amazonaws.sagemaker#InvocationsMaxRetries", "traits": { - "smithy.api#documentation": "The maximum number of retries when invocation requests are failing. The default value\n is 3.
" + "smithy.api#documentation": "The maximum number of retries when invocation requests are failing. The default value is 3.
" } } }, "traits": { - "smithy.api#documentation": "Configures the timeout and maximum number of retries for processing a transform job\n invocation.
" + "smithy.api#documentation": "Configures the timeout and maximum number of retries for processing a transform job invocation.
" } }, "com.amazonaws.sagemaker#ModelCompilationConfig": { @@ -48701,7 +48696,7 @@ } }, "traits": { - "smithy.api#documentation": "An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into\n InAlert status.
An alert action taken to light up an icon on the Amazon SageMaker Model Dashboard when an alert goes into InAlert status.
For models created in SageMaker, this is the model ARN. For models created\n outside of SageMaker, this is a user-customized string.
" + "smithy.api#documentation": "For models created in SageMaker, this is the model ARN. For models created outside of SageMaker, this is a user-customized string.
" } }, "RiskRating": { @@ -48921,7 +48916,7 @@ } }, "traits": { - "smithy.api#documentation": "Specifies the location of ML model data to deploy. If specified, you must specify one\n and only one of the available data sources.
" + "smithy.api#documentation": "Specifies the location of ML model data to deploy. If specified, you must specify one and only one of the available data sources.
" } }, "com.amazonaws.sagemaker#ModelDeployConfig": { @@ -48930,18 +48925,18 @@ "AutoGenerateEndpointName": { "target": "com.amazonaws.sagemaker#AutoGenerateEndpointName", "traits": { - "smithy.api#documentation": "Set to True to automatically generate an endpoint name for a one-click\n Autopilot model deployment; set to False otherwise. The default value is\n False.
If you set AutoGenerateEndpointName to True, do not specify\n the EndpointName; otherwise a 400 error is thrown.
Set to True to automatically generate an endpoint name for a one-click Autopilot model deployment; set to False otherwise. The default value is False.
If you set AutoGenerateEndpointName to True, do not specify the EndpointName; otherwise a 400 error is thrown.
Specifies the endpoint name to use for a one-click Autopilot model deployment if the\n endpoint name is not generated automatically.
\nSpecify the EndpointName if and only if you set\n AutoGenerateEndpointName to False; otherwise a 400 error is\n thrown.
Specifies the endpoint name to use for a one-click Autopilot model deployment if the endpoint name is not generated automatically.
Specify the EndpointName if and only if you set AutoGenerateEndpointName to False; otherwise a 400 error is thrown.
Specifies how to generate the endpoint name for an automatic one-click Autopilot model\n deployment.
" + "smithy.api#documentation": "Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
" } }, "com.amazonaws.sagemaker#ModelDeployResult": { @@ -48950,7 +48945,7 @@ "EndpointName": { "target": "com.amazonaws.sagemaker#EndpointName", "traits": { - "smithy.api#documentation": "The name of the endpoint to which the model has been deployed.
\nIf model deployment fails, this field is omitted from the response.
\nThe name of the endpoint to which the model has been deployed.
If model deployment fails, this field is omitted from the response.
Provides a hash value that uniquely identifies the stored model\n artifacts.
" + "smithy.api#documentation": "Provides a hash value that uniquely identifies the stored model artifacts.
" } } }, @@ -48987,7 +48982,7 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "JSON formatted Amazon S3 file that defines explainability parameters. For more\n information on this JSON configuration file, see Configure model explainability parameters.
", + "smithy.api#documentation": "JSON formatted Amazon S3 file that defines explainability parameters. For more information on this JSON configuration file, see Configure model explainability parameters.
", "smithy.api#required": {} } }, @@ -49043,7 +49038,7 @@ "target": "com.amazonaws.sagemaker#ModelInfrastructureType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The inference option to which to deploy your model. Possible values are the following:
\n\n RealTime: Deploy to real-time inference.
The inference option to which to deploy your model. Possible values are the following:
RealTime: Deploy to real-time inference.
The model latency percentile threshold. Acceptable values are P95 and P99.\n For custom load tests, specify the value as P95.
The model latency percentile threshold. Acceptable values are P95 and P99. For custom load tests, specify the value as P95.
Part of the search expression. You can specify the name and value \n (domain, task, framework, framework version, task, and model).
" + "smithy.api#documentation": "Part of the search expression. You can specify the name and value (domain, task, framework, framework version, task, and model).
" } }, "com.amazonaws.sagemaker#ModelMetadataFilterType": { @@ -49233,7 +49228,7 @@ } }, "traits": { - "smithy.api#documentation": "One or more filters that searches for the specified resource or resources in \n a search. All resource objects that satisfy the expression's condition are \n included in the search results
" + "smithy.api#documentation": "One or more filters that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results
" } }, "com.amazonaws.sagemaker#ModelMetadataSummaries": { @@ -49348,7 +49343,7 @@ "ModelPackageName": { "target": "com.amazonaws.sagemaker#EntityName", "traits": { - "smithy.api#documentation": "The name of the model package. The name can be as follows:
\nFor a versioned model, the name is automatically generated by SageMaker Model Registry and\n follows the format\n 'ModelPackageGroupName/ModelPackageVersion'.
For an unversioned model, you must provide the name.
\nThe name of the model package. The name can be as follows:
For a versioned model, the name is automatically generated by SageMaker Model Registry and follows the format 'ModelPackageGroupName/ModelPackageVersion'.
For an unversioned model, you must provide the name.
Specifies batch transform jobs that SageMaker runs to validate your model\n package.
" + "smithy.api#documentation": "Specifies batch transform jobs that SageMaker runs to validate your model package.
" } }, "ModelPackageStatus": { "target": "com.amazonaws.sagemaker#ModelPackageStatus", "traits": { - "smithy.api#documentation": "The status of the model package. This can be one of the following values.
\n\n PENDING - The model package is pending being created.
\n IN_PROGRESS - The model package is in the process of being\n created.
\n COMPLETED - The model package was successfully created.
\n FAILED - The model package failed.
\n DELETING - The model package is in the process of being\n deleted.
The status of the model package. This can be one of the following values.
PENDING - The model package is pending being created.
IN_PROGRESS - The model package is in the process of being created.
COMPLETED - The model package was successfully created.
FAILED - The model package failed.
DELETING - The model package is in the process of being deleted.
Whether the model package is to be certified to be listed on Amazon Web Services\n Marketplace. For information about listing model packages on Amazon Web Services\n Marketplace, see List Your Algorithm or Model\n Package on Amazon Web Services Marketplace.
" + "smithy.api#documentation": "Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.
" } }, "ModelApprovalStatus": { "target": "com.amazonaws.sagemaker#ModelApprovalStatus", "traits": { - "smithy.api#documentation": "The approval status of the model. This can be one of the following values.
\n\n APPROVED - The model is approved
\n REJECTED - The model is rejected.
\n PENDING_MANUAL_APPROVAL - The model is waiting for manual\n approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
Information about the user who created or modified an experiment, trial, trial\n component, lineage group, or project.
" + "smithy.api#documentation": "Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
" } }, "MetadataProperties": { @@ -49450,7 +49445,7 @@ "LastModifiedBy": { "target": "com.amazonaws.sagemaker#UserContext", "traits": { - "smithy.api#documentation": "Information about the user who created or modified an experiment, trial, trial\n component, lineage group, or project.
" + "smithy.api#documentation": "Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.
" } }, "ApprovalDescription": { @@ -49462,19 +49457,19 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of your model package and its components. Common machine\n learning domains include computer vision and natural language processing.
" + "smithy.api#documentation": "The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
" } }, "Task": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine learning\n tasks include object detection and image classification.
" + "smithy.api#documentation": "The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
" } }, "SamplePayloadUrl": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a\n single gzip compressed tar archive (.tar.gz suffix).
" + "smithy.api#documentation": "The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
" } }, "AdditionalInferenceSpecifications": { @@ -49504,7 +49499,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
" + "smithy.api#documentation": "A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } }, "CustomerMetadataProperties": { @@ -49516,7 +49511,7 @@ "DriftCheckBaselines": { "target": "com.amazonaws.sagemaker#DriftCheckBaselines", "traits": { - "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set\n using the model package.
" + "smithy.api#documentation": "Represents the drift check baselines that can be used when the model monitor is set using the model package.
" } }, "SkipModelValidation": { @@ -49527,7 +49522,7 @@ } }, "traits": { - "smithy.api#documentation": "A container for your trained model that can be deployed for SageMaker inference. This can\n include inference code, artifacts, and metadata. The model package type can be one of\n the following.
\nVersioned model: A part of a model package group in Model Registry.
\nUnversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
\nFor more information, see \n CreateModelPackage\n .
A container for your trained model that can be deployed for SageMaker inference. This can include inference code, artifacts, and metadata. The model package type can be one of the following.
Versioned model: A part of a model package group in Model Registry.
Unversioned model: Not part of a model package group and used in Amazon Web Services Marketplace.
For more information, see CreateModelPackage .
The Amazon Elastic Container Registry (Amazon ECR) path where inference code is stored.
\nIf you are using your own custom algorithm instead of an algorithm provided by SageMaker,\n the inference code must meet SageMaker requirements. SageMaker supports both\n registry/repository[:tag] and registry/repository[@digest]\n image path formats. For more information, see Using Your Own Algorithms with Amazon\n SageMaker.
The Amazon Elastic Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.
An MD5 hash of the training algorithm that identifies the Docker image used for\n training.
" + "smithy.api#documentation": "An MD5 hash of the training algorithm that identifies the Docker image used for training.
" } }, "ModelDataUrl": { "target": "com.amazonaws.sagemaker#Url", "traits": { - "smithy.api#documentation": "The Amazon S3 path where the model artifacts, which result from model training, are stored.\n This path must point to a single gzip compressed tar archive\n (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the\n model package.
\nThe Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same region as the model package.
The environment variables to set in the Docker container. Each key and value in the\n Environment string to string map can have length of up to 1024. We\n support up to 16 entries in the map.
The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.
The name of a pre-trained machine learning benchmarked by \n Amazon SageMaker Inference Recommender model that matches your model. \n You can find a list of benchmarked models by calling ListModelMetadata.
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
The additional data source that is used during inference in the Docker container for\n your model package.
" + "smithy.api#documentation": "The additional data source that is used during inference in the Docker container for your model package.
" } }, "ModelDataETag": { @@ -49695,13 +49690,13 @@ "ModelPackageGroupStatus": { "target": "com.amazonaws.sagemaker#ModelPackageGroupStatus", "traits": { - "smithy.api#documentation": "The status of the model group. This can be one of the following values.
\n\n PENDING - The model group is pending being created.
\n IN_PROGRESS - The model group is in the process of being\n created.
\n COMPLETED - The model group was successfully created.
\n FAILED - The model group failed.
\n DELETING - The model group is in the process of being\n deleted.
\n DELETE_FAILED - SageMaker failed to delete the model group.
The status of the model group. This can be one of the following values.
PENDING - The model group is pending being created.
IN_PROGRESS - The model group is in the process of being created.
COMPLETED - The model group was successfully created.
FAILED - The model group failed.
DELETING - The model group is in the process of being deleted.
DELETE_FAILED - SageMaker failed to delete the model group.
A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
" + "smithy.api#documentation": "A list of the tags associated with the model group. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } } }, @@ -49835,18 +49830,18 @@ "ModelCardContent": { "target": "com.amazonaws.sagemaker#ModelCardContent", "traits": { - "smithy.api#documentation": "The content of the model card. The content must follow the schema described in Model\n Package Model Card Schema.
" + "smithy.api#documentation": "The content of the model card. The content must follow the schema described in Model Package Model Card Schema.
" } }, "ModelCardStatus": { "target": "com.amazonaws.sagemaker#ModelCardStatus", "traits": { - "smithy.api#documentation": "The approval status of the model card within your organization. Different\n organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates can be made\n to the model card content. If you try to update the model card content, you will\n receive the message Model Card is in Archived state.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates can be made to the model card content. If you try to update the model card content, you will receive the message Model Card is in Archived state.
The model card associated with the model package. Since\n ModelPackageModelCard is tied to a model package, it is a specific\n usage of a model card and its schema is simplified compared to the schema of\n ModelCard. The ModelPackageModelCard schema does not\n include model_package_details, and model_overview is composed\n of the model_creator and model_artifact properties. For more\n information about the model package model card schema, see Model\n package model card schema. For more information about the model card\n associated with the model package, see View the Details of a Model\n Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
The KMS Key ID (KMSKeyId) used for encryption of model\n package information.
The KMS Key ID (KMSKeyId) used for encryption of model package information.
An optional Key Management Service key to encrypt, decrypt, and re-encrypt model\n package information for regulated workloads with highly sensitive data.
" + "smithy.api#documentation": "An optional Key Management Service key to encrypt, decrypt, and re-encrypt model package information for regulated workloads with highly sensitive data.
" } }, "com.amazonaws.sagemaker#ModelPackageSortBy": { @@ -50006,7 +50001,7 @@ "ModelPackageGroupName": { "target": "com.amazonaws.sagemaker#EntityName", "traits": { - "smithy.api#documentation": "If the model package is a versioned model, the model group that the versioned model\n belongs to.
" + "smithy.api#documentation": "If the model package is a versioned model, the model group that the versioned model belongs to.
" } }, "ModelPackageVersion": { @@ -50048,7 +50043,7 @@ "ModelApprovalStatus": { "target": "com.amazonaws.sagemaker#ModelApprovalStatus", "traits": { - "smithy.api#documentation": "The approval status of the model. This can be one of the following values.
\n\n APPROVED - The model is approved
\n REJECTED - The model is rejected.
\n PENDING_MANUAL_APPROVAL - The model is waiting for manual\n approval.
The approval status of the model. This can be one of the following values.
APPROVED - The model is approved
REJECTED - The model is rejected.
PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
The TransformJobDefinition object that describes the transform job used\n for the validation of the model package.
The TransformJobDefinition object that describes the transform job used for the validation of the model package.
Contains data, such as the inputs and targeted instance types that are used in the\n process of validating the model package.
\nThe data provided in the validation profile is made available to your buyers on\n Amazon Web Services Marketplace.
" + "smithy.api#documentation": "Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.
" } }, "com.amazonaws.sagemaker#ModelPackageValidationProfiles": { @@ -50139,7 +50134,7 @@ "target": "com.amazonaws.sagemaker#ModelPackageValidationProfiles", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of ModelPackageValidationProfile objects, each of which\n specifies a batch transform job that SageMaker runs to validate your model package.
An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
" } }, "ProblemType": { @@ -50242,7 +50237,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
" } }, "com.amazonaws.sagemaker#ModelQualityJobInput": { @@ -50267,7 +50262,7 @@ } }, "traits": { - "smithy.api#documentation": "The input for the model quality monitoring job. Currently endpoints are supported for\n input for model quality monitoring jobs.
" + "smithy.api#documentation": "The input for the model quality monitoring job. Currently endpoints are supported for input for model quality monitoring jobs.
" } }, "com.amazonaws.sagemaker#ModelQuantizationConfig": { @@ -50296,13 +50291,13 @@ "Status": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "Describes whether the integration to the model registry is enabled or disabled in the\n Canvas application.
" + "smithy.api#documentation": "Describes whether the integration to the model registry is enabled or disabled in the Canvas application.
" } }, "CrossAccountModelRegisterRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions\n created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services\n account in which SageMaker model registry is set up.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the SageMaker model registry account. Required only to register model versions created by a different SageMaker Canvas Amazon Web Services account than the Amazon Web Services account in which SageMaker model registry is set up.
" } } }, @@ -50520,7 +50515,7 @@ "target": "com.amazonaws.sagemaker#ModelVariantStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The status of deployment for the model variant on the hosted inference endpoint.
\n\n Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.\n
\n InService - The model variant is running on the hosted inference endpoint.\n
\n Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.\n
\n Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.\n
\n Deleted - The model variant has been deleted on the hosted inference endpoint. This\n can only happen after stopping the experiment.\n
The status of deployment for the model variant on the hosted inference endpoint.
Creating - Amazon SageMaker is preparing the model variant on the hosted inference endpoint.
InService - The model variant is running on the hosted inference endpoint.
Updating - Amazon SageMaker is updating the model variant on the hosted inference endpoint.
Deleting - Amazon SageMaker is deleting the model variant on the hosted inference endpoint.
Deleted - The model variant has been deleted on the hosted inference endpoint. This can only happen after stopping the experiment.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into\n InAlert status.
An alert action taken to light up an icon on the Model Dashboard when an alert goes into InAlert status.
A list of alert actions taken in response to an alert going into\n InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
A timestamp that indicates when the first alert transition occurred in an alert history.\n An alert transition can be from status InAlert to OK, \n or from OK to InAlert.
A timestamp that indicates when the first alert transition occurred in an alert history. An alert transition can be from status InAlert to OK, or from OK to InAlert.
Within EvaluationPeriod, how many execution failures will raise an\n alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
The number of most recent monitoring executions to consider when evaluating alert\n status.
", + "smithy.api#documentation": "The number of most recent monitoring executions to consider when evaluating alert status.
", "smithy.api#required": {} } }, @@ -50739,7 +50734,7 @@ "target": "com.amazonaws.sagemaker#MonitoringAlertActions", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of alert actions taken in response to an alert going into\n InAlert status.
A list of alert actions taken in response to an alert going into InAlert status.
An Amazon S3 URI to a script that is called per row prior to running analysis. It can \n base64 decode the payload and convert it into a flattened JSON so that the built-in container can use \n the converted data. Applicable only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flattened JSON so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers.
" } }, "PostAnalyticsProcessorSourceUri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable \n only for the built-in (first party) containers.
" + "smithy.api#documentation": "An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
" } } }, @@ -50812,18 +50807,18 @@ "ConstraintsResource": { "target": "com.amazonaws.sagemaker#MonitoringConstraintsResource", "traits": { - "smithy.api#documentation": "The baseline constraint file in Amazon S3 that the current monitoring job should\n validated against.
" + "smithy.api#documentation": "The baseline constraint file in Amazon S3 that the current monitoring job should validated against.
" } }, "StatisticsResource": { "target": "com.amazonaws.sagemaker#MonitoringStatisticsResource", "traits": { - "smithy.api#documentation": "The baseline statistics file in Amazon S3 that the current monitoring job should\n be validated against.
" + "smithy.api#documentation": "The baseline statistics file in Amazon S3 that the current monitoring job should be validated against.
" } } }, "traits": { - "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are \n compared against the results of the current job from the series of jobs scheduled to collect data \n periodically.
" + "smithy.api#documentation": "Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
" } }, "com.amazonaws.sagemaker#MonitoringClusterConfig": { @@ -50833,7 +50828,7 @@ "target": "com.amazonaws.sagemaker#ProcessingInstanceCount", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of ML compute instances to use in the model monitoring job. For distributed\n processing jobs, specify a value greater than 1. The default value is 1.
", + "smithy.api#documentation": "The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
", "smithy.api#required": {} } }, @@ -50849,14 +50844,14 @@ "target": "com.amazonaws.sagemaker#ProcessingVolumeSizeInGB", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The size of the ML storage volume, in gigabytes, that you want to provision. You must\n specify sufficient ML storage for your scenario.
", + "smithy.api#documentation": "The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
", "smithy.api#required": {} } }, "VolumeKmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker AI uses to\n encrypt data on the storage volume attached to the ML compute instance(s) that run the\n model monitoring job.
" + "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
" } } }, @@ -51122,7 +51117,7 @@ "BaselineConfig": { "target": "com.amazonaws.sagemaker#MonitoringBaselineConfig", "traits": { - "smithy.api#documentation": "Baseline configuration used to validate that the data conforms to the specified\n constraints and statistics
" + "smithy.api#documentation": "Baseline configuration used to validate that the data conforms to the specified constraints and statistics
" } }, "MonitoringInputs": { @@ -51145,7 +51140,7 @@ "target": "com.amazonaws.sagemaker#MonitoringResources", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a\n monitoring job. In distributed processing, you specify more than one instance.
", + "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a monitoring job. In distributed processing, you specify more than one instance.
", "smithy.api#required": {} } }, @@ -51179,7 +51174,7 @@ "target": "com.amazonaws.sagemaker#RoleArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can \n assume to perform tasks on your behalf.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.
", "smithy.api#required": {} } } @@ -51300,13 +51295,13 @@ "EnableInterContainerTrafficEncryption": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Whether to encrypt all communications between the instances used for the monitoring\n jobs. Choose True to encrypt communications. Encryption provides greater\n security for distributed jobs, but the processing might take longer.
Whether to encrypt all communications between the instances used for the monitoring jobs. Choose True to encrypt communications. Encryption provides greater security for distributed jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for\n the monitoring job.
" + "smithy.api#documentation": "Whether to allow inbound and outbound network calls to and from the containers used for the monitoring job.
" } }, "VpcConfig": { @@ -51324,7 +51319,7 @@ "target": "com.amazonaws.sagemaker#MonitoringS3Output", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon S3 storage location where the results of a monitoring job are\n saved.
", + "smithy.api#documentation": "The Amazon S3 storage location where the results of a monitoring job are saved.
", "smithy.api#required": {} } } @@ -51340,14 +51335,14 @@ "target": "com.amazonaws.sagemaker#MonitoringOutputs", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Monitoring outputs for monitoring jobs. This is where the output of the periodic\n monitoring jobs is uploaded.
", + "smithy.api#documentation": "Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
", "smithy.api#required": {} } }, "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker AI uses to\n encrypt the model artifacts at rest using Amazon S3 server-side encryption.
" + "smithy.api#documentation": "The Key Management Service (KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
" } } }, @@ -51420,7 +51415,7 @@ "target": "com.amazonaws.sagemaker#MonitoringS3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI\n saves the results of a monitoring job.
", + "smithy.api#documentation": "A URI that identifies the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job.
", "smithy.api#required": {} } }, @@ -51428,19 +51423,19 @@ "target": "com.amazonaws.sagemaker#ProcessingLocalPath", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The local path to the Amazon S3 storage location where Amazon SageMaker AI\n saves the results of a monitoring job. LocalPath is an absolute path for the output\n data.
", + "smithy.api#documentation": "The local path to the Amazon S3 storage location where Amazon SageMaker AI saves the results of a monitoring job. LocalPath is an absolute path for the output data.
", "smithy.api#required": {} } }, "S3UploadMode": { "target": "com.amazonaws.sagemaker#ProcessingS3UploadMode", "traits": { - "smithy.api#documentation": "Whether to upload the results of the monitoring job continuously or after the job\n completes.
" + "smithy.api#documentation": "Whether to upload the results of the monitoring job continuously or after the job completes.
" } } }, "traits": { - "smithy.api#documentation": "Information about where and how you want to store the results of a monitoring\n job.
" + "smithy.api#documentation": "Information about where and how you want to store the results of a monitoring job.
" } }, "com.amazonaws.sagemaker#MonitoringS3Uri": { @@ -51471,7 +51466,7 @@ "MonitoringScheduleStatus": { "target": "com.amazonaws.sagemaker#ScheduleStatus", "traits": { - "smithy.api#documentation": "The status of the monitoring schedule. This can be one of the following values.
\n\n PENDING - The schedule is pending being created.
\n FAILED - The schedule failed.
\n SCHEDULED - The schedule was successfully created.
\n STOPPED - The schedule was stopped.
The status of the monitoring schedule. This can be one of the following values.
PENDING - The schedule is pending being created.
FAILED - The schedule failed.
SCHEDULED - The schedule was successfully created.
STOPPED - The schedule was stopped.
A list of the tags associated with the monitoring schedlue. For more information, see\n Tagging Amazon Web Services resources in the Amazon Web Services General\n Reference Guide.
" + "smithy.api#documentation": "A list of the tags associated with the monitoring schedlue. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
" } } }, "traits": { - "smithy.api#documentation": "A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model\n Monitor.
" + "smithy.api#documentation": "A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
" } }, "com.amazonaws.sagemaker#MonitoringScheduleArn": { @@ -51695,7 +51690,7 @@ "target": "com.amazonaws.sagemaker#MonitoringMaxRuntimeInSeconds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The maximum runtime allowed in seconds.
\nThe MaxRuntimeInSeconds cannot exceed the frequency of the job. For data\n quality and model explainability, this can be up to 3600 seconds for an hourly schedule.\n For model bias and model quality hourly schedules, this can be up to 1800\n seconds.
The maximum runtime allowed in seconds.
The MaxRuntimeInSeconds cannot exceed the frequency of the job. For data quality and model explainability, this can be up to 3600 seconds for an hourly schedule. For model bias and model quality hourly schedules, this can be up to 1800 seconds.
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints\n cache models so that a model does not have to be loaded into memory each time it is\n invoked. Some use cases do not benefit from model caching. For example, if an endpoint\n hosts a large number of models that are each invoked infrequently, the endpoint might\n perform better if you disable model caching. To disable model caching, set the value of\n this parameter to Disabled.
Whether to cache models for a multi-model endpoint. By default, multi-model endpoints cache models so that a model does not have to be loaded into memory each time it is invoked. Some use cases do not benefit from model caching. For example, if an endpoint hosts a large number of models that are each invoked infrequently, the endpoint might perform better if you disable model caching. To disable model caching, set the value of this parameter to Disabled.
The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the\n security groups for the VPC that is specified in the Subnets field.
The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC that you want to connect the compilation job to for\n accessing the model in Amazon S3.
", + "smithy.api#documentation": "The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the model in Amazon S3.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The VpcConfig configuration object that specifies the VPC that you want the\n compilation jobs to connect to. For more information on controlling access to your Amazon S3\n buckets used for compilation job, see Give Amazon SageMaker AI Compilation Jobs Access to\n Resources in Your Amazon VPC.
" + "smithy.api#documentation": "The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker AI Compilation Jobs Access to Resources in Your Amazon VPC.
" } }, "com.amazonaws.sagemaker#NeoVpcSecurityGroupId": { @@ -51852,7 +51847,7 @@ "target": "com.amazonaws.sagemaker#ResourcePropertyName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the property to use in the nested filters. The value must match a listed\n property name, such as InputDataConfig.
The name of the property to use in the nested filters. The value must match a listed property name, such as InputDataConfig.
A list of filters. Each filter acts on a property. Filters must contain at least one\n Filters value. For example, a NestedFilters call might include a\n filter on the PropertyName parameter of the InputDataConfig\n property: InputDataConfig.DataSource.S3DataSource.S3Uri.
A list of filters. Each filter acts on a property. Filters must contain at least one Filters value. For example, a NestedFilters call might include a filter on the PropertyName parameter of the InputDataConfig property: InputDataConfig.DataSource.S3DataSource.S3Uri.
A list of nested Filter objects. A resource must\n satisfy the conditions of all filters to be included in the results returned from the Search\n API.
\nFor example, to filter on a training job's InputDataConfig property with a\n specific channel name and S3Uri prefix, define the following filters:
\n '{Name:\"InputDataConfig.ChannelName\", \"Operator\":\"Equals\", \"Value\":\"train\"}',\n
\n '{Name:\"InputDataConfig.DataSource.S3DataSource.S3Uri\", \"Operator\":\"Contains\",\n \"Value\":\"mybucket/catdata\"}'\n
A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
For example, to filter on a training job's InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:
'{Name:\"InputDataConfig.ChannelName\", \"Operator\":\"Equals\", \"Value\":\"train\"}',
'{Name:\"InputDataConfig.DataSource.S3DataSource.S3Uri\", \"Operator\":\"Contains\", \"Value\":\"mybucket/catdata\"}'
Whether to encrypt all communications between distributed processing jobs. Choose\n True to encrypt communications. Encryption provides greater security\n for distributed processing jobs, but the processing might take longer.
Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
Whether to allow inbound and outbound network calls to and from the containers used for\n the processing job.
" + "smithy.api#documentation": "Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
" } }, "VpcConfig": { @@ -51901,7 +51896,7 @@ } }, "traits": { - "smithy.api#documentation": "Networking options for a job, such as network traffic encryption between containers,\n whether to allow inbound and outbound network calls to and from containers, and the VPC\n subnets and security groups to use for VPC-enabled jobs.
" + "smithy.api#documentation": "Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
" } }, "com.amazonaws.sagemaker#NetworkInterfaceId": { @@ -52157,12 +52152,12 @@ "Content": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigContent", "traits": { - "smithy.api#documentation": "A base64-encoded string that contains a shell script for a notebook instance lifecycle\n configuration.
" + "smithy.api#documentation": "A base64-encoded string that contains a shell script for a notebook instance lifecycle configuration.
" } } }, "traits": { - "smithy.api#documentation": "Contains the notebook instance lifecycle configuration script.
\nEach lifecycle configuration script has a limit of 16384 characters.
\nThe value of the $PATH environment variable that is available to both\n scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log\n group /aws/sagemaker/NotebookInstances in log stream\n [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs\n for longer than 5 minutes, it fails and the notebook instance is not created or\n started.
\nFor information about notebook instance lifestyle configurations, see Step\n 2.1: (Optional) Customize a Notebook Instance.
" + "smithy.api#documentation": "Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
View Amazon CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "com.amazonaws.sagemaker#NotebookInstanceName": { @@ -52300,7 +52295,7 @@ "Url": { "target": "com.amazonaws.sagemaker#NotebookInstanceUrl", "traits": { - "smithy.api#documentation": "The URL that you use to connect to the Jupyter notebook running in your notebook\n instance.
" + "smithy.api#documentation": "The URL that you use to connect to the Jupyter notebook running in your notebook instance.
" } }, "InstanceType": { @@ -52324,19 +52319,19 @@ "NotebookInstanceLifecycleConfigName": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigName", "traits": { - "smithy.api#documentation": "The name of a notebook instance lifecycle configuration associated with this notebook\n instance.
\nFor information about notebook instance lifestyle configurations, see Step\n 2.1: (Optional) Customize a Notebook Instance.
" + "smithy.api#documentation": "The name of a notebook instance lifecycle configuration associated with this notebook instance.
For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "DefaultCodeRepository": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameOrUrl", "traits": { - "smithy.api#documentation": "The Git repository associated with the notebook instance as its default code\n repository. This can be either the name of a Git repository stored as a resource in your\n account, or the URL of a Git repository in Amazon Web Services CodeCommit\n or in any other Git repository. When you open a notebook instance, it opens in the\n directory that contains this repository. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "AdditionalCodeRepositories": { "target": "com.amazonaws.sagemaker#AdditionalCodeRepositoryNamesOrUrls", "traits": { - "smithy.api#documentation": "An array of up to three Git repositories associated with the notebook instance. These\n can be either the names of Git repositories stored as resources in your account, or the\n URL of Git repositories in Amazon Web Services CodeCommit\n or in any other Git repository. These repositories are cloned at the same level as the\n default repository of your notebook instance. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } } }, @@ -52390,7 +52385,7 @@ } }, "traits": { - "smithy.api#documentation": "Configures Amazon SNS notifications of available or expiring work items for work\n teams.
" + "smithy.api#documentation": "Configures Amazon SNS notifications of available or expiring work items for work teams.
" } }, "com.amazonaws.sagemaker#NotificationTopicArn": { @@ -52469,24 +52464,24 @@ "Succeeded": { "target": "com.amazonaws.sagemaker#ObjectiveStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs whose final objective metric was evaluated by the\n hyperparameter tuning job and used in the hyperparameter tuning process.
" + "smithy.api#documentation": "The number of training jobs whose final objective metric was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
" } }, "Pending": { "target": "com.amazonaws.sagemaker#ObjectiveStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs that are in progress and pending evaluation of their final\n objective metric.
" + "smithy.api#documentation": "The number of training jobs that are in progress and pending evaluation of their final objective metric.
" } }, "Failed": { "target": "com.amazonaws.sagemaker#ObjectiveStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs whose final objective metric was not evaluated and used in\n the hyperparameter tuning process. This typically occurs when the training job failed or\n did not emit an objective metric.
" + "smithy.api#documentation": "The number of training jobs whose final objective metric was not evaluated and used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
" } } }, "traits": { - "smithy.api#documentation": "Specifies the number of training jobs that this hyperparameter tuning job launched,\n categorized by the status of their objective metric. The objective metric status shows\n whether the\n final\n objective metric for the training job has been evaluated by the\n tuning job and used in the hyperparameter tuning process.
" + "smithy.api#documentation": "Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
" } }, "com.amazonaws.sagemaker#OfflineStoreConfig": { @@ -52503,13 +52498,13 @@ "DisableGlueTableCreation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Set to True to disable the automatic creation of an Amazon Web Services Glue\n table when configuring an OfflineStore. If set to False, Feature\n Store will name the OfflineStore Glue table following Athena's\n naming recommendations.
The default value is False.
Set to True to disable the automatic creation of an Amazon Web Services Glue table when configuring an OfflineStore. If set to False, Feature Store will name the OfflineStore Glue table following Athena's naming recommendations.
The default value is False.
The meta data of the Glue table that is autogenerated when an OfflineStore\n is created.
The meta data of the Glue table that is autogenerated when an OfflineStore is created.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to\n CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in\n S3StorageConfig.
The configuration of an OfflineStore.
Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore.
To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
A list of comma seperated strings that identifies\n user groups in your OIDC IdP. Each user group is\n made up of a group of private workers.
" + "smithy.api#documentation": "A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.
" } } }, "traits": { - "smithy.api#documentation": "A list of user groups that exist in your OIDC Identity Provider (IdP). \n One to ten groups can be used to create a single private work team. \n When you add a user group to the list of Groups, you can add that user group to one or more\n private work teams. If you add a user group to a private work team, all workers in that user group \n are added to the work team.
A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your\n OnlineStore.
Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your OnlineStore.
Turn OnlineStore off by specifying False for the\n EnableOnlineStore flag. Turn OnlineStore on by specifying\n True for the EnableOnlineStore flag.
The default value is False.
Turn OnlineStore off by specifying False for the EnableOnlineStore flag. Turn OnlineStore on by specifying True for the EnableOnlineStore flag.
The default value is False.
Time to live duration, where the record is hard deleted after the expiration time is\n reached; ExpiresAt = EventTime + TtlDuration. For\n information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Option for different tiers of low latency storage for real-time data retrieval.
\n\n Standard: A managed low latency data store for feature groups.
\n InMemory: A managed data store for feature groups that supports very\n low latency retrieval.
Option for different tiers of low latency storage for real-time data retrieval.
Standard: A managed low latency data store for feature groups.
InMemory: A managed data store for feature groups that supports very low latency retrieval.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or\n KMSKeyId, for at rest data encryption. You can turn\n OnlineStore on or off by specifying the EnableOnlineStore flag\n at General Assembly.
The default value is False.
Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly.
The default value is False.
Time to live duration, where the record is hard deleted after the expiration time is\n reached; ExpiresAt = EventTime + TtlDuration. For\n information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store\n uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side\n encryption.
\nThe caller (either user or IAM role) of CreateFeatureGroup must have below\n permissions to the OnlineStore\n KmsKeyId:
\n \"kms:Encrypt\"\n
\n \"kms:Decrypt\"\n
\n \"kms:DescribeKey\"\n
\n \"kms:CreateGrant\"\n
\n \"kms:RetireGrant\"\n
\n \"kms:ReEncryptFrom\"\n
\n \"kms:ReEncryptTo\"\n
\n \"kms:GenerateDataKey\"\n
\n \"kms:ListAliases\"\n
\n \"kms:ListGrants\"\n
\n \"kms:RevokeGrant\"\n
The caller (either user or IAM role) to all DataPlane operations\n (PutRecord, GetRecord, DeleteRecord) must have the\n following permissions to the KmsKeyId:
\n \"kms:Decrypt\"\n
The Amazon Web Services Key Management Service (KMS) key ARN that SageMaker Feature Store uses to encrypt the Amazon S3 objects at rest using Amazon S3 server-side encryption.
The caller (either user or IAM role) of CreateFeatureGroup must have below permissions to the OnlineStore KmsKeyId:
\"kms:Encrypt\"
\"kms:Decrypt\"
\"kms:DescribeKey\"
\"kms:CreateGrant\"
\"kms:RetireGrant\"
\"kms:ReEncryptFrom\"
\"kms:ReEncryptTo\"
\"kms:GenerateDataKey\"
\"kms:ListAliases\"
\"kms:ListGrants\"
\"kms:RevokeGrant\"
The caller (either user or IAM role) to all DataPlane operations (PutRecord, GetRecord, DeleteRecord) must have the following permissions to the KmsKeyId:
\"kms:Decrypt\"
Settings for an optimization technique that you apply with a model optimization\n job.
" + "smithy.api#documentation": "Settings for an optimization technique that you apply with a model optimization job.
" } }, "com.amazonaws.sagemaker#OptimizationConfigs": { @@ -53200,14 +53195,14 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of a key in Amazon Web Services KMS. SageMaker uses they key to encrypt the artifacts of the\n optimized model when SageMaker uploads the model to Amazon S3.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of a key in Amazon Web Services KMS. SageMaker uses they key to encrypt the artifacts of the optimized model when SageMaker uploads the model to Amazon S3.
" } }, "S3OutputLocation": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon S3 URI for where to store the optimized model that you create with an optimization\n job.
", + "smithy.api#documentation": "The Amazon S3 URI for where to store the optimized model that you create with an optimization job.
", "smithy.api#required": {} } } @@ -53347,7 +53342,7 @@ "target": "com.amazonaws.sagemaker#OptimizationModelAcceptEula", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies agreement to the model end-user license agreement (EULA). The\n AcceptEula value must be explicitly defined as True in order\n to accept the EULA that this model requires. You are responsible for reviewing and\n complying with any applicable license terms and making sure they are acceptable for your\n use case before downloading or using a model.
Specifies agreement to the model end-user license agreement (EULA). The AcceptEula value must be explicitly defined as True in order to accept the EULA that this model requires. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The image that SageMaker recommends that you use to host the optimized model that you created\n with an optimization job.
" + "smithy.api#documentation": "The image that SageMaker recommends that you use to host the optimized model that you created with an optimization job.
" } } }, @@ -53386,7 +53381,7 @@ "target": "com.amazonaws.sagemaker#OptimizationVpcSecurityGroupIds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security\n groups for the VPC that is specified in the Subnets field.
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your optimized\n model.
", + "smithy.api#documentation": "The ID of the subnets in the VPC to which you want to connect your optimized model.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "A VPC in Amazon VPC that's accessible to an optimized that you create with an optimization\n job. You can control access to and from your resources by configuring a VPC. For more\n information, see Give SageMaker Access to Resources in your Amazon VPC.
" + "smithy.api#documentation": "A VPC in Amazon VPC that's accessible to an optimized that you create with an optimization job. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
" } }, "com.amazonaws.sagemaker#OptimizationVpcSecurityGroupId": { @@ -53502,37 +53497,37 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For\n example, s3://bucket-name/key-name-prefix.
Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
Identifies the target device or the machine learning instance that you want to run\n your model on after the compilation has completed. Alternatively, you can specify OS,\n architecture, and accelerator using TargetPlatform\n fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region,\n and ml_inf2 is available only in US East (Ohio) Region.
Identifies the target device or the machine learning instance that you want to run your model on after the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform fields. It can be used instead of TargetPlatform.
Currently ml_trn1 is available only in US East (N. Virginia) Region, and ml_inf2 is available only in US East (Ohio) Region.
Contains information about a target platform that you want your model to run on, such\n as OS, architecture, and accelerators. It is an alternative of\n TargetDevice.
The following examples show how to configure the TargetPlatform and\n CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
\n\n \"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM_EABIHF\"},\n
\n \"CompilerOptions\": {'mattr': ['+neon']}\n
Jetson TX2
\n\n \"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\":\n \"NVIDIA\"},\n
\n \"CompilerOptions\": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1',\n 'cuda-ver': '10.0'}\n
EC2 m5.2xlarge instance OS
\n\n \"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"X86_64\", \"Accelerator\":\n \"NVIDIA\"},\n
\n \"CompilerOptions\": {'mcpu': 'skylake-avx512'}\n
RK3399
\n\n \"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\":\n \"MALI\"}\n
ARMv7 phone (CPU)
\n\n \"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM_EABI\"},\n
\n \"CompilerOptions\": {'ANDROID_PLATFORM': 25, 'mattr':\n ['+neon']}\n
ARMv8 phone (CPU)
\n\n \"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM64\"},\n
\n \"CompilerOptions\": {'ANDROID_PLATFORM': 29}\n
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:
Raspberry Pi 3 Model B+
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM_EABIHF\"},
\"CompilerOptions\": {'mattr': ['+neon']}
Jetson TX2
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\": \"NVIDIA\"},
\"CompilerOptions\": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}
EC2 m5.2xlarge instance OS
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"X86_64\", \"Accelerator\": \"NVIDIA\"},
\"CompilerOptions\": {'mcpu': 'skylake-avx512'}
RK3399
\"TargetPlatform\": {\"Os\": \"LINUX\", \"Arch\": \"ARM64\", \"Accelerator\": \"MALI\"}
ARMv7 phone (CPU)
\"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM_EABI\"},
\"CompilerOptions\": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}
ARMv8 phone (CPU)
\"TargetPlatform\": {\"Os\": \"ANDROID\", \"Arch\": \"ARM64\"},
\"CompilerOptions\": {'ANDROID_PLATFORM': 29}
Specifies additional parameters for compiler options in JSON format. The compiler\n options are TargetPlatform specific. It is required for NVIDIA accelerators\n and highly recommended for CPU compilations. For any other cases, it is optional to\n specify CompilerOptions.\n
\n DTYPE: Specifies the data type for the input. When compiling for\n ml_* (except for ml_inf) instances using PyTorch\n framework, provide the data type (dtype) of the model's input.\n \"float32\" is used if \"DTYPE\" is not specified.\n Options for data type are:
float32: Use either \"float\" or\n \"float32\".
int64: Use either \"int64\" or \"long\".
For example, {\"dtype\" : \"float32\"}.
\n CPU: Compilation for CPU supports the following compiler\n options.
\n mcpu: CPU micro-architecture. For example, {'mcpu':\n 'skylake-avx512'}\n
\n mattr: CPU flags. For example, {'mattr': ['+neon',\n '+vfpv4']}\n
\n ARM: Details of ARM CPU compilations.
\n NEON: NEON is an implementation of the Advanced SIMD\n extension used in ARMv7 processors.
For example, add {'mattr': ['+neon']} to the compiler\n options if compiling for ARM 32-bit platform with the NEON\n support.
\n NVIDIA: Compilation for NVIDIA GPU supports the following\n compiler options.
\n gpu_code: Specifies the targeted architecture.
\n trt-ver: Specifies the TensorRT versions in x.y.z.\n format.
\n cuda-ver: Specifies the CUDA version in x.y\n format.
For example, {'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver':\n '10.1'}\n
\n ANDROID: Compilation for the Android OS supports the following\n compiler options:
\n ANDROID_PLATFORM: Specifies the Android API levels.\n Available levels range from 21 to 29. For example,\n {'ANDROID_PLATFORM': 28}.
\n mattr: Add {'mattr': ['+neon']} to compiler\n options if compiling for ARM 32-bit platform with NEON support.
\n INFERENTIA: Compilation for target ml_inf1 uses compiler options\n passed in as a JSON string. For example, \"CompilerOptions\": \"\\\"--verbose 1\n --num-neuroncores 2 -O2\\\"\".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
\n\n CoreML: Compilation for the CoreML OutputConfig\n TargetDevice supports the following compiler options:
\n class_labels: Specifies the classification labels file\n name inside input tar.gz file. For example, {\"class_labels\":\n \"imagenet_labels_1000.txt\"}. Labels inside the txt file\n should be separated by newlines.
Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases, it is optional to specify CompilerOptions.
DTYPE: Specifies the data type for the input. When compiling for ml_* (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model's input. \"float32\" is used if \"DTYPE\" is not specified. Options for data type are:
float32: Use either \"float\" or \"float32\".
int64: Use either \"int64\" or \"long\".
For example, {\"dtype\" : \"float32\"}.
CPU: Compilation for CPU supports the following compiler options.
mcpu: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}
mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}
ARM: Details of ARM CPU compilations.
NEON: NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors.
For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.
NVIDIA: Compilation for NVIDIA GPU supports the following compiler options.
gpu_code: Specifies the targeted architecture.
trt-ver: Specifies the TensorRT versions in x.y.z. format.
cuda-ver: Specifies the CUDA version in x.y format.
For example, {'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}
ANDROID: Compilation for the Android OS supports the following compiler options:
ANDROID_PLATFORM: Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28}.
mattr: Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support.
INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a JSON string. For example, \"CompilerOptions\": \"\\\"--verbose 1 --num-neuroncores 2 -O2\\\"\".
For information about supported compiler options, see Neuron Compiler CLI Reference Guide.
CoreML: Compilation for the CoreML OutputConfig TargetDevice supports the following compiler options:
class_labels: Specifies the classification labels file name inside input tar.gz file. For example, {\"class_labels\": \"imagenet_labels_1000.txt\"}. Labels inside the txt file should be separated by newlines.
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker AI\n uses to encrypt your output models with Amazon S3 server-side encryption after compilation\n job. If you don't provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your\n role's account. For more information, see KMS-Managed Encryption\n Keys in the Amazon Simple Storage Service Developer\n Guide.\n
\nThe KmsKeyId can be any of the following formats:
\nKey ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker AI uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don't provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Contains information about the output location for the compiled model and the target\n device that the model runs on. TargetDevice and TargetPlatform\n are mutually exclusive, so you need to choose one between the two to specify your target\n device or platform. If you cannot find your device you want to use from the\n TargetDevice list, use TargetPlatform to describe the\n platform of your edge device and CompilerOptions if there are specific\n settings that are required or recommended to use for particular TargetPlatform.
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker\n uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The\n KmsKeyId can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"\n
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must\n include permissions to call kms:Encrypt. If you don't provide a KMS key ID,\n SageMaker uses the default KMS key for Amazon S3 for your role's account.\n \n For more information, see KMS-Managed Encryption\n Keys in the Amazon Simple Storage Service Developer Guide. If the output\n data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3\n managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your\n CreateTrainingJob, CreateTransformJob, or\n CreateHyperParameterTuningJob requests. For more information, see\n Using\n Key Policies in Amazon Web Services KMS in the Amazon Web Services\n Key Management Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
// Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
// KMS Key Alias
\"alias/ExampleAlias\"
// Amazon Resource Name (ARN) of a KMS Key Alias
\"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. If the output data is stored in Amazon S3 Express One Zone, it is encrypted with server-side encryption with Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon S3 Express One Zone
The KMS key policy must grant permission to the IAM role that you specify in your CreateTrainingJob, CreateTransformJob, or CreateHyperParameterTuningJob requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
Identifies the S3 path where you want SageMaker to store the model artifacts. For\n example, s3://bucket-name/key-name-prefix.
Identifies the S3 path where you want SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix.
The model output compression type. Select None to output an uncompressed\n model, recommended for large model outputs. Defaults to gzip.
The model output compression type. Select None to output an uncompressed model, recommended for large model outputs. Defaults to gzip.
Provides information about how to store model training results (model\n artifacts).
" + "smithy.api#documentation": "Provides information about how to store model training results (model artifacts).
" } }, "com.amazonaws.sagemaker#OutputParameter": { @@ -53652,7 +53647,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration that controls the parallelism of the pipeline. \n By default, the parallelism configuration specified applies to all \n executions of the pipeline unless overridden.
" + "smithy.api#documentation": "Configuration that controls the parallelism of the pipeline. By default, the parallelism configuration specified applies to all executions of the pipeline unless overridden.
" } }, "com.amazonaws.sagemaker#Parameter": { @@ -53662,7 +53657,7 @@ "target": "com.amazonaws.sagemaker#PipelineParameterName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the parameter to assign a value to. This \n parameter name must match a named parameter in the \n pipeline definition.
", + "smithy.api#documentation": "The name of the parameter to assign a value to. This parameter name must match a named parameter in the pipeline definition.
", "smithy.api#required": {} } }, @@ -53717,24 +53712,24 @@ "IntegerParameterRangeSpecification": { "target": "com.amazonaws.sagemaker#IntegerParameterRangeSpecification", "traits": { - "smithy.api#documentation": "A IntegerParameterRangeSpecification object that defines the possible\n values for an integer hyperparameter.
A IntegerParameterRangeSpecification object that defines the possible values for an integer hyperparameter.
A ContinuousParameterRangeSpecification object that defines the possible\n values for a continuous hyperparameter.
A ContinuousParameterRangeSpecification object that defines the possible values for a continuous hyperparameter.
A CategoricalParameterRangeSpecification object that defines the possible\n values for a categorical hyperparameter.
A CategoricalParameterRangeSpecification object that defines the possible values for a categorical hyperparameter.
Defines the possible values for categorical, continuous, and integer hyperparameters\n to be used by an algorithm.
" + "smithy.api#documentation": "Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
" } }, "com.amazonaws.sagemaker#ParameterRanges": { @@ -53743,30 +53738,30 @@ "IntegerParameterRanges": { "target": "com.amazonaws.sagemaker#IntegerParameterRanges", "traits": { - "smithy.api#documentation": "The array of IntegerParameterRange objects that specify ranges of integer\n hyperparameters that a hyperparameter tuning job searches.
" + "smithy.api#documentation": "The array of IntegerParameterRange objects that specify ranges of integer hyperparameters that a hyperparameter tuning job searches.
" } }, "ContinuousParameterRanges": { "target": "com.amazonaws.sagemaker#ContinuousParameterRanges", "traits": { - "smithy.api#documentation": "The array of ContinuousParameterRange objects that specify ranges of continuous\n hyperparameters that a hyperparameter tuning job searches.
" + "smithy.api#documentation": "The array of ContinuousParameterRange objects that specify ranges of continuous hyperparameters that a hyperparameter tuning job searches.
" } }, "CategoricalParameterRanges": { "target": "com.amazonaws.sagemaker#CategoricalParameterRanges", "traits": { - "smithy.api#documentation": "The array of CategoricalParameterRange objects that specify ranges of categorical\n hyperparameters that a hyperparameter tuning job searches.
" + "smithy.api#documentation": "The array of CategoricalParameterRange objects that specify ranges of categorical hyperparameters that a hyperparameter tuning job searches.
" } }, "AutoParameters": { "target": "com.amazonaws.sagemaker#AutoParameters", "traits": { - "smithy.api#documentation": "A list containing hyperparameter names and example values to be used by Autotune to\n determine optimal ranges for your tuning job.
" + "smithy.api#documentation": "A list containing hyperparameter names and example values to be used by Autotune to determine optimal ranges for your tuning job.
" } } }, "traits": { - "smithy.api#documentation": "Specifies ranges of integer, continuous, and categorical hyperparameters that a\n hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs\n with hyperparameter values within these ranges to find the combination of values that\n result in the training job with the best performance as measured by the objective metric\n of the hyperparameter tuning job.
\nThe maximum number of items specified for Array Members refers to the\n maximum number of hyperparameters for each range and also the maximum for the\n hyperparameter tuning job itself. That is, the sum of the number of hyperparameters\n for all the ranges can't exceed the maximum number specified.
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
The maximum number of items specified for Array Members refers to the maximum number of hyperparameters for each range and also the maximum for the hyperparameter tuning job itself. That is, the sum of the number of hyperparameters for all the ranges can't exceed the maximum number specified.
The trial that a trial component is associated with and the experiment the trial is part\n of. A component might not be associated with a trial. A component can be associated with\n multiple trials.
" + "smithy.api#documentation": "The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
" } }, "com.amazonaws.sagemaker#ParentHyperParameterTuningJob": { @@ -53846,12 +53841,12 @@ "HyperParameterTuningJobName": { "target": "com.amazonaws.sagemaker#HyperParameterTuningJobName", "traits": { - "smithy.api#documentation": "The name of the hyperparameter tuning job to be used as a starting point for a new\n hyperparameter tuning job.
" + "smithy.api#documentation": "The name of the hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
" } } }, "traits": { - "smithy.api#documentation": "A previously completed or stopped hyperparameter tuning job to be used as a starting\n point for a new hyperparameter tuning job.
" + "smithy.api#documentation": "A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
" } }, "com.amazonaws.sagemaker#ParentHyperParameterTuningJobs": { @@ -54098,7 +54093,7 @@ "ProductionVariants": { "target": "com.amazonaws.sagemaker#PendingProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "An array of PendingProductionVariantSummary objects, one for each model hosted behind\n this endpoint for the in-progress deployment.
" + "smithy.api#documentation": "An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint for the in-progress deployment.
" } }, "StartTime": { @@ -54110,12 +54105,12 @@ "ShadowProductionVariants": { "target": "com.amazonaws.sagemaker#PendingProductionVariantSummaryList", "traits": { - "smithy.api#documentation": "An array of PendingProductionVariantSummary objects, one for each model hosted behind\n this endpoint in shadow mode with production traffic replicated from the model specified\n on ProductionVariants for the in-progress deployment.
An array of PendingProductionVariantSummary objects, one for each model hosted behind this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants for the in-progress deployment.
The summary of an in-progress deployment when an endpoint is creating or updating with\n a new endpoint configuration.
" + "smithy.api#documentation": "The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.
" } }, "com.amazonaws.sagemaker#PendingProductionVariantSummary": { @@ -54132,7 +54127,7 @@ "DeployedImages": { "target": "com.amazonaws.sagemaker#DeployedImages", "traits": { - "smithy.api#documentation": "An array of DeployedImage objects that specify the Amazon EC2 Container\n Registry paths of the inference images deployed on instances of this\n ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The requested weight for the variant in this deployment, as specified in the endpoint\n configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
" + "smithy.api#documentation": "The requested weight for the variant in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
" } }, "CurrentInstanceCount": { @@ -54156,7 +54151,7 @@ "DesiredInstanceCount": { "target": "com.amazonaws.sagemaker#TaskCount", "traits": { - "smithy.api#documentation": "The number of instances requested in this deployment, as specified in the endpoint\n configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
" + "smithy.api#documentation": "The number of instances requested in this deployment, as specified in the endpoint configuration for the endpoint. The value is taken from the request to the CreateEndpointConfig operation.
" } }, "InstanceType": { @@ -54168,13 +54163,13 @@ "AcceleratorType": { "target": "com.amazonaws.sagemaker#ProductionVariantAcceleratorType", "traits": { - "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify the size of the EI instance to use for the\n production variant.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify the size of the EI instance to use for the production variant.
" } }, "VariantStatus": { "target": "com.amazonaws.sagemaker#ProductionVariantStatusList", "traits": { - "smithy.api#documentation": "The endpoint variant status which describes the current deployment stage status or\n operational status.
" + "smithy.api#documentation": "The endpoint variant status which describes the current deployment stage status or operational status.
" } }, "CurrentServerlessConfig": { @@ -54192,18 +54187,18 @@ "ManagedInstanceScaling": { "target": "com.amazonaws.sagemaker#ProductionVariantManagedInstanceScaling", "traits": { - "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions\n as it scales up or down to accommodate traffic.
" + "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
" } }, "RoutingConfig": { "target": "com.amazonaws.sagemaker#ProductionVariantRoutingConfig", "traits": { - "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the\n endpoint hosts.
" + "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
" } } }, "traits": { - "smithy.api#documentation": "The production variant summary for a deployment when an endpoint is creating or\n updating with the CreateEndpoint\n or UpdateEndpoint\n operations. Describes the VariantStatus , weight and capacity for a\n production variant associated with an endpoint.
The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.
Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600.\n This value should not exceed JobDurationInSeconds.
Specifies how long a traffic phase should be. For custom load tests, the value should be between 120 and 3600. This value should not exceed JobDurationInSeconds.
The object key (or key name) uniquely identifies the \n object in an S3 bucket.
", + "smithy.api#documentation": "The object key (or key name) uniquely identifies the object in an S3 bucket.
", "smithy.api#required": {} } }, "VersionId": { "target": "com.amazonaws.sagemaker#VersionId", "traits": { - "smithy.api#documentation": "Version Id of the pipeline definition file. If not specified, Amazon SageMaker \n will retrieve the latest version.
" + "smithy.api#documentation": "Version Id of the pipeline definition file. If not specified, Amazon SageMaker will retrieve the latest version.
" } } }, @@ -54626,7 +54621,7 @@ "SelectiveExecutionResult": { "target": "com.amazonaws.sagemaker#SelectiveExecutionResult", "traits": { - "smithy.api#documentation": "The ARN from an execution of the current pipeline from which\n results are reused for this step.
" + "smithy.api#documentation": "The ARN from an execution of the current pipeline from which results are reused for this step.
" } } }, @@ -54694,13 +54689,13 @@ "Callback": { "target": "com.amazonaws.sagemaker#CallbackStepMetadata", "traits": { - "smithy.api#documentation": "The URL of the Amazon SQS queue used by this step execution, the pipeline generated token,\n and a list of output parameters.
" + "smithy.api#documentation": "The URL of the Amazon SQS queue used by this step execution, the pipeline generated token, and a list of output parameters.
" } }, "Lambda": { "target": "com.amazonaws.sagemaker#LambdaStepMetadata", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of\n output parameters.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Lambda function that was run by this step execution and a list of output parameters.
" } }, "EMR": { @@ -54712,13 +54707,13 @@ "QualityCheck": { "target": "com.amazonaws.sagemaker#QualityCheckStepMetadata", "traits": { - "smithy.api#documentation": "The configurations and outcomes of the check step execution. This includes:
\nThe type of the check conducted.
\nThe Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
\nThe Amazon S3 URIs of newly calculated baseline constraints and statistics.
\nThe model package group name provided.
\nThe Amazon S3 URI of the violation report if violations detected.
\nThe Amazon Resource Name (ARN) of check processing job initiated by the step execution.
\nThe Boolean flags indicating if the drift check is skipped.
\nIf step property BaselineUsedForDriftCheck is set the same as \n CalculatedBaseline.
The configurations and outcomes of the check step execution. This includes:
The type of the check conducted.
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The Boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
Container for the metadata for a Clarify check step. The configurations \n and outcomes of the check step execution. This includes:
\nThe type of the check conducted,
\nThe Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
\nThe Amazon S3 URIs of newly calculated baseline constraints and statistics.
\nThe model package group name provided.
\nThe Amazon S3 URI of the violation report if violations detected.
\nThe Amazon Resource Name (ARN) of check processing job initiated by the step execution.
\nThe boolean flags indicating if the drift check is skipped.
\nIf step property BaselineUsedForDriftCheck is set the same as \n CalculatedBaseline.
Container for the metadata for a Clarify check step. The configurations and outcomes of the check step execution. This includes:
The type of the check conducted,
The Amazon S3 URIs of baseline constraints and statistics files to be used for the drift check.
The Amazon S3 URIs of newly calculated baseline constraints and statistics.
The model package group name provided.
The Amazon S3 URI of the violation report if violations detected.
The Amazon Resource Name (ARN) of check processing job initiated by the step execution.
The boolean flags indicating if the drift check is skipped.
If step property BaselineUsedForDriftCheck is set the same as CalculatedBaseline.
Weight of the priority class. The value is within a range from 0 to 100, where 0 is the\n default.
\nA weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the\n default.
", + "smithy.api#documentation": "Weight of the priority class. The value is within a range from 0 to 100, where 0 is the default.
A weight of 0 is the lowest priority and 100 is the highest. Weight 0 is the default.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Priority class configuration. When included in PriorityClasses, these class\n configurations define how tasks are queued.
Priority class configuration. When included in PriorityClasses, these class configurations define how tasks are queued.
The number of ML compute instances to use in the processing job. For distributed\n processing jobs, specify a value greater than 1. The default value is 1.
", + "smithy.api#documentation": "The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
", "smithy.api#required": {} } }, @@ -55089,14 +55084,14 @@ "target": "com.amazonaws.sagemaker#ProcessingVolumeSizeInGB", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The size of the ML storage volume in gigabytes that you want to provision. You must\n specify sufficient ML storage for your scenario.
\nCertain Nitro-based instances include local storage with a fixed total size,\n dependent on the instance type. When using these instances for processing, Amazon SageMaker\n mounts the local instance storage instead of Amazon EBS gp2 storage. You can't request a\n VolumeSizeInGB greater than the total size of the local instance\n storage.
For a list of instance types that support local instance storage, including the\n total size per instance type, see Instance Store Volumes.
\nThe size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario.
Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can't request a VolumeSizeInGB greater than the total size of the local instance storage.
For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker\n uses to encrypt data on the storage volume attached to the ML compute instance(s) that\n run the processing job.
\nCertain Nitro-based instances include local storage, dependent on the instance\n type. Local storage volumes are encrypted using a hardware module on the instance.\n You can't request a VolumeKmsKeyId when using an instance type with\n local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
\nFor more information about local instance storage encryption, see SSD\n Instance Store Volumes.
\nThe Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output.\n Note that your processing script is responsible for putting records into your Feature\n Store.
", + "smithy.api#documentation": "The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
", "smithy.api#required": {} } } @@ -55169,13 +55164,13 @@ "AppManaged": { "target": "com.amazonaws.sagemaker#AppManaged", "traits": { - "smithy.api#documentation": "When True, input operations such as data download are managed natively by\n the processing job application. When False (default), input operations are\n managed by Amazon SageMaker.
When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
Configuration for downloading input data from Amazon S3 into the processing\n container.
" + "smithy.api#documentation": "Configuration for downloading input data from Amazon S3 into the processing container.
" } }, "DatasetDefinition": { @@ -55186,7 +55181,7 @@ } }, "traits": { - "smithy.api#documentation": "The inputs for a processing job. The processing input must specify exactly one of\n either S3Input or DatasetDefinition types.
The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.
A string, up to one KB in size, that contains metadata from the processing container\n when the processing job exits.
" + "smithy.api#documentation": "A string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
" } }, "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if\n it failed.
" + "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
" } }, "ProcessingEndTime": { @@ -55869,13 +55864,13 @@ "MonitoringScheduleArn": { "target": "com.amazonaws.sagemaker#MonitoringScheduleArn", "traits": { - "smithy.api#documentation": "The ARN of a monitoring schedule for an endpoint associated with this processing\n job.
" + "smithy.api#documentation": "The ARN of a monitoring schedule for an endpoint associated with this processing job.
" } }, "AutoMLJobArn": { "target": "com.amazonaws.sagemaker#AutoMLJobArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the AutoML job associated with this processing\n job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the AutoML job associated with this processing job.
" } }, "TrainingJobArn": { @@ -55887,12 +55882,12 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and\n Cost Management User Guide.
" + "smithy.api#documentation": "An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.
" } } }, "traits": { - "smithy.api#documentation": "An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more\n information, see Process Data and Evaluate\n Models.
" + "smithy.api#documentation": "An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
" } }, "com.amazonaws.sagemaker#ProcessingJobArn": { @@ -56020,13 +56015,13 @@ "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if\n it failed.
" + "smithy.api#documentation": "A string, up to one KB in size, that contains the reason a processing job failed, if it failed.
" } }, "ExitMessage": { "target": "com.amazonaws.sagemaker#ExitMessage", "traits": { - "smithy.api#documentation": "An optional string, up to one KB in size, that contains metadata from the processing\n container when the processing job exits.
" + "smithy.api#documentation": "An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.
" } } }, @@ -56073,18 +56068,18 @@ "FeatureStoreOutput": { "target": "com.amazonaws.sagemaker#ProcessingFeatureStoreOutput", "traits": { - "smithy.api#documentation": "Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output\n type is only supported when AppManaged is specified.
Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged is specified.
When True, output operations such as data upload are managed natively by\n the processing job application. When False (default), output operations are\n managed by Amazon SageMaker.
When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
Describes the results of a processing job. The processing output must specify exactly\n one of either S3Output or FeatureStoreOutput types.
Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.
An array of outputs configuring the data to upload from the processing\n container.
", + "smithy.api#documentation": "An array of outputs configuring the data to upload from the processing container.
", "smithy.api#required": {} } }, "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker\n uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS\n key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to\n all outputs.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.
The configuration for the resources in a cluster used to run the processing\n job.
", + "smithy.api#documentation": "The configuration for the resources in a cluster used to run the processing job.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a\n processing job. In distributed training, you specify more than one instance.
" + "smithy.api#documentation": "Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.
" } }, "com.amazonaws.sagemaker#ProcessingS3CompressionType": { @@ -56195,45 +56190,45 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing\n job.
", + "smithy.api#documentation": "The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.
", "smithy.api#required": {} } }, "LocalPath": { "target": "com.amazonaws.sagemaker#ProcessingLocalPath", "traits": { - "smithy.api#documentation": "The local path in your container where you want Amazon SageMaker to write input data to.\n LocalPath is an absolute path to the input data and must begin with\n /opt/ml/processing/. LocalPath is a required parameter\n when AppManaged is False (default).
The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
Whether you use an S3Prefix or a ManifestFile for the data\n type. If you choose S3Prefix, S3Uri identifies a key name\n prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job.\n If you choose ManifestFile, S3Uri identifies an object that is\n a manifest file containing a list of object keys that you want Amazon SageMaker to use for the\n processing job.
Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for the processing job.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker\n copies the data from the input source onto the local ML storage volume before starting\n your processing container. This is the most commonly used input mode. In\n Pipe mode, Amazon SageMaker streams input data from the source directly to your\n processing container into named pipes without using the ML storage volume.
Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
Whether to distribute the data from Amazon S3 to all processing instances with\n FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key,\n downloading one shard of data to each processing instance.
Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing\n container. Gzip can only be used when Pipe mode is specified\n as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from\n the source directly to your container without using the EBS volume.
Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
Configuration for downloading input data from Amazon S3 into the processing\n container.
" + "smithy.api#documentation": "Configuration for downloading input data from Amazon S3 into the processing container.
" } }, "com.amazonaws.sagemaker#ProcessingS3InputMode": { @@ -56260,21 +56255,21 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of\n a processing job.
", + "smithy.api#documentation": "A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.
", "smithy.api#required": {} } }, "LocalPath": { "target": "com.amazonaws.sagemaker#ProcessingLocalPath", "traits": { - "smithy.api#documentation": "The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3.\n LocalPath is an absolute path to a directory containing output files.\n This directory will be created by the platform and exist when your container's\n entrypoint is invoked.
The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container's entrypoint is invoked.
Whether to upload the results of the processing job continuously or after the job\n completes.
", + "smithy.api#documentation": "Whether to upload the results of the processing job continuously or after the job completes.
", "smithy.api#required": {} } } @@ -56313,7 +56308,7 @@ } }, "traits": { - "smithy.api#documentation": "Configures conditions under which the processing job should be stopped, such as how\n long the processing job has been running. After the condition is met, the processing job\n is stopped.
" + "smithy.api#documentation": "Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
" } }, "com.amazonaws.sagemaker#ProcessingVolumeSizeInGB": { @@ -56372,7 +56367,7 @@ "ModelName": { "target": "com.amazonaws.sagemaker#ModelName", "traits": { - "smithy.api#documentation": "The name of the model that you want to host. This is the name that you specified\n when creating the model.
" + "smithy.api#documentation": "The name of the model that you want to host. This is the name that you specified when creating the model.
" } }, "InitialInstanceCount": { @@ -56390,19 +56385,19 @@ "InitialVariantWeight": { "target": "com.amazonaws.sagemaker#VariantWeight", "traits": { - "smithy.api#documentation": "Determines initial traffic distribution among all of the models that you specify in\n the endpoint configuration. The traffic to a production variant is determined by the\n ratio of the VariantWeight to the sum of all VariantWeight\n values across all ProductionVariants. If unspecified, it defaults to 1.0.\n
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.
This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify the size of the EI instance to use for the\n production variant.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify the size of the EI instance to use for the production variant.
" } }, "CoreDumpConfig": { "target": "com.amazonaws.sagemaker#ProductionVariantCoreDumpConfig", "traits": { - "smithy.api#documentation": "Specifies configuration for a core dump from the model container when the process\n crashes.
" + "smithy.api#documentation": "Specifies configuration for a core dump from the model container when the process crashes.
" } }, "ServerlessConfig": { @@ -56414,48 +56409,48 @@ "VolumeSizeInGB": { "target": "com.amazonaws.sagemaker#ProductionVariantVolumeSizeInGB", "traits": { - "smithy.api#documentation": "The size, in GB, of the ML storage volume attached to individual inference instance\n associated with the production variant. Currently only Amazon EBS gp2 storage volumes are\n supported.
" + "smithy.api#documentation": "The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Currently only Amazon EBS gp2 storage volumes are supported.
" } }, "ModelDataDownloadTimeoutInSeconds": { "target": "com.amazonaws.sagemaker#ProductionVariantModelDataDownloadTimeoutInSeconds", "traits": { - "smithy.api#documentation": "The timeout value, in seconds, to download and extract the model that you want to host\n from Amazon S3 to the individual inference instance associated with this production\n variant.
" + "smithy.api#documentation": "The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant.
" } }, "ContainerStartupHealthCheckTimeoutInSeconds": { "target": "com.amazonaws.sagemaker#ProductionVariantContainerStartupHealthCheckTimeoutInSeconds", "traits": { - "smithy.api#documentation": "The timeout value, in seconds, for your inference container to pass health check by\n SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
" + "smithy.api#documentation": "The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
" } }, "EnableSSMAccess": { "target": "com.amazonaws.sagemaker#ProductionVariantSSMAccess", "traits": { - "smithy.api#documentation": " You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM)\n access for a production variant behind an endpoint. By default, SSM access is disabled\n for all production variants behind an endpoint. You can turn on or turn off SSM access\n for a production variant behind an existing endpoint by creating a new endpoint\n configuration and calling UpdateEndpoint.
You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoint. You can turn on or turn off SSM access for a production variant behind an existing endpoint by creating a new endpoint configuration and calling UpdateEndpoint.
Settings that control the range in the number of instances that the endpoint provisions\n as it scales up or down to accommodate traffic.
" + "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
" } }, "RoutingConfig": { "target": "com.amazonaws.sagemaker#ProductionVariantRoutingConfig", "traits": { - "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the\n endpoint hosts.
" + "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
" } }, "InferenceAmiVersion": { "target": "com.amazonaws.sagemaker#ProductionVariantInferenceAmiVersion", "traits": { - "smithy.api#documentation": "Specifies an option from a collection of preconfigured Amazon Machine Image (AMI)\n images. Each image is configured by Amazon Web Services with a set of software and driver\n versions. Amazon Web Services optimizes these configurations for different machine\n learning workloads.
\nBy selecting an AMI version, you can ensure that your inference environment is\n compatible with specific software requirements, such as CUDA driver versions, Linux\n kernel versions, or Amazon Web Services Neuron driver versions.
\nThe AMI version names, and their configurations, are the following:
\nAccelerator: GPU
\nNVIDIA driver version: 535
\nCUDA version: 12.2
\nAccelerator: GPU
\nNVIDIA driver version: 535
\nCUDA version: 12.2
\nNVIDIA Container Toolkit with disabled CUDA-compat mounting
\nAccelerator: GPU
\nNVIDIA driver version: 550
\nCUDA version: 12.4
\nNVIDIA Container Toolkit with disabled CUDA-compat mounting
\nAccelerator: Inferentia2 and Trainium
\nNeuron driver version: 2.19
\nSpecifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions. Amazon Web Services optimizes these configurations for different machine learning workloads.
By selecting an AMI version, you can ensure that your inference environment is compatible with specific software requirements, such as CUDA driver versions, Linux kernel versions, or Amazon Web Services Neuron driver versions.
The AMI version names, and their configurations, are the following:
Accelerator: GPU
NVIDIA driver version: 535
CUDA version: 12.2
Accelerator: GPU
NVIDIA driver version: 535
CUDA version: 12.2
NVIDIA Container Toolkit with disabled CUDA-compat mounting
Accelerator: GPU
NVIDIA driver version: 550
CUDA version: 12.4
NVIDIA Container Toolkit with disabled CUDA-compat mounting
Accelerator: Inferentia2 and Trainium
Neuron driver version: 2.19
Identifies a model that you want to host and the resources chosen to deploy for\n hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic\n among the models by specifying variant weights. For more information on production\n variants, check Production variants.\n
" + "smithy.api#documentation": "Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell SageMaker how to distribute traffic among the models by specifying variant weights. For more information on production variants, check Production variants.
" } }, "com.amazonaws.sagemaker#ProductionVariantAcceleratorType": { @@ -56522,12 +56517,12 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker\n uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The\n KmsKeyId can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"\n
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must\n include permissions to call kms:Encrypt. If you don't provide a KMS key ID,\n SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side\n encryption with KMS-managed keys for OutputDataConfig. If you use a bucket\n policy with an s3:PutObject permission that only allows objects with\n server-side encryption, set the condition key of\n s3:x-amz-server-side-encryption to \"aws:kms\". For more\n information, see KMS-Managed Encryption\n Keys in the Amazon Simple Storage Service Developer Guide.\n
The KMS key policy must grant permission to the IAM role that you specify in your\n CreateEndpoint and UpdateEndpoint requests. For more\n information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management\n Service Developer Guide.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
// KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
// Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
// KMS Key Alias
\"alias/ExampleAlias\"
// Amazon Resource Name (ARN) of a KMS Key Alias
\"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\"
If you use a KMS key ID or an alias of your KMS key, the SageMaker execution role must include permissions to call kms:Encrypt. If you don't provide a KMS key ID, SageMaker uses the default KMS key for Amazon S3 for your role's account. SageMaker uses server-side encryption with KMS-managed keys for OutputDataConfig. If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to \"aws:kms\". For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint and UpdateEndpoint requests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
Specifies configuration for a core dump from the model container when the process\n crashes.
" + "smithy.api#documentation": "Specifies configuration for a core dump from the model container when the process crashes.
" } }, "com.amazonaws.sagemaker#ProductionVariantInferenceAmiVersion": { @@ -57932,18 +57927,18 @@ "MinInstanceCount": { "target": "com.amazonaws.sagemaker#ManagedInstanceScalingMinInstanceCount", "traits": { - "smithy.api#documentation": "The minimum number of instances that the endpoint must retain when it scales down to\n accommodate a decrease in traffic.
" + "smithy.api#documentation": "The minimum number of instances that the endpoint must retain when it scales down to accommodate a decrease in traffic.
" } }, "MaxInstanceCount": { "target": "com.amazonaws.sagemaker#ManagedInstanceScalingMaxInstanceCount", "traits": { - "smithy.api#documentation": "The maximum number of instances that the endpoint can provision when it scales up to\n accommodate an increase in traffic.
" + "smithy.api#documentation": "The maximum number of instances that the endpoint can provision when it scales up to accommodate an increase in traffic.
" } } }, "traits": { - "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions\n as it scales up or down to accommodate traffic.
" + "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
" } }, "com.amazonaws.sagemaker#ProductionVariantModelDataDownloadTimeoutInSeconds": { @@ -57962,13 +57957,13 @@ "target": "com.amazonaws.sagemaker#RoutingStrategy", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Sets how the endpoint routes incoming traffic:
\n\n LEAST_OUTSTANDING_REQUESTS: The endpoint routes requests to the\n specific instances that have more capacity to process them.
\n RANDOM: The endpoint routes each request to a randomly chosen\n instance.
Sets how the endpoint routes incoming traffic:
LEAST_OUTSTANDING_REQUESTS: The endpoint routes requests to the specific instances that have more capacity to process them.
RANDOM: The endpoint routes each request to a randomly chosen instance.
Settings that control how the endpoint routes incoming traffic to the instances that the\n endpoint hosts.
" + "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
" } }, "com.amazonaws.sagemaker#ProductionVariantSSMAccess": { @@ -57996,7 +57991,7 @@ "ProvisionedConcurrency": { "target": "com.amazonaws.sagemaker#ServerlessProvisionedConcurrency", "traits": { - "smithy.api#documentation": "The amount of provisioned concurrency to allocate for the serverless endpoint.\n Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs.\n For more information about creating an Inference Recommender job, see\n CreateInferenceRecommendationsJobs.
\nThe amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
This field is not supported for serverless endpoint recommendations for Inference Recommender jobs. For more information about creating an Inference Recommender job, see CreateInferenceRecommendationsJobs.
The updated amount of provisioned concurrency to allocate for the serverless endpoint.\n Should be less than or equal to MaxConcurrency.
The updated amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to MaxConcurrency.
The endpoint variant status which describes the current deployment stage status or\n operational status.
\n\n Creating: Creating inference resources for the production\n variant.
\n Deleting: Terminating inference resources for the production\n variant.
\n Updating: Updating capacity for the production variant.
\n ActivatingTraffic: Turning on traffic for the production\n variant.
\n Baking: Waiting period to monitor the CloudWatch alarms in the\n automatic rollback configuration.
The endpoint variant status which describes the current deployment stage status or operational status.
Creating: Creating inference resources for the production variant.
Deleting: Terminating inference resources for the production variant.
Updating: Updating capacity for the production variant.
ActivatingTraffic: Turning on traffic for the production variant.
Baking: Waiting period to monitor the CloudWatch alarms in the automatic rollback configuration.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the\n inference images deployed on instances of this ProductionVariant.
An array of DeployedImage objects that specify the Amazon EC2 Container Registry paths of the inference images deployed on instances of this ProductionVariant.
The requested weight, as specified in the\n UpdateEndpointWeightsAndCapacities request.
The requested weight, as specified in the UpdateEndpointWeightsAndCapacities request.
The number of instances requested in the\n UpdateEndpointWeightsAndCapacities request.
The number of instances requested in the UpdateEndpointWeightsAndCapacities request.
The endpoint variant status which describes the current deployment stage status or\n operational status.
" + "smithy.api#documentation": "The endpoint variant status which describes the current deployment stage status or operational status.
" } }, "CurrentServerlessConfig": { @@ -58126,18 +58121,18 @@ "ManagedInstanceScaling": { "target": "com.amazonaws.sagemaker#ProductionVariantManagedInstanceScaling", "traits": { - "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions\n as it scales up or down to accommodate traffic.
" + "smithy.api#documentation": "Settings that control the range in the number of instances that the endpoint provisions as it scales up or down to accommodate traffic.
" } }, "RoutingConfig": { "target": "com.amazonaws.sagemaker#ProductionVariantRoutingConfig", "traits": { - "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the\n endpoint hosts.
" + "smithy.api#documentation": "Settings that control how the endpoint routes incoming traffic to the instances that the endpoint hosts.
" } } }, "traits": { - "smithy.api#documentation": "Describes weight and capacities for a production variant associated with an\n endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities\n API and the endpoint status is Updating, you get different desired and\n current values.
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
A time interval for capturing system metrics in milliseconds. Available values are\n 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
" + "smithy.api#documentation": "A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
" } }, "ProfilingParameters": { "target": "com.amazonaws.sagemaker#ProfilingParameters", "traits": { - "smithy.api#documentation": "Configuration information for capturing framework metrics. Available key strings for different profiling options are\n DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig.\n The following codes are configuration structures for the ProfilingParameters parameter. To learn more about\n how to configure the ProfilingParameters parameter, \n see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.\n
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and\n storage paths.
" + "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
" } }, "com.amazonaws.sagemaker#ProfilerConfigForUpdate": { @@ -58204,13 +58199,13 @@ "ProfilingIntervalInMilliseconds": { "target": "com.amazonaws.sagemaker#ProfilingIntervalInMilliseconds", "traits": { - "smithy.api#documentation": "A time interval for capturing system metrics in milliseconds. Available values are\n 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
" + "smithy.api#documentation": "A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.
" } }, "ProfilingParameters": { "target": "com.amazonaws.sagemaker#ProfilingParameters", "traits": { - "smithy.api#documentation": "Configuration information for capturing framework metrics. Available key strings for different profiling options are\n DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig.\n The following codes are configuration structures for the ProfilingParameters parameter. To learn more about\n how to configure the ProfilingParameters parameter, \n see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.\n
Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig, PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and\n storage paths.
" + "smithy.api#documentation": "Configuration information for updating the Amazon SageMaker Debugger profile parameters, system and framework metrics configurations, and storage paths.
" } }, "com.amazonaws.sagemaker#ProfilerRuleConfiguration": { @@ -58439,7 +58434,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } }, "LastModifiedTime": { @@ -58668,7 +58663,7 @@ } }, "traits": { - "smithy.api#documentation": "Part of the SuggestionQuery type. Specifies a hint for retrieving property\n names that begin with the specified text.
Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.
A suggested property name based on what you entered in the search textbox in the SageMaker\n console.
" + "smithy.api#documentation": "A suggested property name based on what you entered in the search textbox in the SageMaker console.
" } } }, "traits": { - "smithy.api#documentation": "A property name returned from a GetSearchSuggestions call that specifies a\n value in the PropertyNameQuery field.
A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.
A key value pair used when you provision a project as a service catalog product. For\n information, see What is Amazon Web Services Service\n Catalog.
" + "smithy.api#documentation": "A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog.
" } }, "com.amazonaws.sagemaker#ProvisioningParameterKey": { @@ -58754,7 +58749,7 @@ } }, "traits": { - "smithy.api#documentation": "Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
\nUse one of the following prices for bounding box tasks. Prices are in US dollars and\n should be based on the complexity of the task; the longer it takes in your initial\n testing, the more you should offer.
\n0.036
\n0.048
\n0.060
\n0.072
\n0.120
\n0.240
\n0.360
\n0.480
\n0.600
\n0.720
\n0.840
\n0.960
\n1.080
\n1.200
\nUse one of the following prices for image classification, text classification, and\n custom tasks. Prices are in US dollars.
\n0.012
\n0.024
\n0.036
\n0.048
\n0.060
\n0.072
\n0.120
\n0.240
\n0.360
\n0.480
\n0.600
\n0.720
\n0.840
\n0.960
\n1.080
\n1.200
\nUse one of the following prices for semantic segmentation tasks. Prices are in US\n dollars.
\n0.840
\n0.960
\n1.080
\n1.200
\nUse one of the following prices for Textract AnalyzeDocument Important Form Key Amazon\n Augmented AI review tasks. Prices are in US dollars.
\n2.400
\n2.280
\n2.160
\n2.040
\n1.920
\n1.800
\n1.680
\n1.560
\n1.440
\n1.320
\n1.200
\n1.080
\n0.960
\n0.840
\n0.720
\n0.600
\n0.480
\n0.360
\n0.240
\n0.120
\n0.072
\n0.060
\n0.048
\n0.036
\n0.024
\n0.012
\nUse one of the following prices for Rekognition DetectModerationLabels Amazon\n Augmented AI review tasks. Prices are in US dollars.
\n1.200
\n1.080
\n0.960
\n0.840
\n0.720
\n0.600
\n0.480
\n0.360
\n0.240
\n0.120
\n0.072
\n0.060
\n0.048
\n0.036
\n0.024
\n0.012
\nUse one of the following prices for Amazon Augmented AI custom human review tasks.\n Prices are in US dollars.
\n1.200
\n1.080
\n0.960
\n0.840
\n0.720
\n0.600
\n0.480
\n0.360
\n0.240
\n0.120
\n0.072
\n0.060
\n0.048
\n0.036
\n0.024
\n0.012
\nDefines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
0.012
0.024
0.036
0.048
0.060
0.072
0.120
0.240
0.360
0.480
0.600
0.720
0.840
0.960
1.080
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
0.840
0.960
1.080
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
2.400
2.280
2.160
2.040
1.920
1.800
1.680
1.560
1.440
1.320
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
1.200
1.080
0.960
0.840
0.720
0.600
0.480
0.360
0.240
0.120
0.072
0.060
0.048
0.036
0.024
0.012
Adds a resouce policy to control access to a model group. For information about\n resoure policies, see Identity-based\n policies and resource-based policies in the Amazon Web Services\n Identity and Access Management User Guide..
" + "smithy.api#documentation": "Adds a resouce policy to control access to a model group. For information about resoure policies, see Identity-based policies and resource-based policies in the Amazon Web Services Identity and Access Management User Guide..
" } }, "com.amazonaws.sagemaker#PutModelPackageGroupPolicyInput": { @@ -58874,18 +58869,18 @@ "SkipCheck": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "This flag indicates if the drift check against the previous baseline will be skipped or not. \n If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if the drift check against the previous baseline will be skipped or not. If it is set to False, the previous baseline of the configured check type must be available.
This flag indicates if a newly calculated baseline can be accessed through step properties \n BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. \n If it is set to False, the previous baseline of the configured check type must also be available. \n These can be accessed through the BaselineUsedForDriftCheckConstraints and \n BaselineUsedForDriftCheckStatistics properties.
This flag indicates if a newly calculated baseline can be accessed through step properties BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics. If it is set to False, the previous baseline of the configured check type must also be available. These can be accessed through the BaselineUsedForDriftCheckConstraints and BaselineUsedForDriftCheckStatistics properties.
Container for the metadata for a Quality check step. For more information, see \n the topic on QualityCheck step in the Amazon SageMaker Developer Guide.\n
" + "smithy.api#documentation": "Container for the metadata for a Quality check step. For more information, see the topic on QualityCheck step in the Amazon SageMaker Developer Guide.
" } }, "com.amazonaws.sagemaker#QueryFilters": { @@ -58894,7 +58889,7 @@ "Types": { "target": "com.amazonaws.sagemaker#QueryTypes", "traits": { - "smithy.api#documentation": "Filter the lineage entities connected to the StartArn by type. For example: DataSet, \n Model, Endpoint, or ModelDeployment.
Filter the lineage entities connected to the StartArn by type. For example: DataSet, Model, Endpoint, or ModelDeployment.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. \n If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
Filter the lineage entities connected to the StartArn(s) by a set if property key value pairs. If multiple pairs are provided, an entity is included in the results if it matches any of the provided pairs.
A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the \n QueryLineage API action.
A set of filters to narrow the set of lineage entities connected to the StartArn(s) returned by the QueryLineage API action.
Use this action to inspect your lineage and discover relationships between entities. \n For more information, see \n Querying Lineage Entities in the Amazon SageMaker Developer Guide.
", + "smithy.api#documentation": "Use this action to inspect your lineage and discover relationships between entities. For more information, see Querying Lineage Entities in the Amazon SageMaker Developer Guide.
", "smithy.api#paginated": { "inputToken": "NextToken", "outputToken": "NextToken", @@ -58988,25 +58983,25 @@ "Direction": { "target": "com.amazonaws.sagemaker#Direction", "traits": { - "smithy.api#documentation": "Associations between lineage entities have a direction. This parameter determines the direction from the \n StartArn(s) that the query traverses.
" + "smithy.api#documentation": "Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.
" } }, "IncludeEdges": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": " Setting this value to True retrieves not only the entities of interest but also the \n Associations and \n lineage entities on the path. Set to False to only return lineage entities that match your query.
Setting this value to True retrieves not only the entities of interest but also the Associations and lineage entities on the path. Set to False to only return lineage entities that match your query.
A set of filtering parameters that allow you to specify which entities should be returned.
\nProperties - Key-value pairs to match on the lineage entities' properties.
\nLineageTypes - A set of lineage entity types to match on. For example: TrialComponent, \n Artifact, or Context.
CreatedBefore - Filter entities created before this date.
\nModifiedBefore - Filter entities modified before this date.
\nModifiedAfter - Filter entities modified after this date.
\nA set of filtering parameters that allow you to specify which entities should be returned.
Properties - Key-value pairs to match on the lineage entities' properties.
LineageTypes - A set of lineage entity types to match on. For example: TrialComponent, Artifact, or Context.
CreatedBefore - Filter entities created before this date.
ModifiedBefore - Filter entities modified before this date.
ModifiedAfter - Filter entities modified after this date.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number \n of Associations from the StartArn entity to the matched results.
The maximum depth in lineage relationships from the StartArns that are traversed. Depth is a measure of the number of Associations from the StartArn entity to the matched results.
A list of custom SageMaker AI images that are configured to run as a RSession\n app.
" + "smithy.api#documentation": "A list of custom SageMaker AI images that are configured to run as a RSession app.
" } } }, @@ -59143,18 +59138,18 @@ "AccessStatus": { "target": "com.amazonaws.sagemaker#RStudioServerProAccessStatus", "traits": { - "smithy.api#documentation": "Indicates whether the current user has access to the RStudioServerPro\n app.
Indicates whether the current user has access to the RStudioServerPro app.
The level of permissions that the user has within the RStudioServerPro app.\n This value defaults to `User`. The `Admin` value allows the user access to the RStudio\n Administrative Dashboard.
The level of permissions that the user has within the RStudioServerPro app. This value defaults to `User`. The `Admin` value allows the user access to the RStudio Administrative Dashboard.
A collection of settings that configure user interaction with the\n RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
The ARN of the execution role for the RStudioServerPro Domain-level\n app.
The ARN of the execution role for the RStudioServerPro Domain-level app.
A collection of settings that configure the RStudioServerPro Domain-level\n app.
A collection of settings that configure the RStudioServerPro Domain-level app.
A collection of settings that update the current configuration for the\n RStudioServerPro Domain-level app.
A collection of settings that update the current configuration for the RStudioServerPro Domain-level app.
Identifies the Amazon S3 bucket where you want SageMaker to store the \n compiled model artifacts.
" + "smithy.api#documentation": "Identifies the Amazon S3 bucket where you want SageMaker to store the compiled model artifacts.
" } } }, "traits": { - "smithy.api#documentation": "Provides information about the output configuration for the compiled \n model.
" + "smithy.api#documentation": "Provides information about the output configuration for the compiled model.
" } }, "com.amazonaws.sagemaker#RecommendationJobContainerConfig": { @@ -59359,19 +59354,19 @@ "Domain": { "target": "com.amazonaws.sagemaker#String", "traits": { - "smithy.api#documentation": "The machine learning domain of the model and its components.
\nValid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING |\n MACHINE_LEARNING\n
The machine learning domain of the model and its components.
Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING
The machine learning task that the model accomplishes.
\nValid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION\n | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION |\n REGRESSION | OTHER\n
The machine learning task that the model accomplishes.
Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER
The machine learning framework of the container image.
\nValid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN\n
The machine learning framework of the container image.
Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
\nValid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn |\n densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet\n
The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.
Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet
The endpoint type to receive recommendations for. By default this is null, and the results of \n the inference recommendation job return a combined list of both real-time and serverless benchmarks.\n By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
" + "smithy.api#documentation": "The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.
" } }, "DataInputConfig": { "target": "com.amazonaws.sagemaker#RecommendationJobDataInputConfig", "traits": { - "smithy.api#documentation": "Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form.\n This field is used for optimizing your model using SageMaker Neo. For more information, see\n DataInputConfig.
" + "smithy.api#documentation": "Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.
" } }, "SupportedResponseMIMETypes": { @@ -59418,7 +59413,7 @@ } }, "traits": { - "smithy.api#documentation": "Specifies mandatory fields for running an Inference Recommender job directly in the\n CreateInferenceRecommendationsJob\n API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use\n ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key \n that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. \n This key will be passed to SageMaker Hosting for endpoint creation.
\nThe SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage \n volume of the endpoints created for inference recommendation. The inference recommendation job will fail \n asynchronously during endpoint configuration creation if the role passed does not have \n kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:\n
For more information about key identifiers, see \n Key identifiers (KeyID) in the \n Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. This key will be passed to SageMaker Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant permission in order to encrypt data on the storage volume of the endpoints created for inference recommendation. The inference recommendation job will fail asynchronously during endpoint configuration creation if the role passed does not have kms:CreateGrant permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
// Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>\"
// KMS Key Alias
\"alias/ExampleAlias\"
// Amazon Resource Name (ARN) of a KMS Key Alias
\"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>\"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
" } }, "ContainerConfig": { "target": "com.amazonaws.sagemaker#RecommendationJobContainerConfig", "traits": { - "smithy.api#documentation": "Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig\n override the corresponding fields in the model package.
Specifies mandatory fields for running an Inference Recommender job. The fields specified in ContainerConfig override the corresponding fields in the model package.
The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key \n that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. \n The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:\n
// KMS Key Alias
\n\n \"alias/ExampleAlias\"\n
// Amazon Resource Name (ARN) of a KMS Key Alias
\n\n \"arn:aws:kms:\n
For more information about key identifiers, see \n Key identifiers (KeyID) in the \n Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt your output artifacts with Amazon S3 server-side encryption. The SageMaker execution role must have kms:GenerateDataKey permission.
The KmsKeyId can be any of the following formats:
// KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
// Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>\"
// KMS Key Alias
\"alias/ExampleAlias\"
// Amazon Resource Name (ARN) of a KMS Key Alias
\"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>\"
For more information about key identifiers, see Key identifiers (KeyID) in the Amazon Web Services Key Management Service (Amazon Web Services KMS) documentation.
" } }, "CompiledOutputConfig": { "target": "com.amazonaws.sagemaker#RecommendationJobCompiledOutputConfig", "traits": { - "smithy.api#documentation": "Provides information about the output configuration for the compiled \n model.
" + "smithy.api#documentation": "Provides information about the output configuration for the compiled model.
" } } }, @@ -59627,7 +59622,7 @@ } }, "traits": { - "smithy.api#documentation": "Specifies the maximum number of jobs that can run in parallel \n and the maximum number of jobs that can run.
" + "smithy.api#documentation": "Specifies the maximum number of jobs that can run in parallel and the maximum number of jobs that can run.
" } }, "com.amazonaws.sagemaker#RecommendationJobStatus": { @@ -59695,18 +59690,18 @@ "ModelLatencyThresholds": { "target": "com.amazonaws.sagemaker#ModelLatencyThresholds", "traits": { - "smithy.api#documentation": "The interval of time taken by a model to respond as viewed from SageMaker. \n The interval includes the local communication time taken to send the request \n and to fetch the response from the container of a model and the time taken to \n complete the inference in the container.
" + "smithy.api#documentation": "The interval of time taken by a model to respond as viewed from SageMaker. The interval includes the local communication time taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
" } }, "FlatInvocations": { "target": "com.amazonaws.sagemaker#FlatInvocations", "traits": { - "smithy.api#documentation": "Stops a load test when the number of invocations (TPS) peaks and flattens,\n which means that the instance has reached capacity. The default value is Stop.\n If you want the load test to continue after invocations have flattened, set the value to Continue.
Stops a load test when the number of invocations (TPS) peaks and flattens, which means that the instance has reached capacity. The default value is Stop. If you want the load test to continue after invocations have flattened, set the value to Continue.
Specifies conditions for stopping a job. When a job reaches a \n stopping condition limit, SageMaker ends the job.
" + "smithy.api#documentation": "Specifies conditions for stopping a job. When a job reaches a stopping condition limit, SageMaker ends the job.
" } }, "com.amazonaws.sagemaker#RecommendationJobSupportedContentType": { @@ -59788,7 +59783,7 @@ "target": "com.amazonaws.sagemaker#RecommendationJobVpcSecurityGroupIds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The VPC security group IDs. IDs have the form of sg-xxxxxxxx.\n Specify the security groups for the VPC that is specified in the Subnets field.
The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The expected CPU utilization at maximum invocations per minute for the instance.
\n\n NaN indicates that the value is not available.
The expected CPU utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
\n\n NaN indicates that the value is not available.
The expected memory utilization at maximum invocations per minute for the instance.
NaN indicates that the value is not available.
The time it takes to launch new compute resources for a serverless endpoint.\n The time can vary depending on the model size, how long it takes to download the\n model, and the start-up time of the container.
\n\n NaN indicates that the value is not available.
The time it takes to launch new compute resources for a serverless endpoint. The time can vary depending on the model size, how long it takes to download the model, and the start-up time of the container.
NaN indicates that the value is not available.
The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate\n datasets.
", + "smithy.api#documentation": "The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
", "smithy.api#required": {} } }, @@ -60028,7 +60023,7 @@ "KmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker\n uses to encrypt data from a Redshift execution.
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
" } }, "OutputFormat": { @@ -60244,7 +60239,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" + "smithy.api#documentation": "Configuration for remote debugging for the CreateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
" } }, "com.amazonaws.sagemaker#RemoteDebugConfigForUpdate": { @@ -60258,7 +60253,7 @@ } }, "traits": { - "smithy.api#documentation": "Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging\n functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
" + "smithy.api#documentation": "Configuration for remote debugging for the UpdateTrainingJob API. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
" } }, "com.amazonaws.sagemaker#RenderUiTemplate": { @@ -60291,7 +60286,7 @@ "target": "com.amazonaws.sagemaker#RenderableTask", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A RenderableTask object containing a representative task to\n render.
A RenderableTask object containing a representative task to render.
The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the\n template.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) that has access to the S3 objects that are used by the template.
", "smithy.api#required": {} } }, "HumanTaskUiArn": { "target": "com.amazonaws.sagemaker#HumanTaskUiArn", "traits": { - "smithy.api#documentation": "The HumanTaskUiArn of the worker UI that you want to render. Do not\n provide a HumanTaskUiArn if you use the UiTemplate\n parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
" + "smithy.api#documentation": "The HumanTaskUiArn of the worker UI that you want to render. Do not provide a HumanTaskUiArn if you use the UiTemplate parameter.
See a list of available Human Ui Amazon Resource Names (ARNs) in UiConfig.
" } } }, @@ -60329,7 +60324,7 @@ "target": "com.amazonaws.sagemaker#RenderingErrorList", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of one or more RenderingError objects if any were encountered\n while rendering the template. If there were no errors, the list is empty.
A list of one or more RenderingError objects if any were encountered while rendering the template. If there were no errors, the list is empty.
A JSON object that contains values for the variables defined in the template. It is\n made available to the template under the substitution variable task.input.\n For example, if you define a variable task.input.text in your template, you\n can supply the variable in the JSON object as \"text\": \"sample text\".
A JSON object that contains values for the variables defined in the template. It is made available to the template under the substitution variable task.input. For example, if you define a variable task.input.text in your template, you can supply the variable in the JSON object as \"text\": \"sample text\".
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides\n credentials to authenticate to the private Docker registry where your model image is\n hosted. For information about how to create an Amazon Web Services Lambda function, see\n Create a Lambda function\n with the console in the Amazon Web Services Lambda Developer\n Guide.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that provides credentials to authenticate to the private Docker registry where your model image is hosted. For information about how to create an Amazon Web Services Lambda function, see Create a Lambda function with the console in the Amazon Web Services Lambda Developer Guide.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies an authentication configuration for the private docker registry where your\n model image is hosted. Specify a value for this property only if you specified\n Vpc as the value for the RepositoryAccessMode field of the\n ImageConfig object that you passed to a call to\n CreateModel and the private Docker registry where the model image is\n hosted requires authentication.
Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the ImageConfig object that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.
The number of whole hours in the total duration for this reserved capacity\n offering.
" + "smithy.api#documentation": "The number of whole hours in the total duration for this reserved capacity offering.
" } }, "DurationMinutes": { "target": "com.amazonaws.sagemaker#ReservedCapacityDurationMinutes", "traits": { - "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this reserved\n capacity offering.
" + "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this reserved capacity offering.
" } }, "StartTime": { @@ -60566,7 +60561,7 @@ } }, "traits": { - "smithy.api#documentation": "Details about a reserved capacity offering for a training plan offering.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
Details about a reserved capacity offering for a training plan offering.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The additional minutes beyond whole hours in the total duration for this reserved\n capacity.
" + "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this reserved capacity.
" } }, "StartTime": { @@ -60695,7 +60690,7 @@ } }, "traits": { - "smithy.api#documentation": "Details of a reserved capacity for the training plan.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
Details of a reserved capacity for the training plan.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
A resource catalog containing all of the resources of a specific resource type within\n a resource owner account. For an example on sharing the Amazon SageMaker Feature Store\n DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.\n
A resource catalog containing all of the resources of a specific resource type within a resource owner account. For an example on sharing the Amazon SageMaker Feature Store DefaultFeatureGroupCatalog, see Share Amazon SageMaker Catalog resource type in the Amazon SageMaker Developer Guide.
The ML compute instance type.
\nSageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting\n December 9th, 2022.
\n\n Amazon EC2 P4de instances\n (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance\n HBM2e GPU memory, which accelerate the speed of training ML models that need to be\n trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker\n supports ML training jobs on P4de instances (ml.p4de.24xlarge) to\n reduce model training time. The ml.p4de.24xlarge instances are\n available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
\nUS West (Oregon) (us-west-2)
\nTo request quota limit increase and start using P4de instances, contact the SageMaker\n Training service team through your account team.
\nThe ML compute instance type.
SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de instances is in preview release starting December 9th, 2022.
Amazon EC2 P4de instances (currently in preview) are powered by 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory, which accelerate the speed of training ML models that need to be trained on large datasets of high-resolution data. In this preview release, Amazon SageMaker supports ML training jobs on P4de instances (ml.p4de.24xlarge) to reduce model training time. The ml.p4de.24xlarge instances are available in the following Amazon Web Services Regions.
US East (N. Virginia) (us-east-1)
US West (Oregon) (us-west-2)
To request quota limit increase and start using P4de instances, contact the SageMaker Training service team through your account team.
The number of ML compute instances to use. For distributed training, provide a\n value greater than 1.
" + "smithy.api#documentation": "The number of ML compute instances to use. For distributed training, provide a value greater than 1.
" } }, "VolumeSizeInGB": { "target": "com.amazonaws.sagemaker#VolumeSizeInGB", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The size of the ML storage volume that you want to provision.
\nML storage volumes store model artifacts and incremental states. Training\n algorithms might also use the ML storage volume for scratch space. If you want to store\n the training data in the ML storage volume, choose File as the\n TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD\n volumes, SageMaker doesn't provision Amazon EBS General Purpose SSD (gp2) storage.\n Available storage is fixed to the NVMe-type instance's storage capacity. SageMaker configures\n storage paths for training datasets, checkpoints, model artifacts, and outputs to use\n the entire capacity of the instance storage. For example, ML instance families with the\n NVMe-type instance storage include ml.p4d, ml.g4dn, and\n ml.g5.
When using an ML instance with the EBS-only storage option and without instance\n storage, you must define the size of EBS volume through VolumeSizeInGB in\n the ResourceConfig API. For example, ML instance families that use EBS\n volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
\nTo find the default local paths defined by the SageMaker training platform, see Amazon SageMaker\n Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and\n Outputs.
", + "smithy.api#documentation": "The size of the ML storage volume that you want to provision.
ML storage volumes store model artifacts and incremental states. Training algorithms might also use the ML storage volume for scratch space. If you want to store the training data in the ML storage volume, choose File as the TrainingInputMode in the algorithm specification.
When using an ML instance with NVMe SSD volumes, SageMaker doesn't provision Amazon EBS General Purpose SSD (gp2) storage. Available storage is fixed to the NVMe-type instance's storage capacity. SageMaker configures storage paths for training datasets, checkpoints, model artifacts, and outputs to use the entire capacity of the instance storage. For example, ML instance families with the NVMe-type instance storage include ml.p4d, ml.g4dn, and ml.g5.
When using an ML instance with the EBS-only storage option and without instance storage, you must define the size of EBS volume through VolumeSizeInGB in the ResourceConfig API. For example, ML instance families that use EBS volumes include ml.c5 and ml.p2.
To look up instance types and their instance storage types and volumes, see Amazon EC2 Instance Types.
To find the default local paths defined by the SageMaker training platform, see Amazon SageMaker Training Storage Folders for Training Datasets, Checkpoints, Model Artifacts, and Outputs.
", "smithy.api#required": {} } }, "VolumeKmsKeyId": { "target": "com.amazonaws.sagemaker#KmsKeyId", "traits": { - "smithy.api#documentation": "The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume\n attached to the ML compute instance(s) that run the training job.
\nCertain Nitro-based instances include local storage, dependent on the instance\n type. Local storage volumes are encrypted using a hardware module on the instance.\n You can't request a VolumeKmsKeyId when using an instance type with\n local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
\nFor more information about local instance storage encryption, see SSD\n Instance Store Volumes.
\nThe VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
\n\n \"1234abcd-12ab-34cd-56ef-1234567890ab\"\n
// Amazon Resource Name (ARN) of a KMS Key
\n\n \"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"\n
The Amazon Web Services KMS key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be in any of the following formats:
// KMS Key ID
\"1234abcd-12ab-34cd-56ef-1234567890ab\"
// Amazon Resource Name (ARN) of a KMS Key
\"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\"
The duration of time in seconds to retain configured resources in a warm pool for\n subsequent training jobs.
" + "smithy.api#documentation": "The duration of time in seconds to retain configured resources in a warm pool for subsequent training jobs.
" } }, "InstanceGroups": { @@ -60879,7 +60874,7 @@ } }, "traits": { - "smithy.api#documentation": "Describes the resources, including machine learning (ML) compute instances and ML\n storage volumes, to use for model training.
" + "smithy.api#documentation": "Describes the resources, including machine learning (ML) compute instances and ML storage volumes, to use for model training.
" } }, "com.amazonaws.sagemaker#ResourceConfigForUpdate": { @@ -60889,13 +60884,13 @@ "target": "com.amazonaws.sagemaker#KeepAlivePeriodInSeconds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The KeepAlivePeriodInSeconds value specified in the\n ResourceConfig to update.
The KeepAlivePeriodInSeconds value specified in the ResourceConfig to update.
The ResourceConfig to update KeepAlivePeriodInSeconds. Other\n fields in the ResourceConfig cannot be updated.
The ResourceConfig to update KeepAlivePeriodInSeconds. Other fields in the ResourceConfig cannot be updated.
You have exceeded an SageMaker resource limit. For example, you might have too many\n training jobs created.
", + "smithy.api#documentation": "You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
", "smithy.api#error": "client" } }, @@ -60937,14 +60932,14 @@ "MaxNumberOfTrainingJobs": { "target": "com.amazonaws.sagemaker#MaxNumberOfTrainingJobs", "traits": { - "smithy.api#documentation": "The maximum number of training jobs that a hyperparameter tuning job can\n launch.
" + "smithy.api#documentation": "The maximum number of training jobs that a hyperparameter tuning job can launch.
" } }, "MaxParallelTrainingJobs": { "target": "com.amazonaws.sagemaker#MaxParallelTrainingJobs", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The maximum number of concurrent training jobs that a hyperparameter tuning job can\n launch.
", + "smithy.api#documentation": "The maximum number of concurrent training jobs that a hyperparameter tuning job can launch.
", "smithy.api#required": {} } }, @@ -60956,7 +60951,7 @@ } }, "traits": { - "smithy.api#documentation": "Specifies the maximum number of training jobs and parallel training jobs that a\n hyperparameter tuning job can launch.
" + "smithy.api#documentation": "Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
" } }, "com.amazonaws.sagemaker#ResourceNotFound": { @@ -61007,14 +61002,14 @@ "target": "com.amazonaws.sagemaker#ResourceSharingStrategy", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The strategy of how idle compute is shared within the cluster. The following are the\n options of strategies.
\n\n DontLend: entities do not lend idle compute.
\n Lend: entities can lend idle compute to entities that can\n borrow.
\n LendandBorrow: entities can lend idle compute and borrow idle compute\n from other entities.
Default is LendandBorrow.
The strategy of how idle compute is shared within the cluster. The following are the options of strategies.
DontLend: entities do not lend idle compute.
Lend: entities can lend idle compute to entities that can borrow.
LendandBorrow: entities can lend idle compute and borrow idle compute from other entities.
Default is LendandBorrow.
The limit on how much idle compute can be borrowed.The values can be 1 - 500 percent of\n idle compute that the team is allowed to borrow.
\nDefault is 50.
The limit on how much idle compute can be borrowed.The values can be 1 - 500 percent of idle compute that the team is allowed to borrow.
Default is 50.
The instance type that the image version runs on.
\n\n JupyterServer apps only support the system value.
For KernelGateway apps, the system\n value is translated to ml.t3.medium. KernelGateway apps also support all other values for available\n instance types.
The instance type that the image version runs on.
JupyterServer apps only support the system value.
For KernelGateway apps, the system value is translated to ml.t3.medium. KernelGateway apps also support all other values for available instance types.
The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the\n Resource.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.
" } } }, "traits": { - "smithy.api#documentation": "Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that\n the version runs on.
\nWhen both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
Specifies the ARN's of a SageMaker AI image and SageMaker AI image version, and the instance type that the version runs on.
When both SageMakerImageVersionArn and SageMakerImageArn are passed, SageMakerImageVersionArn is used. Any updates to SageMakerImageArn will not take effect if SageMakerImageVersionArn already exists in the ResourceSpec because SageMakerImageVersionArn always takes precedence. To clear the value set for SageMakerImageVersionArn, pass None as the value.
The default is Retain, which specifies to keep the data stored on the\n Amazon EFS volume.
Specify Delete to delete the data stored on the Amazon EFS\n volume.
The default is Retain, which specifies to keep the data stored on the Amazon EFS volume.
Specify Delete to delete the data stored on the Amazon EFS volume.
A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than once.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -61283,7 +61278,7 @@ "ParallelismConfiguration": { "target": "com.amazonaws.sagemaker#ParallelismConfiguration", "traits": { - "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration \n of the parent pipeline.
" + "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration of the parent pipeline.
" } } }, @@ -61312,13 +61307,13 @@ "target": "com.amazonaws.sagemaker#MaximumRetryAttempts", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The number of times to retry the job. When the job is retried, it's\n SecondaryStatus is changed to STARTING.
The number of times to retry the job. When the job is retried, it's SecondaryStatus is changed to STARTING.
The retry strategy to use when a training job fails due to an\n InternalServerError. RetryStrategy is specified as part of\n the CreateTrainingJob and CreateHyperParameterTuningJob\n requests. You can add the StoppingCondition parameter to the request to\n limit the training time for the complete job.
The retry strategy to use when a training job fails due to an InternalServerError. RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.
Batch size for each rolling step to provision capacity and turn on traffic on the new\n endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between\n 5% to 50% of the variant's total instance count.
", + "smithy.api#documentation": "Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant's total instance count.
", "smithy.api#required": {} } }, @@ -61368,7 +61363,7 @@ "target": "com.amazonaws.sagemaker#WaitIntervalInSeconds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The length of the baking period, during which SageMaker monitors alarms for each batch on\n the new fleet.
", + "smithy.api#documentation": "The length of the baking period, during which SageMaker monitors alarms for each batch on the new fleet.
", "smithy.api#required": {} } }, @@ -61381,7 +61376,7 @@ "RollbackMaximumBatchSize": { "target": "com.amazonaws.sagemaker#CapacitySize", "traits": { - "smithy.api#documentation": "Batch size for rollback to the old endpoint fleet. Each rolling step to provision\n capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the\n new endpoint fleet. If this field is absent, the default value will be set to 100% of\n total capacity which means to bring up the whole capacity of the old fleet at once\n during rollback.
" + "smithy.api#documentation": "Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.
" } } }, @@ -61513,7 +61508,7 @@ "target": "com.amazonaws.sagemaker#S3DataType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "If you choose S3Prefix, S3Uri identifies a key name prefix.\n SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that\n is a manifest file containing a list of object keys that you want SageMaker to use for model\n training.
If you choose AugmentedManifestFile, S3Uri identifies an\n object that is an augmented manifest file in JSON lines format. This file contains the\n data you want to use for model training. AugmentedManifestFile can only be\n used if the Channel's input mode is Pipe.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix for model training.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want SageMaker to use for model training.
If you choose AugmentedManifestFile, S3Uri identifies an object that is an augmented manifest file in JSON lines format. This file contains the data you want to use for model training. AugmentedManifestFile can only be used if the Channel's input mode is Pipe.
Depending on the value specified for the S3DataType, identifies either\n a key name prefix or a manifest. For example:
A key name prefix might look like this:\n s3://bucketname/exampleprefix/\n
A manifest might look like this:\n s3://bucketname/example.manifest\n
A manifest is an S3 object which is a JSON file consisting of an array of\n elements. The first element is a prefix which is followed by one or more\n suffixes. SageMaker appends the suffix elements to the prefix to get a full set of\n S3Uri. Note that the prefix must be a valid non-empty\n S3Uri that precludes users from specifying a manifest whose\n individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
\n\n [ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},\n
\n \"relative/path/to/custdata-1\",\n
\n \"relative/path/custdata-2\",\n
\n ...\n
\n \"relative/path/custdata-N\"\n
\n ]\n
This JSON is equivalent to the following S3Uri\n list:
\n s3://customer_bucket/some/prefix/relative/path/to/custdata-1\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-2\n
\n ...\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-N\n
The complete set of S3Uri in this manifest is the input data\n for the channel for this data source. The object that each S3Uri\n points to must be readable by the IAM role that SageMaker uses to perform tasks on\n your behalf.
Your input bucket must be located in same Amazon Web Services region as your\n training job.
", + "smithy.api#documentation": "Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/
A manifest might look like this: s3://bucketname/example.manifest
A manifest is an S3 object which is a JSON file consisting of an array of elements. The first element is a prefix which is followed by one or more suffixes. SageMaker appends the suffix elements to the prefix to get a full set of S3Uri. Note that the prefix must be a valid non-empty S3Uri that precludes users from specifying a manifest whose individual S3Uri is sourced from different S3 buckets.
The following code example shows a valid manifest format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
This JSON is equivalent to the following S3Uri list:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uri in this manifest is the input data for the channel for this data source. The object that each S3Uri points to must be readable by the IAM role that SageMaker uses to perform tasks on your behalf.
Your input bucket must be located in same Amazon Web Services region as your training job.
", "smithy.api#required": {} } }, "S3DataDistributionType": { "target": "com.amazonaws.sagemaker#S3DataDistribution", "traits": { - "smithy.api#documentation": "If you want SageMaker to replicate the entire dataset on each ML compute instance that\n is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is\n launched for model training, specify ShardedByS3Key. If there are\n n ML compute instances launched for a training job, each\n instance gets approximately 1/n of the number of S3 objects. In\n this case, model training on each machine uses only the subset of training data.
Don't choose more ML compute instances for training than available S3 objects. If\n you do, some nodes won't get any data and you will pay for nodes that aren't getting any\n training data. This applies in both File and Pipe modes. Keep this in mind when\n developing algorithms.
\nIn distributed training, where you use multiple ML compute EC2 instances, you might\n choose ShardedByS3Key. If the algorithm requires copying training data to\n the ML storage volume (when TrainingInputMode is set to File),\n this copies 1/n of the number of objects.
If you want SageMaker to replicate the entire dataset on each ML compute instance that is launched for model training, specify FullyReplicated.
If you want SageMaker to replicate a subset of data on each ML compute instance that is launched for model training, specify ShardedByS3Key. If there are n ML compute instances launched for a training job, each instance gets approximately 1/n of the number of S3 objects. In this case, model training on each machine uses only the subset of training data.
Don't choose more ML compute instances for training than available S3 objects. If you do, some nodes won't get any data and you will pay for nodes that aren't getting any training data. This applies in both File and Pipe modes. Keep this in mind when developing algorithms.
In distributed training, where you use multiple ML compute EC2 instances, you might choose ShardedByS3Key. If the algorithm requires copying training data to the ML storage volume (when TrainingInputMode is set to File), this copies 1/n of the number of objects.
A list of one or more attribute names to use that are found in a specified augmented\n manifest file.
" + "smithy.api#documentation": "A list of one or more attribute names to use that are found in a specified augmented manifest file.
" } }, "InstanceGroupNames": { @@ -61554,7 +61549,7 @@ } }, "traits": { - "smithy.api#documentation": "Describes the S3 data source.
\nYour input bucket must be in the same Amazon Web Services region as your training\n job.
" + "smithy.api#documentation": "Describes the S3 data source.
Your input bucket must be in the same Amazon Web Services region as your training job.
" } }, "com.amazonaws.sagemaker#S3DataType": { @@ -61595,7 +61590,7 @@ "target": "com.amazonaws.sagemaker#S3ModelDataType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies the type of ML model data to deploy.
\nIf you choose S3Prefix, S3Uri identifies a key name prefix.\n SageMaker uses all objects that match the specified key name prefix as part of the ML model\n data to deploy. A valid key name prefix identified by S3Uri always ends\n with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is\n the ML model data to deploy.
Specifies the type of ML model data to deploy.
If you choose S3Prefix, S3Uri identifies a key name prefix. SageMaker uses all objects that match the specified key name prefix as part of the ML model data to deploy. A valid key name prefix identified by S3Uri always ends with a forward slash (/).
If you choose S3Object, S3Uri identifies an object that is the ML model data to deploy.
Specifies how the ML model data is prepared.
\nIf you choose Gzip and choose S3Object as the value of\n S3DataType, S3Uri identifies an object that is a\n gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during\n model deployment.
If you choose None and chooose S3Object as the value of\n S3DataType, S3Uri identifies an object that represents an\n uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of\n S3DataType, S3Uri identifies a key name prefix, under\n which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files\n under /opt/ml/model directory for use by your inference code:
\nIf you choose S3Object as the value of S3DataType,\n then SageMaker will split the key of the S3 object referenced by S3Uri\n by slash (/), and use the last part as the filename of the file holding the\n content of the S3 object.
If you choose S3Prefix as the value of S3DataType,\n then for each S3 object under the key name pefix referenced by\n S3Uri, SageMaker will trim its key by the prefix, and use the\n remainder as the path (relative to /opt/ml/model) of the file\n holding the content of the S3 object. SageMaker will split the remainder by slash\n (/), using intermediate parts as directory names and the last part as filename\n of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
\nAn empty or blank string
\nA string which contains null bytes
\nA string longer than 255 bytes
\nA single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if\n your uncompressed ML model consists of two S3 objects\n s3://mybucket/model/weights and\n s3://mybucket/model/weights/part1 and you specify\n s3://mybucket/model/ as the value of S3Uri and\n S3Prefix as the value of S3DataType, then it will\n result in name clash between /opt/ml/model/weights (a regular file)\n and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using\n folders. When you create a folder in S3 console, S3 creates a 0-byte\n object with a key set to the folder name you provide. They key of the 0-byte\n object ends with a slash (/) which violates SageMaker restrictions on model artifact\n file names, leading to model deployment failure.
\nSpecifies how the ML model data is prepared.
If you choose Gzip and choose S3Object as the value of S3DataType, S3Uri identifies an object that is a gzip-compressed TAR archive. SageMaker will attempt to decompress and untar the object during model deployment.
If you choose None and chooose S3Object as the value of S3DataType, S3Uri identifies an object that represents an uncompressed ML model to deploy.
If you choose None and choose S3Prefix as the value of S3DataType, S3Uri identifies a key name prefix, under which all objects represents the uncompressed ML model to deploy.
If you choose None, then SageMaker will follow rules below when creating model data files under /opt/ml/model directory for use by your inference code:
If you choose S3Object as the value of S3DataType, then SageMaker will split the key of the S3 object referenced by S3Uri by slash (/), and use the last part as the filename of the file holding the content of the S3 object.
If you choose S3Prefix as the value of S3DataType, then for each S3 object under the key name pefix referenced by S3Uri, SageMaker will trim its key by the prefix, and use the remainder as the path (relative to /opt/ml/model) of the file holding the content of the S3 object. SageMaker will split the remainder by slash (/), using intermediate parts as directory names and the last part as filename of the file holding the content of the S3 object.
Do not use any of the following as file names or directory names:
An empty or blank string
A string which contains null bytes
A string longer than 255 bytes
A single dot (.)
A double dot (..)
Ambiguous file names will result in model deployment failure. For example, if your uncompressed ML model consists of two S3 objects s3://mybucket/model/weights and s3://mybucket/model/weights/part1 and you specify s3://mybucket/model/ as the value of S3Uri and S3Prefix as the value of S3DataType, then it will result in name clash between /opt/ml/model/weights (a regular file) and /opt/ml/model/weights/ (a directory).
Do not organize the model artifacts in S3 console using folders. When you create a folder in S3 console, S3 creates a 0-byte object with a key set to the folder name you provide. They key of the 0-byte object ends with a slash (/) which violates SageMaker restrictions on model artifact file names, leading to model deployment failure.
Specifies the access configuration file for the ML model. You can explicitly accept the\n model end-user license agreement (EULA) within the ModelAccessConfig. You are\n responsible for reviewing and complying with any applicable license terms and making sure\n they are acceptable for your use case before downloading or using a model.
Specifies the access configuration file for the ML model. You can explicitly accept the model end-user license agreement (EULA) within the ModelAccessConfig. You are responsible for reviewing and complying with any applicable license terms and making sure they are acceptable for your use case before downloading or using a model.
The Amazon S3 URI of the manifest file. The manifest file is a CSV file that stores the\n artifact locations.
" + "smithy.api#documentation": "The Amazon S3 URI of the manifest file. The manifest file is a CSV file that stores the artifact locations.
" } }, "ETag": { @@ -61690,7 +61685,7 @@ } }, "traits": { - "smithy.api#documentation": "This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access.
To learn more about how custom templates are created, see Create custom worker task templates.
" + "smithy.api#documentation": "This object defines the access restrictions to Amazon S3 resources that are included in custom worker task templates using the Liquid filter, grant_read_access.
To learn more about how custom templates are created, see Create custom worker task templates.
" } }, "com.amazonaws.sagemaker#S3StorageConfig": { @@ -61700,14 +61695,14 @@ "target": "com.amazonaws.sagemaker#S3Uri", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following:\n s3://example-bucket/prefix/.
The S3 URI, or location in Amazon S3, of OfflineStore.
S3 URIs have a format similar to the following: s3://example-bucket/prefix/.
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt\n any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to\n CreateFeatureGroup must have below permissions to the\n KmsKeyId:
\n \"kms:GenerateDataKey\"\n
The Amazon Web Services Key Management Service (KMS) key ARN of the key used to encrypt any objects written into the OfflineStore S3 location.
The IAM roleARN that is passed as a parameter to CreateFeatureGroup must have below permissions to the KmsKeyId:
\"kms:GenerateDataKey\"
The Amazon Simple Storage (Amazon S3) location and security configuration for\n OfflineStore.
The Amazon Simple Storage (Amazon S3) location and security configuration for OfflineStore.
Provides APIs for creating and managing SageMaker resources.
\nOther Resources:
\nProvides APIs for creating and managing SageMaker resources.
Other Resources:
", "smithy.api#title": "Amazon SageMaker Service", "smithy.api#xmlNamespace": { "uri": "http://sagemaker.amazonaws.com/doc/2017-05-13/" @@ -63972,13 +63967,13 @@ "InvocationsPerInstance": { "target": "com.amazonaws.sagemaker#Integer", "traits": { - "smithy.api#documentation": "The number of invocations sent to a model, normalized by InstanceCount\n in each ProductionVariant. 1/numberOfInstances is sent as the value on each\n request, where numberOfInstances is the number of active instances for the\n ProductionVariant behind the endpoint at the time of the request.
The number of invocations sent to a model, normalized by InstanceCount in each ProductionVariant. 1/numberOfInstances is sent as the value on each request, where numberOfInstances is the number of active instances for the ProductionVariant behind the endpoint at the time of the request.
The interval of time taken by a model to respond as viewed from SageMaker.\n This interval includes the local communication times taken to send the request\n and to fetch the response from the container of a model and the time taken to\n complete the inference in the container.
" + "smithy.api#documentation": "The interval of time taken by a model to respond as viewed from SageMaker. This interval includes the local communication times taken to send the request and to fetch the response from the container of a model and the time taken to complete the inference in the container.
" } } }, @@ -64013,20 +64008,20 @@ "target": "com.amazonaws.sagemaker#ScheduleExpression", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A cron expression that describes details about the monitoring schedule.
\nThe supported cron expressions are:
\nIf you want to set the job to start every hour, use the following:
\n\n Hourly: cron(0 * ? * * *)\n
If you want to start the job daily:
\n\n cron(0 [00-23] ? * * *)\n
If you want to run the job one time, immediately, use the following\n keyword:
\n\n NOW\n
For example, the following are valid cron expressions:
\nDaily at noon UTC: cron(0 12 ? * * *)\n
Daily at midnight UTC: cron(0 0 ? * * *)\n
To support running every 6, 12 hours, the following are also supported:
\n\n cron(0 [00-23]/[01-24] ? * * *)\n
For example, the following are valid cron expressions:
\nEvery 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)\n
Every two hours starting at midnight: cron(0 0/2 ? * * *)\n
Even though the cron expression is set to start at 5PM UTC, note that there\n could be a delay of 0-20 minutes from the actual requested time to run the\n execution.
\nWe recommend that if you would like a daily schedule, you do not provide this\n parameter. Amazon SageMaker AI will pick a time for running every day.
\nYou can also specify the keyword NOW to run the monitoring job immediately,\n one time, without recurring.
A cron expression that describes details about the monitoring schedule.
The supported cron expressions are:
If you want to set the job to start every hour, use the following:
Hourly: cron(0 * ? * * *)
If you want to start the job daily:
cron(0 [00-23] ? * * *)
If you want to run the job one time, immediately, use the following keyword:
NOW
For example, the following are valid cron expressions:
Daily at noon UTC: cron(0 12 ? * * *)
Daily at midnight UTC: cron(0 0 ? * * *)
To support running every 6, 12 hours, the following are also supported:
cron(0 [00-23]/[01-24] ? * * *)
For example, the following are valid cron expressions:
Every 12 hours, starting at 5pm UTC: cron(0 17/12 ? * * *)
Every two hours starting at midnight: cron(0 0/2 ? * * *)
Even though the cron expression is set to start at 5PM UTC, note that there could be a delay of 0-20 minutes from the actual requested time to run the execution.
We recommend that if you would like a daily schedule, you do not provide this parameter. Amazon SageMaker AI will pick a time for running every day.
You can also specify the keyword NOW to run the monitoring job immediately, one time, without recurring.
Sets the start time for a monitoring job window. Express this time as an offset to the\n times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the\n ScheduleExpression parameter. Specify this offset in ISO 8601 duration\n format. For example, if you want to monitor the five hours of data in your dataset that\n precede the start of each monitoring job, you would specify: \"-PT5H\".
The start time that you specify must not precede the end time that you specify by more\n than 24 hours. You specify the end time with the DataAnalysisEndTime\n parameter.
If you set ScheduleExpression to NOW, this parameter is\n required.
Sets the start time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to monitor the five hours of data in your dataset that precede the start of each monitoring job, you would specify: \"-PT5H\".
The start time that you specify must not precede the end time that you specify by more than 24 hours. You specify the end time with the DataAnalysisEndTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
Sets the end time for a monitoring job window. Express this time as an offset to the\n times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the\n ScheduleExpression parameter. Specify this offset in ISO 8601 duration\n format. For example, if you want to end the window one hour before the start of each\n monitoring job, you would specify: \"-PT1H\".
The end time that you specify must not follow the start time that you specify by more\n than 24 hours. You specify the start time with the DataAnalysisStartTime\n parameter.
If you set ScheduleExpression to NOW, this parameter is\n required.
Sets the end time for a monitoring job window. Express this time as an offset to the times that you schedule your monitoring jobs to run. You schedule monitoring jobs with the ScheduleExpression parameter. Specify this offset in ISO 8601 duration format. For example, if you want to end the window one hour before the start of each monitoring job, you would specify: \"-PT1H\".
The end time that you specify must not follow the start time that you specify by more than 24 hours. You specify the start time with the DataAnalysisStartTime parameter.
If you set ScheduleExpression to NOW, this parameter is required.
List of the priority classes, PriorityClass, of the cluster policy. When\n specified, these class configurations define how tasks are queued.
List of the priority classes, PriorityClass, of the cluster policy. When specified, these class configurations define how tasks are queued.
When enabled, entities borrow idle compute based on their assigned\n FairShareWeight.
When disabled, entities borrow idle compute based on a first-come first-serve\n basis.
\nDefault is Enabled.
When enabled, entities borrow idle compute based on their assigned FairShareWeight.
When disabled, entities borrow idle compute based on a first-come first-serve basis.
Default is Enabled.
Cluster policy configuration. This policy is used for task prioritization and fair-share\n allocation. This helps prioritize critical workloads and distributes idle compute\n across entities.
" + "smithy.api#documentation": "Cluster policy configuration. This policy is used for task prioritization and fair-share allocation. This helps prioritize critical workloads and distributes idle compute across entities.
" } }, "com.amazonaws.sagemaker#SchedulerResourceStatus": { @@ -64210,7 +64205,7 @@ "target": "com.amazonaws.sagemaker#SearchResponse" }, "traits": { - "smithy.api#documentation": "Finds SageMaker resources that match a search query. Matching resources are returned as a list\n of SearchRecord objects in the response. You can sort the search results by any\n resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and\n timestamp.
\nThe Search API may provide access to otherwise restricted data. See Amazon SageMaker API\n Permissions: Actions, Permissions, and Resources Reference for more\n information.
\nFinds SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order.
You can query against the following value types: numeric, text, Boolean, and timestamp.
The Search API may provide access to otherwise restricted data. See Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference for more information.
A Boolean operator used to evaluate the search expression. If you want every conditional\n statement in all lists to be satisfied for the entire search expression to be true, specify\n And. If only a single conditional statement needs to be true for the entire\n search expression to be true, specify Or. The default value is\n And.
A Boolean operator used to evaluate the search expression. If you want every conditional statement in all lists to be satisfied for the entire search expression to be true, specify And. If only a single conditional statement needs to be true for the entire search expression to be true, specify Or. The default value is And.
A multi-expression that searches for the specified resource or resources in a search. All\n resource objects that satisfy the expression's condition are included in the search results.\n You must specify at least one subexpression, filter, or nested filter. A\n SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression\n comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of\n Boolean expressions using a list of resource properties. A nested filter is satisfied if a\n single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be\n nested in a list of search expression objects.
A Boolean operator: And or Or.
A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
A SearchExpression contains the following components:
A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.
A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.
A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.
A Boolean operator: And or Or.
A Boolean conditional statement. Resources must satisfy this condition to be included in\n search results. You must provide at least one subexpression, filter, or nested filter. The\n maximum number of recursive SubExpressions, NestedFilters, and\n Filters that can be included in a SearchExpression object is\n 50.
A Boolean conditional statement. Resources must satisfy this condition to be included in search results. You must provide at least one subexpression, filter, or nested filter. The maximum number of recursive SubExpressions, NestedFilters, and Filters that can be included in a SearchExpression object is 50.
The name of the resource property used to sort the SearchResults. The default\n is LastModifiedTime.
The name of the resource property used to sort the SearchResults. The default is LastModifiedTime.
How SearchResults are ordered. Valid values are Ascending or\n Descending. The default is Descending.
How SearchResults are ordered. Valid values are Ascending or Descending. The default is Descending.
If more than MaxResults resources match the specified\n SearchExpression, the response includes a NextToken. The\n NextToken can be passed to the next SearchRequest to continue\n retrieving results.
If more than MaxResults resources match the specified SearchExpression, the response includes a NextToken. The NextToken can be passed to the next SearchRequest to continue retrieving results.
A cross account filter option. When the value is \"CrossAccount\" the search\n results will only include resources made discoverable to you from other accounts. When the\n value is \"SameAccount\" or null the search results will only include\n resources from your account. Default is null. For more information on searching\n for resources made discoverable to your account, see Search\n discoverable resources in the SageMaker Developer Guide. The maximum number of\n ResourceCatalogs viewable is 1000.
A cross account filter option. When the value is \"CrossAccount\" the search results will only include resources made discoverable to you from other accounts. When the value is \"SameAccount\" or null the search results will only include resources from your account. Default is null. For more information on searching for resources made discoverable to your account, see Search discoverable resources in the SageMaker Developer Guide. The maximum number of ResourceCatalogs viewable is 1000.
If the result of the previous Search request was truncated, the response\n includes a NextToken. To retrieve the next set of results, use the token in the next\n request.
If the result of the previous Search request was truncated, the response includes a NextToken. To retrieve the next set of results, use the token in the next request.
Searches for available training plan offerings based on specified criteria.
\nUsers search for available plan offerings based on their requirements (e.g.,\n instance type, count, start time, duration).
\nAnd then, they create a plan that best matches their needs using the ID of the\n plan offering they want to use.
\nFor more information about how to reserve GPU capacity for your SageMaker training jobs or\n SageMaker HyperPod clusters using Amazon SageMaker Training Plan , see \n CreateTrainingPlan\n .
Searches for available training plan offerings based on specified criteria.
Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration).
And then, they create a plan that best matches their needs using the ID of the plan offering they want to use.
For more information about how to reserve GPU capacity for your SageMaker training jobs or SageMaker HyperPod clusters using Amazon SageMaker Training Plan , see CreateTrainingPlan .
The type of instance you want to search for in the available training plan offerings.\n This field allows you to filter the search results based on the specific compute resources\n you require for your SageMaker training jobs or SageMaker HyperPod clusters. When searching for training\n plan offerings, specifying the instance type helps you find Reserved Instances that match\n your computational needs.
" + "smithy.api#documentation": "The type of instance you want to search for in the available training plan offerings. This field allows you to filter the search results based on the specific compute resources you require for your SageMaker training jobs or SageMaker HyperPod clusters. When searching for training plan offerings, specifying the instance type helps you find Reserved Instances that match your computational needs.
" } }, "InstanceCount": { "target": "com.amazonaws.sagemaker#ReservedCapacityInstanceCount", "traits": { - "smithy.api#documentation": "The number of instances you want to reserve in the training plan offerings. This allows\n you to specify the quantity of compute resources needed for your SageMaker training jobs or\n SageMaker HyperPod clusters, helping you find reserved capacity offerings that match your\n requirements.
" + "smithy.api#documentation": "The number of instances you want to reserve in the training plan offerings. This allows you to specify the quantity of compute resources needed for your SageMaker training jobs or SageMaker HyperPod clusters, helping you find reserved capacity offerings that match your requirements.
" } }, "StartTimeAfter": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter to search for training plan offerings with a start time after a specified\n date.
" + "smithy.api#documentation": "A filter to search for training plan offerings with a start time after a specified date.
" } }, "EndTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A filter to search for reserved capacity offerings with an end time before a specified\n date.
" + "smithy.api#documentation": "A filter to search for reserved capacity offerings with an end time before a specified date.
" } }, "DurationHours": { @@ -64503,7 +64498,7 @@ "target": "com.amazonaws.sagemaker#SageMakerResourceNames", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) to search for in the\n offerings.
\nTraining plans are specific to their target resource.
\nA training plan designed for SageMaker training jobs can only be used to schedule and\n run training jobs.
\nA training plan for HyperPod clusters can be used exclusively to provide\n compute resources to a cluster's instance group.
\nThe target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) to search for in the offerings.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
Contains a secondary status information from a training\n job.
\nStatus might be one of the following secondary statuses:
\n\n Starting\n - Starting the training job.
\n Downloading - An optional stage for algorithms that\n support File training input mode. It indicates that\n data is being downloaded to the ML storage volumes.
\n Training - Training is in progress.
\n Uploading - Training is complete and the model\n artifacts are being uploaded to the S3 location.
\n Completed - The training job has completed.
\n Failed - The training job has failed. The reason for\n the failure is returned in the FailureReason field of\n DescribeTrainingJobResponse.
\n MaxRuntimeExceeded - The job stopped because it\n exceeded the maximum allowed runtime.
\n Stopped - The training job has stopped.
\n Stopping - Stopping the training job.
We no longer support the following secondary statuses:
\n\n LaunchingMLInstances\n
\n PreparingTrainingStack\n
\n DownloadingTrainingImage\n
Contains a secondary status information from a training job.
Status might be one of the following secondary statuses:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
A timestamp that shows when the training job transitioned to the current secondary\n status state.
", + "smithy.api#documentation": "A timestamp that shows when the training job transitioned to the current secondary status state.
", "smithy.api#required": {} } }, "EndTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A timestamp that shows when the training job transitioned out of this secondary status\n state into another secondary status state or when the training job has ended.
" + "smithy.api#documentation": "A timestamp that shows when the training job transitioned out of this secondary status state into another secondary status state or when the training job has ended.
" } }, "StatusMessage": { "target": "com.amazonaws.sagemaker#StatusMessage", "traits": { - "smithy.api#documentation": "A detailed description of the progress within a secondary status.\n
\nSageMaker provides secondary statuses and status messages that apply to each of\n them:
\nStarting the training job.
\nLaunching requested ML\n instances.
\nInsufficient\n capacity error from EC2 while launching instances,\n retrying!
\nLaunched\n instance was unhealthy, replacing it!
\nPreparing the instances for training.
\nTraining\n image download completed. Training in\n progress.
\nStatus messages are subject to change. Therefore, we recommend not including them\n in code that programmatically initiates actions. For examples, don't use status\n messages in if statements.
\nTo have an overview of your training job's progress, view\n TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example,\n at the start of a training job, you might see the following:
\n TrainingJobStatus - InProgress
\n SecondaryStatus - Training
\n StatusMessage - Downloading the training image
A detailed description of the progress within a secondary status.
SageMaker provides secondary statuses and status messages that apply to each of them:
Starting the training job.
Launching requested ML instances.
Insufficient capacity error from EC2 while launching instances, retrying!
Launched instance was unhealthy, replacing it!
Preparing the instances for training.
Training image download completed. Training in progress.
Status messages are subject to change. Therefore, we recommend not including them in code that programmatically initiates actions. For examples, don't use status messages in if statements.
To have an overview of your training job's progress, view TrainingJobStatus and SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example, at the start of a training job, you might see the following:
TrainingJobStatus - InProgress
SecondaryStatus - Training
StatusMessage - Downloading the training image
An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the\n training job has transitioned through. A training job can be in one of several states,\n for example, starting, downloading, training, or uploading. Within each state, there are\n a number of intermediate states. For example, within the starting state, SageMaker could be\n starting the training job or launching the ML instances. These transitional states are\n referred to as the job's secondary\n status.\n
An array element of SecondaryStatusTransitions for DescribeTrainingJob. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job's secondary status.
The ARN from a reference execution of the current pipeline. \n Used to copy input collaterals needed for the selected steps to run.\n The execution status of the pipeline can be either Failed\n or Success.
This field is required if the steps you specify for\n SelectedSteps depend on output collaterals from any non-specified pipeline\n steps. For more information, see Selective\n Execution for Pipeline Steps.
The ARN from a reference execution of the current pipeline. Used to copy input collaterals needed for the selected steps to run. The execution status of the pipeline can be either Failed or Success.
This field is required if the steps you specify for SelectedSteps depend on output collaterals from any non-specified pipeline steps. For more information, see Selective Execution for Pipeline Steps.
A list of pipeline steps to run. All step(s) in all path(s) between\n two selected steps should be included.
", + "smithy.api#documentation": "A list of pipeline steps to run. All step(s) in all path(s) between two selected steps should be included.
", "smithy.api#required": {} } } @@ -64796,7 +64791,7 @@ } ], "traits": { - "smithy.api#documentation": "Notifies the pipeline that the execution of a callback step failed, along with a\n message describing why. When a callback step is run, the pipeline generates a callback\n token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
" + "smithy.api#documentation": "Notifies the pipeline that the execution of a callback step failed, along with a message describing why. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
" } }, "com.amazonaws.sagemaker#SendPipelineExecutionStepFailureRequest": { @@ -64819,7 +64814,7 @@ "ClientRequestToken": { "target": "com.amazonaws.sagemaker#IdempotencyToken", "traits": { - "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than one time.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
", "smithy.api#idempotencyToken": {} } } @@ -64862,7 +64857,7 @@ } ], "traits": { - "smithy.api#documentation": "Notifies the pipeline that the execution of a callback step succeeded and provides a\n list of the step's output parameters. When a callback step is run, the pipeline generates\n a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
" + "smithy.api#documentation": "Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters. When a callback step is run, the pipeline generates a callback token and includes the token in a message sent to Amazon Simple Queue Service (Amazon SQS).
" } }, "com.amazonaws.sagemaker#SendPipelineExecutionStepSuccessRequest": { @@ -64885,7 +64880,7 @@ "ClientRequestToken": { "target": "com.amazonaws.sagemaker#IdempotencyToken", "traits": { - "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than one time.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than one time.
", "smithy.api#idempotencyToken": {} } } @@ -64957,12 +64952,12 @@ "ProvisionedProductStatusMessage": { "target": "com.amazonaws.sagemaker#ProvisionedProductStatusMessage", "traits": { - "smithy.api#documentation": "The current status of the product.
\n\n AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
\n UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
\n TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
\n ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
\n PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
The current status of the product.
AVAILABLE - Stable state, ready to perform any operation. The most recent operation succeeded and completed.
UNDER_CHANGE - Transitive state. Operations performed might not have valid results. Wait for an AVAILABLE status before performing operations.
TAINTED - Stable state, ready to perform any operation. The stack has completed the requested operation but is not exactly what was requested. For example, a request to update to a new version failed and the stack rolled back to the current version.
ERROR - An unexpected error occurred. The provisioned product exists but the stack is not running. For example, CloudFormation received a parameter value that was not valid and could not launch the stack.
PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to provision a new product, but resources have not yet been created. After reviewing the list of resources to be created, execute the plan. Wait for an AVAILABLE status before performing operations.
Details of a provisioned service catalog product. For information about service catalog,\n see What is Amazon Web Services Service\n Catalog.
" + "smithy.api#documentation": "Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
" } }, "com.amazonaws.sagemaker#ServiceCatalogProvisioningDetails": { @@ -64996,7 +64991,7 @@ } }, "traits": { - "smithy.api#documentation": "Details that you specify to provision a service catalog product. For information about\n service catalog, see What is Amazon Web Services Service\n Catalog.
" + "smithy.api#documentation": "Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
" } }, "com.amazonaws.sagemaker#ServiceCatalogProvisioningUpdateDetails": { @@ -65016,7 +65011,7 @@ } }, "traits": { - "smithy.api#documentation": "Details that you specify to provision a service catalog product. \n For information about service catalog, see What is Amazon Web Services Service Catalog.\n
" + "smithy.api#documentation": "Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog.
" } }, "com.amazonaws.sagemaker#SessionChainingConfig": { @@ -65025,12 +65020,12 @@ "EnableSessionTagChaining": { "target": "com.amazonaws.sagemaker#EnableSessionTagChaining", "traits": { - "smithy.api#documentation": "Set to True to allow SageMaker to extract session tags from a training job\n creation role and reuse these tags when assuming the training job execution role.
Set to True to allow SageMaker to extract session tags from a training job creation role and reuse these tags when assuming the training job execution role.
Contains information about attribute-based access control (ABAC) for a training job.\n The session chaining configuration uses Amazon Security Token Service (STS) for your training job to\n request temporary, limited-privilege credentials to tenants. For more information, see\n Attribute-based access control (ABAC) for multi-tenancy training.
" + "smithy.api#documentation": "Contains information about attribute-based access control (ABAC) for a training job. The session chaining configuration uses Amazon Security Token Service (STS) for your training job to request temporary, limited-privilege credentials to tenants. For more information, see Attribute-based access control (ABAC) for multi-tenancy training.
" } }, "com.amazonaws.sagemaker#SessionExpirationDurationInSeconds": { @@ -65049,7 +65044,7 @@ "target": "com.amazonaws.sagemaker#ModelVariantName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "\n The name of the production variant, which takes all the inference requests.\n
", + "smithy.api#documentation": "The name of the production variant, which takes all the inference requests.
", "smithy.api#required": {} } }, @@ -65063,7 +65058,7 @@ } }, "traits": { - "smithy.api#documentation": "\n The configuration of ShadowMode inference experiment type, which specifies a production variant\n to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the\n inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.\n
The configuration of ShadowMode inference experiment type, which specifies a production variant to take all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also specifies the percentage of requests that Amazon SageMaker replicates.
\n The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.\n
", + "smithy.api#documentation": "The percentage of inference requests that Amazon SageMaker replicates from the production variant to the shadow variant.
", "smithy.api#required": {} } } @@ -65108,24 +65103,24 @@ "NotebookOutputOption": { "target": "com.amazonaws.sagemaker#NotebookOutputOption", "traits": { - "smithy.api#documentation": "Whether to include the notebook cell output when sharing the notebook. The default is\n Disabled.
Whether to include the notebook cell output when sharing the notebook. The default is Disabled.
When NotebookOutputOption is Allowed, the Amazon S3\n bucket used to store the shared notebook snapshots.
When NotebookOutputOption is Allowed, the Amazon S3 bucket used to store the shared notebook snapshots.
When NotebookOutputOption is Allowed, the Amazon Web Services Key\n Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the\n Amazon S3 bucket.
When NotebookOutputOption is Allowed, the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.
Specifies options for sharing Amazon SageMaker AI Studio notebooks. These settings are\n specified as part of DefaultUserSettings when the CreateDomain API\n is called, and as part of UserSettings when the CreateUserProfile\n API is called. When SharingSettings is not specified, notebook sharing isn't\n allowed.
Specifies options for sharing Amazon SageMaker AI Studio notebooks. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called. When SharingSettings is not specified, notebook sharing isn't allowed.
A configuration for a shuffle option for input data in a channel. If you use\n S3Prefix for S3DataType, the results of the S3 key prefix\n matches are shuffled. If you use ManifestFile, the order of the S3 object\n references in the ManifestFile is shuffled. If you use\n AugmentedManifestFile, the order of the JSON lines in the\n AugmentedManifestFile is shuffled. The shuffling order is determined\n using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at\n the start of every epoch. With large datasets, this ensures that the order of the\n training data is different for each epoch, and it helps reduce bias and possible\n overfitting. In a multi-node training job when ShuffleConfig is combined\n with S3DataDistributionType of ShardedByS3Key, the data is\n shuffled across nodes so that the content sent to a particular node on the first epoch\n might be sent to a different node on the second epoch.
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
For Pipe input mode, when ShuffleConfig is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.
The Amazon S3 path where the model artifacts, which result from model training, are stored.\n This path must point to a single gzip compressed tar archive\n (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services\n region as the algorithm.
\nThe Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
The model artifacts must be in an S3 bucket that is in the same Amazon Web Services region as the algorithm.
The name of an algorithm that was used to create the model package. The algorithm must\n be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
", + "smithy.api#documentation": "The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies an algorithm that was used to create the model package. The algorithm must\n be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
" + "smithy.api#documentation": "Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in Amazon Web Services Marketplace that you are subscribed to.
" } }, "com.amazonaws.sagemaker#SourceAlgorithmList": { @@ -65589,13 +65584,13 @@ "target": "com.amazonaws.sagemaker#Cidrs", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of one to ten Classless Inter-Domain Routing (CIDR) values.
\nMaximum: Ten CIDR values
\nThe following Length Constraints apply to individual CIDR values in\n the CIDR value list.
\nA list of one to ten Classless Inter-Domain Routing (CIDR) values.
Maximum: Ten CIDR values
The following Length Constraints apply to individual CIDR values in the CIDR value list.
A list of IP address ranges (CIDRs). Used to create an allow\n list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an\n IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
" + "smithy.api#documentation": "A list of IP address ranges (CIDRs). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to log in to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.
" } }, "com.amazonaws.sagemaker#SourceType": { @@ -65628,7 +65623,7 @@ } }, "traits": { - "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio\n applications in a space.
" + "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of Amazon SageMaker Studio applications in a space.
" } }, "com.amazonaws.sagemaker#SpaceArn": { @@ -65650,7 +65645,7 @@ "AppLifecycleManagement": { "target": "com.amazonaws.sagemaker#SpaceAppLifecycleManagement", "traits": { - "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of CodeEditor applications in\n a space.
" + "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of CodeEditor applications in a space.
" } } }, @@ -65735,7 +65730,7 @@ "IdleTimeoutInMinutes": { "target": "com.amazonaws.sagemaker#IdleTimeoutInMinutes", "traits": { - "smithy.api#documentation": "The time that SageMaker waits after the application becomes idle before shutting it\n down.
" + "smithy.api#documentation": "The time that SageMaker waits after the application becomes idle before shutting it down.
" } } }, @@ -65758,7 +65753,7 @@ "AppLifecycleManagement": { "target": "com.amazonaws.sagemaker#SpaceAppLifecycleManagement", "traits": { - "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of JupyterLab applications in\n a space.
" + "smithy.api#documentation": "Settings that are used to configure and manage the lifecycle of JupyterLab applications in a space.
" } } }, @@ -65806,7 +65801,7 @@ "AppType": { "target": "com.amazonaws.sagemaker#AppType", "traits": { - "smithy.api#documentation": "The type of app created within the space.
\nIf using the \n UpdateSpace API, you can't change the app type of your\n space by specifying a different value for this field.
" + "smithy.api#documentation": "The type of app created within the space.
If using the UpdateSpace API, you can't change the app type of your space by specifying a different value for this field.
" } }, "SpaceStorageSettings": { @@ -65818,13 +65813,13 @@ "SpaceManagedResources": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "If you enable this option, SageMaker AI creates the following resources on your\n behalf when you create the space:
\nThe user profile that possesses the space.
\nThe app that the space contains.
\nIf you enable this option, SageMaker AI creates the following resources on your behalf when you create the space:
The user profile that possesses the space.
The app that the space contains.
A file system, created by you, that you assign to a space for an Amazon SageMaker AI\n Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" + "smithy.api#documentation": "A file system, created by you, that you assign to a space for an Amazon SageMaker AI Domain. Permitted users can access this file system in Amazon SageMaker AI Studio.
" } } }, @@ -66083,7 +66078,7 @@ } }, "traits": { - "smithy.api#documentation": "Defines the stairs traffic pattern for an Inference Recommender load test. This pattern\n type consists of multiple steps where the number of users increases at each step.
\nSpecify either the stairs or phases traffic pattern.
" + "smithy.api#documentation": "Defines the stairs traffic pattern for an Inference Recommender load test. This pattern type consists of multiple steps where the number of users increases at each step.
Specify either the stairs or phases traffic pattern.
" } }, "com.amazonaws.sagemaker#StartEdgeDeploymentStage": { @@ -66238,7 +66233,7 @@ } ], "traits": { - "smithy.api#documentation": "Starts a previously stopped monitoring schedule.
\nBy default, when you successfully create a new schedule, the status of a monitoring\n schedule is scheduled.
Starts a previously stopped monitoring schedule.
By default, when you successfully create a new schedule, the status of a monitoring schedule is scheduled.
Launches an ML compute instance with the latest version of the libraries and\n attaches your ML storage volume. After configuring the notebook instance, SageMaker AI sets the notebook instance status to InService. A notebook\n instance's status must be InService before you can connect to your Jupyter\n notebook.
Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, SageMaker AI sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.
A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than once.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -66354,7 +66349,7 @@ "ParallelismConfiguration": { "target": "com.amazonaws.sagemaker#ParallelismConfiguration", "traits": { - "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration \n of the parent pipeline for this specific run.
" + "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
" } }, "SelectiveExecutionConfig": { @@ -66548,7 +66543,7 @@ } ], "traits": { - "smithy.api#documentation": "Stops a model compilation job.
\nTo stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal. This gracefully shuts the\n job down. If the job hasn't stopped, it sends the SIGKILL signal.
\nWhen it receives a StopCompilationJob request, Amazon SageMaker AI changes the\n CompilationJobStatus of the job to Stopping. After Amazon\n SageMaker stops the job, it sets the CompilationJobStatus to\n Stopped.
Stops a model compilation job.
To stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal.
When it receives a StopCompilationJob request, Amazon SageMaker AI changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobStatus to Stopped.
Stops a running hyperparameter tuning job and all running training jobs that the\n tuning job launched.
\nAll model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All\n data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the\n tuning job moves to the Stopped state, it releases all\n reserved\n resources for the tuning job.
Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.
\n Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:\n
\n\n Promote - Promote the shadow variant to a production variant
\n Remove - Delete the variant
\n Retain - Keep the variant as it is
Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:
Promote - Promote the shadow variant to a production variant
Remove - Delete the variant
Retain - Keep the variant as it is
\n An array of ModelVariantConfig objects. There is one for each variant that you want to deploy\n after the inference experiment stops. Each ModelVariantConfig describes the infrastructure\n configuration for deploying the corresponding variant.\n
An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.
\n The desired state of the experiment after stopping. The possible states are the following:\n
\n\n Completed: The experiment completed successfully
\n Cancelled: The experiment was canceled
The desired state of the experiment after stopping. The possible states are the following:
Completed: The experiment completed successfully
Cancelled: The experiment was canceled
Stops a running labeling job. A job that is stopped cannot be restarted. Any results\n obtained before the job is stopped are placed in the Amazon S3 output bucket.
" + "smithy.api#documentation": "Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.
" } }, "com.amazonaws.sagemaker#StopLabelingJobRequest": { @@ -66900,7 +66895,7 @@ "target": "smithy.api#Unit" }, "traits": { - "smithy.api#documentation": "Terminates the ML compute instance. Before terminating the instance, SageMaker AI disconnects the ML storage volume from it. SageMaker AI preserves the\n ML storage volume. SageMaker AI stops charging you for the ML compute instance when\n you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been\n terminated, call the StartNotebookInstance API.\n StartNotebookInstance launches another ML compute instance, configures\n it, and attaches the preserved ML storage volume so you can continue your work.\n
Terminates the ML compute instance. Before terminating the instance, SageMaker AI disconnects the ML storage volume from it. SageMaker AI preserves the ML storage volume. SageMaker AI stops charging you for the ML compute instance when you call StopNotebookInstance.
To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.
Stops a pipeline execution.
\n\n Callback Step\n
\nA pipeline execution won't stop while a callback step is running.\n When you call StopPipelineExecution\n on a pipeline execution with a running callback step, SageMaker Pipelines sends an\n additional Amazon SQS message to the specified SQS queue. The body of the SQS message\n contains a \"Status\" field which is set to \"Stopping\".
You should add logic to your Amazon SQS message consumer to take any needed action (for\n example, resource cleanup) upon receipt of the message followed by a call to\n SendPipelineExecutionStepSuccess or\n SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
\n\n Lambda Step\n
\nA pipeline execution can't be stopped while a lambda step is running because the Lambda\n function invoked by the lambda step can't be stopped. If you attempt to stop the execution\n while the Lambda function is running, the pipeline waits for the Lambda function to finish\n or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function\n finishes, the pipeline execution status is Stopped. If the timeout is hit\n the pipeline execution status is Failed.
Stops a pipeline execution.
Callback Step
A pipeline execution won't stop while a callback step is running. When you call StopPipelineExecution on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a \"Status\" field which is set to \"Stopping\".
You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to SendPipelineExecutionStepSuccess or SendPipelineExecutionStepFailure.
Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can't be stopped while a lambda step is running because the Lambda function invoked by the lambda step can't be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is Stopped. If the timeout is hit the pipeline execution status is Failed.
A unique, case-sensitive identifier that you provide to ensure the idempotency of the\n operation. An idempotent operation completes no more than once.
", + "smithy.api#documentation": "A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
", "smithy.api#idempotencyToken": {}, "smithy.api#required": {} } @@ -67058,7 +67053,7 @@ } ], "traits": { - "smithy.api#documentation": "Stops a training job. To stop a job, SageMaker sends the algorithm the\n SIGTERM signal, which delays job termination for 120 seconds.\n Algorithms might use this 120-second window to save the model artifacts, so the results\n of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of\n the job to Stopping. After SageMaker stops the job, it sets the status to\n Stopped.
Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of the job to Stopping. After SageMaker stops the job, it sets the status to Stopped.
Stops a batch transform job.
\nWhen Amazon SageMaker receives a StopTransformJob request, the status of the job\n changes to Stopping. After Amazon SageMaker\n stops\n the job, the status is set to Stopped. When you stop a batch transform job before\n it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
Stops a batch transform job.
When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a batch transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.
The maximum length of time, in seconds, that a training or compilation job can run\n before it is stopped.
\nFor compilation jobs, if the job does not complete during this time, a\n TimeOut error is generated. We recommend starting with 900 seconds and\n increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job.\n When RetryStrategy is specified in the job request,\n MaxRuntimeInSeconds specifies the maximum time for all of the attempts\n in total, not each individual attempt. The default value is 1 day. The maximum value is\n 28 days.
The maximum time that a TrainingJob can run in total, including any time\n spent publishing metrics or archiving and uploading models after it has been stopped, is\n 30 days.
The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend starting with 900 seconds and increasing as necessary based on your model.
For all other jobs, if the job does not complete during this time, SageMaker ends the job. When RetryStrategy is specified in the job request, MaxRuntimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days.
The maximum time that a TrainingJob can run in total, including any time spent publishing metrics or archiving and uploading models after it has been stopped, is 30 days.
The maximum length of time, in seconds, that a managed Spot training job has to\n complete. It is the amount of time spent waiting for Spot capacity plus the amount of\n time the job can run. It must be equal to or greater than\n MaxRuntimeInSeconds. If the job does not complete during this time,\n SageMaker ends the job.
When RetryStrategy is specified in the job request,\n MaxWaitTimeInSeconds specifies the maximum time for all of the attempts\n in total, not each individual attempt.
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job.
When RetryStrategy is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in total, not each individual attempt.
The maximum length of time, in seconds, that a training or compilation job can be\n pending before it is stopped.
\nWhen working with training jobs that use capacity from training\n plans, not all Pending job states count against the\n MaxPendingTimeInSeconds limit. The following scenarios do not\n increment the MaxPendingTimeInSeconds counter:
The plan is in a Scheduled state: Jobs queued (in\n Pending status) before a plan's start date (waiting for\n scheduled start time)
Between capacity reservations: Jobs temporarily back to\n Pending status between two capacity reservation\n periods
\n MaxPendingTimeInSeconds only increments when jobs are actively\n waiting for capacity in an Active plan.
The maximum length of time, in seconds, that a training or compilation job can be pending before it is stopped.
When working with training jobs that use capacity from training plans, not all Pending job states count against the MaxPendingTimeInSeconds limit. The following scenarios do not increment the MaxPendingTimeInSeconds counter:
The plan is in a Scheduled state: Jobs queued (in Pending status) before a plan's start date (waiting for scheduled start time)
Between capacity reservations: Jobs temporarily back to Pending status between two capacity reservation periods
MaxPendingTimeInSeconds only increments when jobs are actively waiting for capacity in an Active plan.
Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker\n ends the job. Use this API to cap costs.
\nTo stop a training job, SageMaker sends the algorithm the SIGTERM signal,\n which delays job termination for 120 seconds. Algorithms can use this 120-second window\n to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results\n of a model training job when possible. This attempt to save artifacts is only a best\n effort case as model might not be in a state from which it can be saved. For example, if\n training has just started, the model might not be ready to save. When saved, this\n intermediate data is a valid model artifact. You can use it to create a model with\n CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model\n artifacts. When training NTMs, make sure that the maximum runtime is sufficient for\n the training job to complete.
\nSpecifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.
To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel.
The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle\n Configurations are immutable.
" + "smithy.api#documentation": "This value is equivalent to CreationTime because Amazon SageMaker AI Studio Lifecycle Configurations are immutable.
" } }, "StudioLifecycleConfigAppType": { @@ -67403,7 +67398,7 @@ "HiddenAppTypes": { "target": "com.amazonaws.sagemaker#HiddenAppTypesList", "traits": { - "smithy.api#documentation": "The Applications supported in Studio that are hidden from the Studio left navigation\n pane.
" + "smithy.api#documentation": "The Applications supported in Studio that are hidden from the Studio left navigation pane.
" } }, "HiddenInstanceTypes": { @@ -67420,7 +67415,7 @@ } }, "traits": { - "smithy.api#documentation": "Studio settings. If these settings are applied on a user level, they take priority over\n the settings applied on a domain level.
" + "smithy.api#documentation": "Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
" } }, "com.amazonaws.sagemaker#SubnetId": { @@ -67500,22 +67495,12 @@ "PropertyNameQuery": { "target": "com.amazonaws.sagemaker#PropertyNameQuery", "traits": { - "smithy.api#documentation": "Defines a property name hint. Only property names that begin with the specified hint are\n included in the response.
" + "smithy.api#documentation": "Defines a property name hint. Only property names that begin with the specified hint are included in the response.
" } } }, "traits": { - "smithy.api#documentation": "Specified in the GetSearchSuggestions request. Limits the property names that are included in the\n response.
" - } - }, - "com.amazonaws.sagemaker#SynthesizedJsonHumanLoopActivationConditions": { - "type": "string", - "traits": { - "smithy.api#length": { - "min": 0, - "max": 10240 - }, - "smithy.api#mediaType": "application/json" + "smithy.api#documentation": "Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
" } }, "com.amazonaws.sagemaker#TableFormat": { @@ -67566,39 +67551,39 @@ "FeatureSpecificationS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "A URL to the Amazon S3 data source containing selected features from the input\n data source to run an Autopilot job V2. You can input FeatureAttributeNames\n (optional) in JSON format as shown below:
\n { \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown\n below:
\n\n { \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }\n
These column keys may not include the target column.
\nIn ensembling mode, Autopilot only supports the following data types: numeric,\n categorical, text, and datetime. In HPO mode,\n Autopilot can support numeric, categorical, text,\n datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1,\n col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are\n provided, then the column keys should be a subset of the column names provided in\n FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in\n [\"col1\", \"col2\", ...] are case sensitive and should be a list of strings\n containing unique values that are a subset of the column names in the input data. The list\n of columns provided must not include the target column.
A URL to the Amazon S3 data source containing selected features from the input data source to run an Autopilot job V2. You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }
These column keys may not include the target column.
In ensembling mode, Autopilot only supports the following data types: numeric, categorical, text, and datetime. In HPO mode, Autopilot can support numeric, categorical, text, datetime, and sequence.
If only FeatureDataTypes is provided, the column keys (col1, col2,..) should be a subset of the column names in the input data.
If both FeatureDataTypes and FeatureAttributeNames are provided, then the column keys should be a subset of the column names provided in FeatureAttributeNames.
The key name FeatureAttributeNames is fixed. The values listed in [\"col1\", \"col2\", ...] are case sensitive and should be a list of strings containing unique values that are a subset of the column names in the input data. The list of columns provided must not include the target column.
The method that Autopilot uses to train the data. You can either specify the mode manually\n or let Autopilot choose for you based on the dataset size by selecting AUTO. In\n AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than\n 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict\n classification and regression tasks directly from your dataset. This machine learning mode\n combines several base models to produce an optimal predictive model. It then uses a\n stacking ensemble method to combine predictions from contributing members. A multi-stack\n ensemble model can provide better performance over a single model by combining the\n predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by\n ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train\n the best version of a model. HPO automatically selects an algorithm for the type of problem\n you want to solve. Then HPO finds the best hyperparameters according to your objective\n metric. See Autopilot algorithm support for a list of algorithms supported by\n HYPERPARAMETER_TUNING mode.
The method that Autopilot uses to train the data. You can either specify the mode manually or let Autopilot choose for you based on the dataset size by selecting AUTO. In AUTO mode, Autopilot chooses ENSEMBLING for datasets smaller than 100 MB, and HYPERPARAMETER_TUNING for larger ones.
The ENSEMBLING mode uses a multi-stack ensemble model to predict classification and regression tasks directly from your dataset. This machine learning mode combines several base models to produce an optimal predictive model. It then uses a stacking ensemble method to combine predictions from contributing members. A multi-stack ensemble model can provide better performance over a single model by combining the predictive capabilities of multiple models. See Autopilot algorithm support for a list of algorithms supported by ENSEMBLING mode.
The HYPERPARAMETER_TUNING (HPO) mode uses the best hyperparameters to train the best version of a model. HPO automatically selects an algorithm for the type of problem you want to solve. Then HPO finds the best hyperparameters according to your objective metric. See Autopilot algorithm support for a list of algorithms supported by HYPERPARAMETER_TUNING mode.
Generates possible candidates without training the models. A model candidate is a\n combination of data preprocessors, algorithms, and algorithm parameter settings.
" + "smithy.api#documentation": "Generates possible candidates without training the models. A model candidate is a combination of data preprocessors, algorithms, and algorithm parameter settings.
" } }, "ProblemType": { "target": "com.amazonaws.sagemaker#ProblemType", "traits": { - "smithy.api#documentation": "The type of supervised learning problem available for the model candidates of the AutoML\n job V2. For more information, see \n SageMaker Autopilot problem types.
\nYou must either specify the type of supervised learning problem in\n ProblemType and provide the AutoMLJobObjective metric, or none at all.
The type of supervised learning problem available for the model candidates of the AutoML job V2. For more information, see SageMaker Autopilot problem types.
You must either specify the type of supervised learning problem in ProblemType and provide the AutoMLJobObjective metric, or none at all.
The name of the target variable in supervised learning, usually represented by\n 'y'.
", + "smithy.api#documentation": "The name of the target variable in supervised learning, usually represented by 'y'.
", "smithy.api#required": {} } }, "SampleWeightAttributeName": { "target": "com.amazonaws.sagemaker#SampleWeightAttributeName", "traits": { - "smithy.api#documentation": "If specified, this column name indicates which column of the dataset should be treated\n as sample weights for use by the objective metric during the training, evaluation, and the\n selection of the best model. This column is not considered as a predictive feature. For\n more information on Autopilot metrics, see Metrics and\n validation.
\nSample weights should be numeric, non-negative, with larger values indicating which rows\n are more important than others. Data points that have invalid or no weight value are\n excluded.
\nSupport for sample weights is available in Ensembling\n mode only.
" + "smithy.api#documentation": "If specified, this column name indicates which column of the dataset should be treated as sample weights for use by the objective metric during the training, evaluation, and the selection of the best model. This column is not considered as a predictive feature. For more information on Autopilot metrics, see Metrics and validation.
Sample weights should be numeric, non-negative, with larger values indicating which rows are more important than others. Data points that have invalid or no weight value are excluded.
Support for sample weights is available in Ensembling mode only.
" } } }, @@ -67612,7 +67597,7 @@ "ProblemType": { "target": "com.amazonaws.sagemaker#ProblemType", "traits": { - "smithy.api#documentation": "The type of supervised learning problem available for the model candidates of the AutoML\n job V2 (Binary Classification, Multiclass Classification, Regression). For more\n information, see \n SageMaker Autopilot problem types.
" + "smithy.api#documentation": "The type of supervised learning problem available for the model candidates of the AutoML job V2 (Binary Classification, Multiclass Classification, Regression). For more information, see SageMaker Autopilot problem types.
" } } }, @@ -67641,7 +67626,7 @@ } }, "traits": { - "smithy.api#documentation": "A tag object that consists of a key and an optional value, used to manage metadata\n for SageMaker Amazon Web Services resources.
\nYou can add tags to notebook instances, training jobs, hyperparameter tuning jobs,\n batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and\n endpoints. For more information on adding tags to SageMaker resources, see AddTags.
\nFor more information on adding metadata to your Amazon Web Services resources with\n tagging, see Tagging Amazon Web Services resources. For advice on best practices for\n managing Amazon Web Services resources with tagging, see Tagging\n Best Practices: Implement an Effective Amazon Web Services Resource Tagging\n Strategy.
" + "smithy.api#documentation": "A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.
For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.
" } }, "com.amazonaws.sagemaker#TagKey": { @@ -67959,7 +67944,7 @@ "target": "com.amazonaws.sagemaker#TargetPlatformOs", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a target platform OS.
\n\n LINUX: Linux-based operating systems.
\n ANDROID: Android operating systems. Android API level can be\n specified using the ANDROID_PLATFORM compiler option. For example,\n \"CompilerOptions\": {'ANDROID_PLATFORM': 28}\n
Specifies a target platform OS.
LINUX: Linux-based operating systems.
ANDROID: Android operating systems. Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, \"CompilerOptions\": {'ANDROID_PLATFORM': 28}
Specifies a target platform architecture.
\n\n X86_64: 64-bit version of the x86 instruction set.
\n X86: 32-bit version of the x86 instruction set.
\n ARM64: ARMv8 64-bit CPU.
\n ARM_EABIHF: ARMv7 32-bit, Hard Float.
\n ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM\n platform.
Specifies a target platform architecture.
X86_64: 64-bit version of the x86 instruction set.
X86: 32-bit version of the x86 instruction set.
ARM64: ARMv8 64-bit CPU.
ARM_EABIHF: ARMv7 32-bit, Hard Float.
ARM_EABI: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.
Specifies a target platform accelerator (optional).
\n\n NVIDIA: Nvidia graphics processing unit. It also requires\n gpu-code, trt-ver, cuda-ver compiler\n options
\n MALI: ARM Mali graphics processor
\n INTEL_GRAPHICS: Integrated Intel graphics
Specifies a target platform accelerator (optional).
NVIDIA: Nvidia graphics processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler options
MALI: ARM Mali graphics processor
INTEL_GRAPHICS: Integrated Intel graphics
Contains information about a target platform that you want your model to run on, such\n as OS, architecture, and accelerators. It is an alternative of\n TargetDevice.
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
A target tracking scaling policy. Includes support for predefined or customized metrics.
\nWhen using the PutScalingPolicy API,\n this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
A target tracking scaling policy. Includes support for predefined or customized metrics.
When using the PutScalingPolicy API, this parameter is required when you are creating a policy with the policy type TargetTrackingScaling.
The default instance type and the Amazon Resource Name (ARN) of the SageMaker AI\n image created on the instance.
" + "smithy.api#documentation": "The default instance type and the Amazon Resource Name (ARN) of the SageMaker AI image created on the instance.
" } } }, @@ -68207,7 +68192,7 @@ "LocalPath": { "target": "com.amazonaws.sagemaker#DirectoryPath", "traits": { - "smithy.api#documentation": "Path to local storage location for tensorBoard output. Defaults to\n /opt/ml/output/tensorboard.
Path to local storage location for tensorBoard output. Defaults to /opt/ml/output/tensorboard.
How long a job is allowed to run, or how many candidates a job is allowed to\n generate.
" + "smithy.api#documentation": "How long a job is allowed to run, or how many candidates a job is allowed to generate.
" } }, "ContentColumn": { "target": "com.amazonaws.sagemaker#ContentColumn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the column used to provide the sentences to be classified. It should not be\n the same as the target column.
", + "smithy.api#documentation": "The name of the column used to provide the sentences to be classified. It should not be the same as the target column.
", "smithy.api#required": {} } }, @@ -68262,13 +68247,13 @@ "target": "com.amazonaws.sagemaker#TargetLabelColumn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the column used to provide the class labels. It should not be same as the\n content column.
", + "smithy.api#documentation": "The name of the column used to provide the class labels. It should not be same as the content column.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the text classification problem\n type.
" + "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the text classification problem type.
" } }, "com.amazonaws.sagemaker#TextGenerationHyperParameterKey": { @@ -68312,19 +68297,19 @@ "CompletionCriteria": { "target": "com.amazonaws.sagemaker#AutoMLJobCompletionCriteria", "traits": { - "smithy.api#documentation": "How long a fine-tuning job is allowed to run. For TextGenerationJobConfig\n problem types, the MaxRuntimePerTrainingJobInSeconds attribute of\n AutoMLJobCompletionCriteria defaults to 72h (259200s).
How long a fine-tuning job is allowed to run. For TextGenerationJobConfig problem types, the MaxRuntimePerTrainingJobInSeconds attribute of AutoMLJobCompletionCriteria defaults to 72h (259200s).
The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large\n language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no\n BaseModelName is provided, the default model used is Falcon7BInstruct.
The name of the base model to fine-tune. Autopilot supports fine-tuning a variety of large language models. For information on the list of supported models, see Text generation models supporting fine-tuning in Autopilot. If no BaseModelName is provided, the default model used is Falcon7BInstruct.
The hyperparameters used to configure and optimize the learning process of the base\n model. You can set any combination of the following hyperparameters for all base models.\n For more information on each supported hyperparameter, see Optimize\n the learning process of your text generation models with hyperparameters.
\n\n \"epochCount\": The number of times the model goes through the entire\n training dataset. Its value should be a string containing an integer value within the\n range of \"1\" to \"10\".
\n \"batchSize\": The number of data samples used in each iteration of\n training. Its value should be a string containing an integer value within the range\n of \"1\" to \"64\".
\n \"learningRate\": The step size at which a model's parameters are\n updated during training. Its value should be a string containing a floating-point\n value within the range of \"0\" to \"1\".
\n \"learningRateWarmupSteps\": The number of training steps during which\n the learning rate gradually increases before reaching its target or maximum value.\n Its value should be a string containing an integer value within the range of \"0\" to\n \"250\".
Here is an example where all four hyperparameters are configured.
\n\n { \"epochCount\":\"5\", \"learningRate\":\"0.5\", \"batchSize\": \"32\",\n \"learningRateWarmupSteps\": \"10\" }\n
The hyperparameters used to configure and optimize the learning process of the base model. You can set any combination of the following hyperparameters for all base models. For more information on each supported hyperparameter, see Optimize the learning process of your text generation models with hyperparameters.
\"epochCount\": The number of times the model goes through the entire training dataset. Its value should be a string containing an integer value within the range of \"1\" to \"10\".
\"batchSize\": The number of data samples used in each iteration of training. Its value should be a string containing an integer value within the range of \"1\" to \"64\".
\"learningRate\": The step size at which a model's parameters are updated during training. Its value should be a string containing a floating-point value within the range of \"0\" to \"1\".
\"learningRateWarmupSteps\": The number of training steps during which the learning rate gradually increases before reaching its target or maximum value. Its value should be a string containing an integer value within the range of \"0\" to \"250\".
Here is an example where all four hyperparameters are configured.
{ \"epochCount\":\"5\", \"learningRate\":\"0.5\", \"batchSize\": \"32\", \"learningRateWarmupSteps\": \"10\" }
The collection of settings used by an AutoML job V2 for the text generation problem\n type.
\nThe text generation models that support fine-tuning in Autopilot are currently accessible\n exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported\n Regions.
\nThe collection of settings used by an AutoML job V2 for the text generation problem type.
The text generation models that support fine-tuning in Autopilot are currently accessible exclusively in regions supported by Canvas. Refer to the documentation of Canvas for the full list of its supported Regions.
The mode used for your feature group throughput: ON_DEMAND or\n PROVISIONED.
The mode used for your feature group throughput: ON_DEMAND or PROVISIONED.
For provisioned feature groups with online store enabled, this indicates the read\n throughput you are billed for and can consume without throttling.
\nThis field is not applicable for on-demand feature groups.
" + "smithy.api#documentation": "For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
" } }, "ProvisionedWriteCapacityUnits": { "target": "com.amazonaws.sagemaker#CapacityUnit", "traits": { - "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for\n and can consume without throttling.
\nThis field is not applicable for on-demand feature groups.
" + "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
" } } }, "traits": { - "smithy.api#documentation": "Used to set feature group throughput configuration. There are two modes:\n ON_DEMAND and PROVISIONED. With on-demand mode, you are\n charged for data reads and writes that your application performs on your feature group. You\n do not need to specify read and write throughput because Feature Store accommodates your\n workloads as they ramp up and down. You can switch a feature group to on-demand only once\n in a 24 hour period. With provisioned throughput mode, you specify the read and write\n capacity per second that you expect your application to require, and you are billed based\n on those limits. Exceeding provisioned throughput will result in your requests being\n throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that\n are offline-only, or use the \n Standard\n tier online store.
Used to set feature group throughput configuration. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
The mode used for your feature group throughput: ON_DEMAND or\n PROVISIONED.
The mode used for your feature group throughput: ON_DEMAND or PROVISIONED.
For provisioned feature groups with online store enabled, this indicates the read\n throughput you are billed for and can consume without throttling.
\nThis field is not applicable for on-demand feature groups.
" + "smithy.api#documentation": "For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
" } }, "ProvisionedWriteCapacityUnits": { "target": "com.amazonaws.sagemaker#CapacityUnit", "traits": { - "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for\n and can consume without throttling.
\nThis field is not applicable for on-demand feature groups.
" + "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
This field is not applicable for on-demand feature groups.
" } } }, "traits": { - "smithy.api#documentation": "Active throughput configuration of the feature group. There are two modes:\n ON_DEMAND and PROVISIONED. With on-demand mode, you are\n charged for data reads and writes that your application performs on your feature group. You\n do not need to specify read and write throughput because Feature Store accommodates your\n workloads as they ramp up and down. You can switch a feature group to on-demand only once\n in a 24 hour period. With provisioned throughput mode, you specify the read and write\n capacity per second that you expect your application to require, and you are billed based\n on those limits. Exceeding provisioned throughput will result in your requests being\n throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that\n are offline-only, or use the \n Standard\n tier online store.
Active throughput configuration of the feature group. There are two modes: ON_DEMAND and PROVISIONED. With on-demand mode, you are charged for data reads and writes that your application performs on your feature group. You do not need to specify read and write throughput because Feature Store accommodates your workloads as they ramp up and down. You can switch a feature group to on-demand only once in a 24 hour period. With provisioned throughput mode, you specify the read and write capacity per second that you expect your application to require, and you are billed based on those limits. Exceeding provisioned throughput will result in your requests being throttled.
Note: PROVISIONED throughput mode is supported only for feature groups that are offline-only, or use the Standard tier online store.
Target throughput mode of the feature group. Throughput update is an asynchronous\n operation, and the outcome should be monitored by polling LastUpdateStatus\n field in DescribeFeatureGroup response. You cannot update a feature group's\n throughput while another update is in progress.
Target throughput mode of the feature group. Throughput update is an asynchronous operation, and the outcome should be monitored by polling LastUpdateStatus field in DescribeFeatureGroup response. You cannot update a feature group's throughput while another update is in progress.
For provisioned feature groups with online store enabled, this indicates the read\n throughput you are billed for and can consume without throttling.
" + "smithy.api#documentation": "For provisioned feature groups with online store enabled, this indicates the read throughput you are billed for and can consume without throttling.
" } }, "ProvisionedWriteCapacityUnits": { "target": "com.amazonaws.sagemaker#CapacityUnit", "traits": { - "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for\n and can consume without throttling.
" + "smithy.api#documentation": "For provisioned feature groups, this indicates the write throughput you are billed for and can consume without throttling.
" } } }, "traits": { - "smithy.api#documentation": "The new throughput configuration for the feature group. You can switch between on-demand\n and provisioned modes or update the read / write capacity of provisioned feature groups.\n You can switch a feature group to on-demand only once in a 24 hour period.
" + "smithy.api#documentation": "The new throughput configuration for the feature group. You can switch between on-demand and provisioned modes or update the read / write capacity of provisioned feature groups. You can switch a feature group to on-demand only once in a 24 hour period.
" } }, "com.amazonaws.sagemaker#ThroughputMode": { @@ -68465,7 +68450,7 @@ "target": "com.amazonaws.sagemaker#TargetAttributeName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the column representing the target variable that you want to predict for\n each item in your dataset. The data type of the target variable must be numerical.
", + "smithy.api#documentation": "The name of the column representing the target variable that you want to predict for each item in your dataset. The data type of the target variable must be numerical.
", "smithy.api#required": {} } }, @@ -68473,7 +68458,7 @@ "target": "com.amazonaws.sagemaker#TimestampAttributeName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the column indicating a point in time at which the target value of a given\n item is recorded.
", + "smithy.api#documentation": "The name of the column indicating a point in time at which the target value of a given item is recorded.
", "smithy.api#required": {} } }, @@ -68481,14 +68466,14 @@ "target": "com.amazonaws.sagemaker#ItemIdentifierAttributeName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the column that represents the set of item identifiers for which you want to\n predict the target value.
", + "smithy.api#documentation": "The name of the column that represents the set of item identifiers for which you want to predict the target value.
", "smithy.api#required": {} } }, "GroupingAttributeNames": { "target": "com.amazonaws.sagemaker#GroupingAttributeNames", "traits": { - "smithy.api#documentation": "A set of columns names that can be grouped with the item identifier column to create a\n composite key for which a target value is predicted.
" + "smithy.api#documentation": "A set of columns names that can be grouped with the item identifier column to create a composite key for which a target value is predicted.
" } } }, @@ -68502,7 +68487,7 @@ "FeatureSpecificationS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "A URL to the Amazon S3 data source containing additional selected features that\n complement the target, itemID, timestamp, and grouped columns set in\n TimeSeriesConfig. When not provided, the AutoML job V2 includes all the\n columns from the original dataset that are not already declared in\n TimeSeriesConfig. If provided, the AutoML job V2 only considers these\n additional columns as a complement to the ones declared in\n TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown\n below:
\n { \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown\n below:
\n\n { \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }\n
Autopilot supports the following data types: numeric, categorical,\n text, and datetime.
These column keys must not include any column set in\n TimeSeriesConfig.
A URL to the Amazon S3 data source containing additional selected features that complement the target, itemID, timestamp, and grouped columns set in TimeSeriesConfig. When not provided, the AutoML job V2 includes all the columns from the original dataset that are not already declared in TimeSeriesConfig. If provided, the AutoML job V2 only considers these additional columns as a complement to the ones declared in TimeSeriesConfig.
You can input FeatureAttributeNames (optional) in JSON format as shown below:
{ \"FeatureAttributeNames\":[\"col1\", \"col2\", ...] }.
You can also specify the data type of the feature (optional) in the format shown below:
{ \"FeatureDataTypes\":{\"col1\":\"numeric\", \"col2\":\"categorical\" ... } }
Autopilot supports the following data types: numeric, categorical, text, and datetime.
These column keys must not include any column set in TimeSeriesConfig.
The frequency of predictions in a forecast.
\nValid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H\n (Hour), and min (Minute). For example, 1D indicates every day and\n 15min indicates every 15 minutes. The value of a frequency must not overlap\n with the next larger frequency. For example, you must use a frequency of 1H\n instead of 60min.
The valid values for each frequency are the following:
\nMinute - 1-59
\nHour - 1-23
\nDay - 1-6
\nWeek - 1-4
\nMonth - 1-11
\nYear - 1
\nThe frequency of predictions in a forecast.
Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, 1D indicates every day and 15min indicates every 15 minutes. The value of a frequency must not overlap with the next larger frequency. For example, you must use a frequency of 1H instead of 60min.
The valid values for each frequency are the following:
Minute - 1-59
Hour - 1-23
Day - 1-6
Week - 1-4
Month - 1-11
Year - 1
The number of time-steps that the model predicts. The forecast horizon is also called\n the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4\n of the time-steps in the dataset.
", + "smithy.api#documentation": "The number of time-steps that the model predicts. The forecast horizon is also called the prediction length. The maximum forecast horizon is the lesser of 500 time-steps or 1/4 of the time-steps in the dataset.
", "smithy.api#required": {} } }, "ForecastQuantiles": { "target": "com.amazonaws.sagemaker#ForecastQuantiles", "traits": { - "smithy.api#documentation": "The quantiles used to train the model for forecasts at a specified quantile. You can\n specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of\n 0.01 or higher. Up to five forecast quantiles can be specified. When\n ForecastQuantiles is not provided, the AutoML job uses the quantiles p10,\n p50, and p90 as default.
The quantiles used to train the model for forecasts at a specified quantile. You can specify quantiles from 0.01 (p1) to 0.99 (p99), by increments of 0.01 or higher. Up to five forecast quantiles can be specified. When ForecastQuantiles is not provided, the AutoML job uses the quantiles p10, p50, and p90 as default.
The transformations modifying specific attributes of the time-series, such as filling\n strategies for missing values.
" + "smithy.api#documentation": "The transformations modifying specific attributes of the time-series, such as filling strategies for missing values.
" } }, "TimeSeriesConfig": { @@ -68547,7 +68532,7 @@ "HolidayConfig": { "target": "com.amazonaws.sagemaker#HolidayConfig", "traits": { - "smithy.api#documentation": "The collection of holiday featurization attributes used to incorporate national holiday\n information into your forecasting model.
" + "smithy.api#documentation": "The collection of holiday featurization attributes used to incorporate national holiday information into your forecasting model.
" } }, "CandidateGenerationConfig": { @@ -68555,7 +68540,7 @@ } }, "traits": { - "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the time-series forecasting\n problem type.
" + "smithy.api#documentation": "The collection of settings used by an AutoML job V2 for the time-series forecasting problem type.
" } }, "com.amazonaws.sagemaker#TimeSeriesForecastingSettings": { @@ -68564,13 +68549,13 @@ "Status": { "target": "com.amazonaws.sagemaker#FeatureStatus", "traits": { - "smithy.api#documentation": "Describes whether time series forecasting is enabled or disabled in the Canvas\n application.
" + "smithy.api#documentation": "Describes whether time series forecasting is enabled or disabled in the Canvas application.
" } }, "AmazonForecastRoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default,\n Canvas uses the execution role specified in the UserProfile that launches the\n Canvas application. If an execution role is not specified in the UserProfile,\n Canvas uses the execution role specified in the Domain that owns the\n UserProfile. To allow time series forecasting, this IAM role should have the\n AmazonSageMakerCanvasForecastAccess policy attached and\n forecast.amazonaws.com added in the trust relationship as a service\n principal.
The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile that launches the Canvas application. If an execution role is not specified in the UserProfile, Canvas uses the execution role specified in the Domain that owns the UserProfile. To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com added in the trust relationship as a service principal.
A key value pair defining the filling method for a column, where the key is the column\n name and the value is an object which defines the filling logic. You can specify multiple\n filling methods for a single column.
\nThe supported filling methods and their corresponding options are:
\n\n frontfill: none (Supported only for target\n column)
\n middlefill: zero, value,\n median, mean, min, max\n
\n backfill: zero, value, median,\n mean, min, max\n
\n futurefill: zero, value,\n median, mean, min, max\n
To set a filling method to a specific value, set the fill parameter to the chosen\n filling method value (for example \"backfill\" : \"value\"), and define the\n filling value in an additional parameter prefixed with \"_value\". For example, to set\n backfill to a value of 2, you must include two parameters:\n \"backfill\": \"value\" and \"backfill_value\":\"2\".
A key value pair defining the filling method for a column, where the key is the column name and the value is an object which defines the filling logic. You can specify multiple filling methods for a single column.
The supported filling methods and their corresponding options are:
frontfill: none (Supported only for target column)
middlefill: zero, value, median, mean, min, max
backfill: zero, value, median, mean, min, max
futurefill: zero, value, median, mean, min, max
To set a filling method to a specific value, set the fill parameter to the chosen filling method value (for example \"backfill\" : \"value\"), and define the filling value in an additional parameter prefixed with \"_value\". For example, to set backfill to a value of 2, you must include two parameters: \"backfill\": \"value\" and \"backfill_value\":\"2\".
A key value pair defining the aggregation method for a column, where the key is the\n column name and the value is the aggregation method.
\nThe supported aggregation methods are sum (default), avg,\n first, min, max.
Aggregation is only supported for the target column.
\nA key value pair defining the aggregation method for a column, where the key is the column name and the value is the aggregation method.
The supported aggregation methods are sum (default), avg, first, min, max.
Aggregation is only supported for the target column.
Transformations allowed on the dataset. Supported transformations are\n Filling and Aggregation. Filling specifies how to\n add values to missing values in the dataset. Aggregation defines how to\n aggregate data that does not align with forecast frequency.
Transformations allowed on the dataset. Supported transformations are Filling and Aggregation. Filling specifies how to add values to missing values in the dataset. Aggregation defines how to aggregate data that does not align with forecast frequency.
The total number of matching results. This value may be exact or an estimate, depending on\n the Relation field.
The total number of matching results. This value may be exact or an estimate, depending on the Relation field.
Indicates the relationship between the returned Value and the actual total\n number of matching results. Possible values are:
\n EqualTo: The Value is the exact count of matching\n results.
\n GreaterThanOrEqualTo: The Value is a lower bound of the\n actual count of matching results.
Indicates the relationship between the returned Value and the actual total number of matching results. Possible values are:
EqualTo: The Value is the exact count of matching results.
GreaterThanOrEqualTo: The Value is a lower bound of the actual count of matching results.
Represents the total number of matching results and indicates how accurate that count\n is.
\nThe Value field provides the count, which may be exact or estimated. The\n Relation field indicates whether it's an exact figure or a lower bound. This\n helps understand the full scope of search results, especially when dealing with large result\n sets.
Represents the total number of matching results and indicates how accurate that count is.
The Value field provides the count, which may be exact or estimated. The Relation field indicates whether it's an exact figure or a lower bound. This helps understand the full scope of search results, especially when dealing with large result sets.
Traffic routing strategy type.
\n\n ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single\n step.
\n CANARY: Endpoint traffic shifts to the new fleet in two steps.\n The first step is the canary, which is a small portion of the traffic. The\n second step is the remainder of the traffic.
\n LINEAR: Endpoint traffic shifts to the new fleet in n steps of a\n configurable size.
Traffic routing strategy type.
ALL_AT_ONCE: Endpoint traffic shifts to the new fleet in a single step.
CANARY: Endpoint traffic shifts to the new fleet in two steps. The first step is the canary, which is a small portion of the traffic. The second step is the remainder of the traffic.
LINEAR: Endpoint traffic shifts to the new fleet in n steps of a configurable size.
The waiting time (in seconds) between incremental steps to turn on traffic on the new\n endpoint fleet.
", + "smithy.api#documentation": "The waiting time (in seconds) between incremental steps to turn on traffic on the new endpoint fleet.
", "smithy.api#required": {} } }, "CanarySize": { "target": "com.amazonaws.sagemaker#CapacitySize", "traits": { - "smithy.api#documentation": "Batch size for the first step to turn on traffic on the new endpoint fleet.\n Value must be less than or equal to 50% of the variant's total instance\n count.
Batch size for the first step to turn on traffic on the new endpoint fleet. Value must be less than or equal to 50% of the variant's total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet.\n Value must be 10-50% of the variant's total instance count.
Batch size for each step to turn on traffic on the new endpoint fleet. Value must be 10-50% of the variant's total instance count.
Defines the traffic routing strategy during an endpoint deployment to shift traffic\n from the old fleet to the new fleet.
" + "smithy.api#documentation": "Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.
" } }, "com.amazonaws.sagemaker#TrafficRoutingConfigType": { @@ -69055,19 +69040,19 @@ "target": "com.amazonaws.sagemaker#TrainingRepositoryAccessMode", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The method that your training job will use to gain access to the images in your\n private Docker registry. For access to an image in a private Docker registry, set to\n Vpc.
The method that your training job will use to gain access to the images in your private Docker registry. For access to an image in a private Docker registry, set to Vpc.
An object containing authentication information for a private Docker registry\n containing your training images.
" + "smithy.api#documentation": "An object containing authentication information for a private Docker registry containing your training images.
" } } }, "traits": { - "smithy.api#documentation": "The configuration to use an image from a private Docker registry for a training\n job.
" + "smithy.api#documentation": "The configuration to use an image from a private Docker registry for a training job.
" } }, "com.amazonaws.sagemaker#TrainingInputMode": { @@ -69093,7 +69078,7 @@ } }, "traits": { - "smithy.api#documentation": "The training input mode that the algorithm supports. For more information about input\n modes, see Algorithms.
\n\n Pipe mode\n
\nIf an algorithm supports Pipe mode, Amazon SageMaker streams data directly from\n Amazon S3 to the container.
\n File mode\n
\nIf an algorithm supports File mode, SageMaker downloads the training data from\n S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume\n for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the\n data downloaded from S3. In addition to the training data, the ML storage volume also\n stores the output model. The algorithm container uses the ML storage volume to also\n store intermediate information, if any.
\nFor distributed algorithms, training data is distributed uniformly. Your training\n duration is predictable if the input data objects sizes are approximately the same. SageMaker\n does not split the files any further for model training. If the object sizes are skewed,\n training won't be optimal as the data distribution is also skewed when one host in a\n training cluster is overloaded, thus becoming a bottleneck in training.
\n\n FastFile mode\n
\nIf an algorithm supports FastFile mode, SageMaker streams data directly from\n S3 to the container with no code changes, and provides file system access to the data.\n Users can author their training script to interact with these files as if they were\n stored on disk.
\n FastFile mode works best when the data is read sequentially. Augmented\n manifest files aren't supported. The startup time is lower when there are fewer files in\n the S3 bucket provided.
The training input mode that the algorithm supports. For more information about input modes, see Algorithms.
Pipe mode
If an algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon S3 to the container.
File mode
If an algorithm supports File mode, SageMaker downloads the training data from S3 to the provisioned ML storage volume, and mounts the directory to the Docker volume for the training container.
You must provision the ML storage volume with sufficient capacity to accommodate the data downloaded from S3. In addition to the training data, the ML storage volume also stores the output model. The algorithm container uses the ML storage volume to also store intermediate information, if any.
For distributed algorithms, training data is distributed uniformly. Your training duration is predictable if the input data objects sizes are approximately the same. SageMaker does not split the files any further for model training. If the object sizes are skewed, training won't be optimal as the data distribution is also skewed when one host in a training cluster is overloaded, thus becoming a bottleneck in training.
FastFile mode
If an algorithm supports FastFile mode, SageMaker streams data directly from S3 to the container with no code changes, and provides file system access to the data. Users can author their training script to interact with these files as if they were stored on disk.
FastFile mode works best when the data is read sequentially. Augmented manifest files aren't supported. The startup time is lower when there are fewer files in the S3 bucket provided.
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the\n training job was launched by a hyperparameter tuning job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
" } }, "LabelingJobArn": { @@ -69799,19 +69784,19 @@ "ModelArtifacts": { "target": "com.amazonaws.sagemaker#ModelArtifacts", "traits": { - "smithy.api#documentation": "Information about the Amazon S3 location that is configured for storing model\n artifacts.
" + "smithy.api#documentation": "Information about the Amazon S3 location that is configured for storing model artifacts.
" } }, "TrainingJobStatus": { "target": "com.amazonaws.sagemaker#TrainingJobStatus", "traits": { - "smithy.api#documentation": "The status of the\n training\n job.
\nTraining job statuses are:
\n\n InProgress - The training is in progress.
\n Completed - The training job has completed.
\n Failed - The training job has failed. To see the reason for the\n failure, see the FailureReason field in the response to a\n DescribeTrainingJobResponse call.
\n Stopping - The training job is stopping.
\n Stopped - The training job has stopped.
For\n more detailed information, see SecondaryStatus.
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
Provides detailed information about the state of the training job. For detailed\n information about the secondary status of the training job, see\n StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of\n them:
\n\n Starting\n - Starting the training job.
\n Downloading - An optional stage for algorithms that\n support File training input mode. It indicates that\n data is being downloaded to the ML storage volumes.
\n Training - Training is in progress.
\n Uploading - Training is complete and the model\n artifacts are being uploaded to the S3 location.
\n Completed - The training job has completed.
\n Failed - The training job has failed. The reason for\n the failure is returned in the FailureReason field of\n DescribeTrainingJobResponse.
\n MaxRuntimeExceeded - The job stopped because it\n exceeded the maximum allowed runtime.
\n Stopped - The training job has stopped.
\n Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
\n\n LaunchingMLInstances\n
\n PreparingTrainingStack\n
\n DownloadingTrainingImage\n
Provides detailed information about the state of the training job. For detailed information about the secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
The Amazon Web Services Identity and Access Management (IAM) role configured for the\n training job.
" + "smithy.api#documentation": "The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
" } }, "InputDataConfig": { "target": "com.amazonaws.sagemaker#InputDataConfig", "traits": { - "smithy.api#documentation": "An array of Channel objects that describes each data input\n channel.
Your input must be in the same Amazon Web Services region as your training job.
" + "smithy.api#documentation": "An array of Channel objects that describes each data input channel.
Your input must be in the same Amazon Web Services region as your training job.
" } }, "OutputDataConfig": { "target": "com.amazonaws.sagemaker#OutputDataConfig", "traits": { - "smithy.api#documentation": "The S3 path where model artifacts that you configured when creating the job are\n stored. SageMaker creates subfolders for model artifacts.
" + "smithy.api#documentation": "The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
" } }, "ResourceConfig": { "target": "com.amazonaws.sagemaker#ResourceConfig", "traits": { - "smithy.api#documentation": "Resources, including ML compute instances and ML storage volumes, that are configured\n for model training.
" + "smithy.api#documentation": "Resources, including ML compute instances and ML storage volumes, that are configured for model training.
" } }, "VpcConfig": { "target": "com.amazonaws.sagemaker#VpcConfig", "traits": { - "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this training job has access\n to. For more information, see Protect Training Jobs by Using an Amazon\n Virtual Private Cloud.
" + "smithy.api#documentation": "A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
" } }, "StoppingCondition": { "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { - "smithy.api#documentation": "Specifies a limit to how long a model training job can run. It also specifies how long\n a managed Spot training job has to complete. When the job reaches the time limit, SageMaker\n ends the training job. Use this API to cap model training costs.
\nTo stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays\n job termination for 120 seconds. Algorithms can use this 120-second window to save the\n model artifacts, so the results of training are not lost.
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
Indicates the time when the training job starts on training instances. You are billed\n for the time interval between this time and the value of TrainingEndTime.\n The start time in CloudWatch Logs might be later than this time. The difference is due to the time\n it takes to download the training data and to the size of the training container.
Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.
Indicates the time when the training job ends on training instances. You are billed\n for the time interval between the value of TrainingStartTime and this time.\n For successful jobs and stopped jobs, this is the time after model artifacts are\n uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.
A timestamp that indicates when the status of the training job was last\n modified.
" + "smithy.api#documentation": "A timestamp that indicates when the status of the training job was last modified.
" } }, "SecondaryStatusTransitions": { "target": "com.amazonaws.sagemaker#SecondaryStatusTransitions", "traits": { - "smithy.api#documentation": "A history of all of the secondary statuses that the training job has transitioned\n through.
" + "smithy.api#documentation": "A history of all of the secondary statuses that the training job has transitioned through.
" } }, "FinalMetricDataList": { "target": "com.amazonaws.sagemaker#FinalMetricDataList", "traits": { - "smithy.api#documentation": "A list of final metric values that are set when the training job completes. Used only\n if the training job was configured to use metrics.
" + "smithy.api#documentation": "A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
" } }, "EnableNetworkIsolation": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "If the TrainingJob was created with network isolation, the value is set\n to true. If network isolation is enabled, nodes can't communicate beyond\n the VPC they run in.
If the TrainingJob was created with network isolation, the value is set to true. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.
To encrypt all communications between ML compute instances in distributed training,\n choose True. Encryption provides greater security for distributed training,\n but training might take longer. How long it takes depends on the amount of communication\n between compute instances, especially if you use a deep learning algorithm in\n distributed training.
To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
When true, enables managed spot training using Amazon EC2 Spot instances to run\n training jobs instead of on-demand instances. For more information, see Managed Spot Training.
" + "smithy.api#documentation": "When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
" } }, "CheckpointConfig": { @@ -69970,13 +69955,13 @@ "RetryStrategy": { "target": "com.amazonaws.sagemaker#RetryStrategy", "traits": { - "smithy.api#documentation": "The number of times to retry the job when the job fails due to an\n InternalServerError.
The number of times to retry the job when the job fails due to an InternalServerError.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services\n resources in different ways, for example, by purpose, owner, or environment. For more\n information, see Tagging Amazon Web Services Resources.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
" } } }, @@ -70014,7 +69999,7 @@ "target": "com.amazonaws.sagemaker#InputDataConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "An array of Channel objects, each of which specifies an input\n source.
An array of Channel objects, each of which specifies an input source.
the path to the S3 bucket where you want to store model artifacts. SageMaker creates\n subfolders for the artifacts.
", + "smithy.api#documentation": "the path to the S3 bucket where you want to store model artifacts. SageMaker creates subfolders for the artifacts.
", "smithy.api#required": {} } }, @@ -70030,7 +70015,7 @@ "target": "com.amazonaws.sagemaker#ResourceConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The resources, including the ML compute instances and ML storage volumes, to use for\n model training.
", + "smithy.api#documentation": "The resources, including the ML compute instances and ML storage volumes, to use for model training.
", "smithy.api#required": {} } }, @@ -70038,7 +70023,7 @@ "target": "com.amazonaws.sagemaker#StoppingCondition", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Specifies a limit to how long a model training job can run. It also specifies how long\n a managed Spot training job has to complete. When the job reaches the time limit, SageMaker\n ends the training job. Use this API to cap model training costs.
\nTo stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job\n termination for 120 seconds. Algorithms can use this 120-second window to save the model\n artifacts.
", + "smithy.api#documentation": "Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.
", "smithy.api#required": {} } } @@ -70152,36 +70137,36 @@ "Completed": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounter", "traits": { - "smithy.api#documentation": "The number of completed training jobs launched by the hyperparameter tuning\n job.
" + "smithy.api#documentation": "The number of completed training jobs launched by the hyperparameter tuning job.
" } }, "InProgress": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounter", "traits": { - "smithy.api#documentation": "The number of in-progress training jobs launched by a hyperparameter tuning\n job.
" + "smithy.api#documentation": "The number of in-progress training jobs launched by a hyperparameter tuning job.
" } }, "RetryableError": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs that failed, but can be retried. A failed training job can\n be retried only if it failed because an internal service error occurred.
" + "smithy.api#documentation": "The number of training jobs that failed, but can be retried. A failed training job can be retried only if it failed because an internal service error occurred.
" } }, "NonRetryableError": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs that failed and can't be retried. A failed training job\n can't be retried if it failed because a client error occurred.
" + "smithy.api#documentation": "The number of training jobs that failed and can't be retried. A failed training job can't be retried if it failed because a client error occurred.
" } }, "Stopped": { "target": "com.amazonaws.sagemaker#TrainingJobStatusCounter", "traits": { - "smithy.api#documentation": "The number of training jobs launched by a hyperparameter tuning job that were\n manually\n stopped.
" + "smithy.api#documentation": "The number of training jobs launched by a hyperparameter tuning job that were manually stopped.
" } } }, "traits": { - "smithy.api#documentation": "The numbers of training jobs launched by a hyperparameter tuning job, categorized by\n status.
" + "smithy.api#documentation": "The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
" } }, "com.amazonaws.sagemaker#TrainingJobStepMetadata": { @@ -70234,7 +70219,7 @@ "TrainingEndTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "A timestamp that shows when the training job ended. This field is set only if the\n training job has one of the terminal statuses (Completed,\n Failed, or Stopped).
A timestamp that shows when the training job ended. This field is set only if the training job has one of the terminal statuses (Completed, Failed, or Stopped).
The Amazon Resource Name (ARN); of the training plan associated with this training job.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
The Amazon Resource Name (ARN); of the training plan associated with this training job.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
A filter to apply when listing or searching for training plans.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
A filter to apply when listing or searching for training plans.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) for this training plan\n offering.
\nTraining plans are specific to their target resource.
\nA training plan designed for SageMaker training jobs can only be used to schedule and\n run training jobs.
\nA training plan for HyperPod clusters can be used exclusively to provide\n compute resources to a cluster's instance group.
\nThe target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) for this training plan offering.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
The requested start time that the user specified when searching for the training plan\n offering.
" + "smithy.api#documentation": "The requested start time that the user specified when searching for the training plan offering.
" } }, "RequestedEndTimeBefore": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "The requested end time that the user specified when searching for the training plan\n offering.
" + "smithy.api#documentation": "The requested end time that the user specified when searching for the training plan offering.
" } }, "DurationHours": { @@ -70414,7 +70399,7 @@ "DurationMinutes": { "target": "com.amazonaws.sagemaker#TrainingPlanDurationMinutes", "traits": { - "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training plan\n offering.
" + "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training plan offering.
" } }, "UpfrontFee": { @@ -70432,12 +70417,12 @@ "ReservedCapacityOfferings": { "target": "com.amazonaws.sagemaker#ReservedCapacityOfferings", "traits": { - "smithy.api#documentation": "A list of reserved capacity offerings associated with this training plan\n offering.
" + "smithy.api#documentation": "A list of reserved capacity offerings associated with this training plan offering.
" } } }, "traits": { - "smithy.api#documentation": "Details about a training plan offering.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
Details about a training plan offering.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The current status of the training plan (e.g., Pending, Active, Expired). To see the\n complete list of status values available for a training plan, refer to the\n Status attribute within the \n TrainingPlanSummary\n object.
The current status of the training plan (e.g., Pending, Active, Expired). To see the complete list of status values available for a training plan, refer to the Status attribute within the TrainingPlanSummary object.
A message providing additional information about the current status of the training\n plan.
" + "smithy.api#documentation": "A message providing additional information about the current status of the training plan.
" } }, "DurationHours": { @@ -70593,7 +70578,7 @@ "DurationMinutes": { "target": "com.amazonaws.sagemaker#TrainingPlanDurationMinutes", "traits": { - "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training\n plan.
" + "smithy.api#documentation": "The additional minutes beyond whole hours in the total duration for this training plan.
" } }, "StartTime": { @@ -70641,18 +70626,18 @@ "TargetResources": { "target": "com.amazonaws.sagemaker#SageMakerResourceNames", "traits": { - "smithy.api#documentation": "The target resources (e.g., training jobs, HyperPod clusters) that can use this training\n plan.
\nTraining plans are specific to their target resource.
\nA training plan designed for SageMaker training jobs can only be used to schedule and\n run training jobs.
\nA training plan for HyperPod clusters can be used exclusively to provide\n compute resources to a cluster's instance group.
\nThe target resources (e.g., training jobs, HyperPod clusters) that can use this training plan.
Training plans are specific to their target resource.
A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster's instance group.
A list of reserved capacities associated with this training plan, including details such\n as instance types, counts, and availability zones.
" + "smithy.api#documentation": "A list of reserved capacities associated with this training plan, including details such as instance types, counts, and availability zones.
" } } }, "traits": { - "smithy.api#documentation": "Details of the training plan.
\nFor more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using\n Amazon SageMaker Training Plan, see \n CreateTrainingPlan\n .
Details of the training plan.
For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan .
The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access\n credentials to your private Docker registry.
", + "smithy.api#documentation": "The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function used to give SageMaker access credentials to your private Docker registry.
", "smithy.api#required": {} } } @@ -70705,20 +70690,20 @@ "target": "com.amazonaws.sagemaker#ContainerImage", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The Amazon ECR registry path of the Docker image that contains the training\n algorithm.
", + "smithy.api#documentation": "The Amazon ECR registry path of the Docker image that contains the training algorithm.
", "smithy.api#required": {} } }, "TrainingImageDigest": { "target": "com.amazonaws.sagemaker#ImageDigest", "traits": { - "smithy.api#documentation": "An MD5 hash of the training algorithm that identifies the Docker image used for\n training.
" + "smithy.api#documentation": "An MD5 hash of the training algorithm that identifies the Docker image used for training.
" } }, "SupportedHyperParameters": { "target": "com.amazonaws.sagemaker#HyperParameterSpecifications", "traits": { - "smithy.api#documentation": "A list of the HyperParameterSpecification objects, that define the\n supported hyperparameters. This is required if the algorithm supports automatic model\n tuning.>
A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Indicates whether the algorithm supports distributed training. If set to false, buyers\n can't request more than one instance during training.
" + "smithy.api#documentation": "Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
" } }, "MetricDefinitions": { "target": "com.amazonaws.sagemaker#MetricDefinitionList", "traits": { - "smithy.api#documentation": "A list of MetricDefinition objects, which are used for parsing metrics\n generated by the algorithm.
A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
A list of ChannelSpecification objects, which specify the input sources\n to be used by the algorithm.
A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
A list of the metrics that the algorithm emits that can be used as the objective\n metric in a hyperparameter tuning job.
" + "smithy.api#documentation": "A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
" } }, "AdditionalS3DataSource": { @@ -70842,31 +70827,31 @@ "target": "com.amazonaws.sagemaker#TransformDataSource", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Describes the location of\n the\n channel data, which is, the S3 location of the input data that the\n model can consume.
", + "smithy.api#documentation": "Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
", "smithy.api#required": {} } }, "ContentType": { "target": "com.amazonaws.sagemaker#ContentType", "traits": { - "smithy.api#documentation": "The multipurpose internet mail extension\n (MIME)\n type of the data. Amazon SageMaker uses the MIME type with each http call to\n transfer data to the transform job.
" + "smithy.api#documentation": "The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
" } }, "CompressionType": { "target": "com.amazonaws.sagemaker#CompressionType", "traits": { - "smithy.api#documentation": "If your transform data\n is\n compressed, specify the compression type. Amazon SageMaker automatically\n decompresses the data for the transform job accordingly. The default value is\n None.
If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
The method to use to split the transform job's data files into smaller batches.\n Splitting is necessary when the total size of each object is too large to fit in a\n single request. You can also use data splitting to improve performance by processing\n multiple concurrent mini-batches. The default value for SplitType is\n None, which indicates that input data files are not split, and request\n payloads contain the entire contents of an input object. Set the value of this parameter\n to Line to split records on a newline character boundary.\n SplitType also supports a number of record-oriented binary data\n formats. Currently, the supported record formats are:
RecordIO
\nTFRecord
\nWhen splitting is enabled, the size of a mini-batch depends on the values of the\n BatchStrategy and MaxPayloadInMB parameters. When the\n value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum\n number of records in each request, up to the MaxPayloadInMB limit. If the\n value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual\n records in each request.
Some data formats represent a record as a binary payload wrapped with extra\n padding bytes. When splitting is applied to a binary data format, padding is removed\n if the value of BatchStrategy is set to SingleRecord.\n Padding is not removed if the value of BatchStrategy is set to\n MultiRecord.
For more information about RecordIO, see Create a Dataset Using\n RecordIO in the MXNet documentation. For more information about\n TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
The method to use to split the transform job's data files into smaller batches. Splitting is necessary when the total size of each object is too large to fit in a single request. You can also use data splitting to improve performance by processing multiple concurrent mini-batches. The default value for SplitType is None, which indicates that input data files are not split, and request payloads contain the entire contents of an input object. Set the value of this parameter to Line to split records on a newline character boundary. SplitType also supports a number of record-oriented binary data formats. Currently, the supported record formats are:
RecordIO
TFRecord
When splitting is enabled, the size of a mini-batch depends on the values of the BatchStrategy and MaxPayloadInMB parameters. When the value of BatchStrategy is MultiRecord, Amazon SageMaker sends the maximum number of records in each request, up to the MaxPayloadInMB limit. If the value of BatchStrategy is SingleRecord, Amazon SageMaker sends individual records in each request.
Some data formats represent a record as a binary payload wrapped with extra padding bytes. When splitting is applied to a binary data format, padding is removed if the value of BatchStrategy is set to SingleRecord. Padding is not removed if the value of BatchStrategy is set to MultiRecord.
For more information about RecordIO, see Create a Dataset Using RecordIO in the MXNet documentation. For more information about TFRecord, see Consuming TFRecord data in the TensorFlow documentation.
Describes the input source of a transform job and the way the transform job consumes\n it.
" + "smithy.api#documentation": "Describes the input source of a transform job and the way the transform job consumes it.
" } }, "com.amazonaws.sagemaker#TransformInstanceCount": { @@ -71511,7 +71496,7 @@ "TransformJobStatus": { "target": "com.amazonaws.sagemaker#TransformJobStatus", "traits": { - "smithy.api#documentation": "The status of the transform job.
\nTransform job statuses are:
\n\n InProgress - The job is in progress.
\n Completed - The job has completed.
\n Failed - The transform job has failed. To see the reason for the failure,\n see the FailureReason field in the response to a\n DescribeTransformJob call.
\n Stopping - The transform job is stopping.
\n Stopped - The transform job has stopped.
The status of the transform job.
Transform job statuses are:
InProgress - The job is in progress.
Completed - The job has completed.
Failed - The transform job has failed. To see the reason for the failure, see the FailureReason field in the response to a DescribeTransformJob call.
Stopping - The transform job is stopping.
Stopped - The transform job has stopped.
The maximum number of parallel requests that can be sent to each instance in a transform\n job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the\n optional execution-parameters to determine the settings for your chosen algorithm. If the\n execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms,\n you don't need to set a value for MaxConcurrentTransforms.
The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For built-in algorithms, you don't need to set a value for MaxConcurrentTransforms.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record\n (without metadata). The value in MaxPayloadInMB must be greater than, or equal\n to, the size of a single record. To estimate the size of a record in MB, divide the size of\n your dataset by the number of records. To ensure that the records fit within the maximum\n payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases\n where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding,\n set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in\n algorithms do not support HTTP chunked encoding.
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding.
Specifies the number of records to include in a mini-batch for an HTTP inference request.\n A record is a single unit of input data that inference can be made on. For example, a single\n line in a CSV file is a record.
" + "smithy.api#documentation": "Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.
" } }, "Environment": { "target": "com.amazonaws.sagemaker#TransformEnvironmentMap", "traits": { - "smithy.api#documentation": "The environment variables to set in the Docker container. We support up to 16 key and\n values entries in the map.
" + "smithy.api#documentation": "The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
" } }, "TransformInput": { @@ -71574,19 +71559,19 @@ "TransformStartTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Indicates when the transform job starts on ML instances. You are billed for the time\n interval between this time and the value of TransformEndTime.
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime.
Indicates when the transform job has been completed, or has stopped or failed. You are\n billed for the time interval between this time and the value of\n TransformStartTime.
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of TransformStartTime.
The Amazon Resource Name (ARN) of the labeling job that created the transform job.
" + "smithy.api#documentation": "The Amazon Resource Name (ARN) of the labeling job that created the transform job.
" } }, "AutoMLJobArn": { @@ -71609,7 +71594,7 @@ } }, "traits": { - "smithy.api#documentation": "A batch transform job. For information about SageMaker batch transform, see Use Batch\n Transform.
" + "smithy.api#documentation": "A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
" } }, "com.amazonaws.sagemaker#TransformJobArn": { @@ -71628,25 +71613,25 @@ "MaxConcurrentTransforms": { "target": "com.amazonaws.sagemaker#MaxConcurrentTransforms", "traits": { - "smithy.api#documentation": "The maximum number of parallel requests that can be sent to each instance in a\n transform job. The default value is 1.
" + "smithy.api#documentation": "The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
" } }, "MaxPayloadInMB": { "target": "com.amazonaws.sagemaker#MaxPayloadInMB", "traits": { - "smithy.api#documentation": "The maximum payload size allowed, in MB. A payload is the data portion of a record\n (without metadata).
" + "smithy.api#documentation": "The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
" } }, "BatchStrategy": { "target": "com.amazonaws.sagemaker#BatchStrategy", "traits": { - "smithy.api#documentation": "A string that determines the number of records included in a single mini-batch.
\n\n SingleRecord means only one record is used per mini-batch.\n MultiRecord means a mini-batch is set to contain as many records that\n can fit within the MaxPayloadInMB limit.
A string that determines the number of records included in a single mini-batch.
SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.
The environment variables to set in the Docker container. We support up to 16 key and\n values entries in the map.
" + "smithy.api#documentation": "The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
" } }, "TransformInput": { @@ -71661,7 +71646,7 @@ "target": "com.amazonaws.sagemaker#TransformOutput", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the\n transform job.
", + "smithy.api#documentation": "Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
", "smithy.api#required": {} } }, @@ -71675,7 +71660,7 @@ } }, "traits": { - "smithy.api#documentation": "Defines the input needed to run a transform job using the inference specification\n specified in the algorithm.
" + "smithy.api#documentation": "Defines the input needed to run a transform job using the inference specification specified in the algorithm.
" } }, "com.amazonaws.sagemaker#TransformJobName": { @@ -71773,7 +71758,7 @@ "TransformEndTime": { "target": "com.amazonaws.sagemaker#Timestamp", "traits": { - "smithy.api#documentation": "Indicates when the transform\n job\n ends on compute instances. For successful jobs and stopped jobs, this\n is the exact time\n recorded\n after the results are uploaded. For failed jobs, this is when Amazon SageMaker\n detected that the job failed.
" + "smithy.api#documentation": "Indicates when the transform job ends on compute instances. For successful jobs and stopped jobs, this is the exact time recorded after the results are uploaded. For failed jobs, this is when Amazon SageMaker detected that the job failed.
" } }, "LastModifiedTime": { @@ -71793,12 +71778,12 @@ "FailureReason": { "target": "com.amazonaws.sagemaker#FailureReason", "traits": { - "smithy.api#documentation": "If the transform job failed,\n the\n reason it failed.
" + "smithy.api#documentation": "If the transform job failed, the reason it failed.
" } } }, "traits": { - "smithy.api#documentation": "Provides a\n summary\n of a transform job. Multiple TransformJobSummary objects are returned as a\n list after in response to a ListTransformJobs call.
Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For\n example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the\n transformed data with an .out suffix in a corresponding subfolder in the\n location in the output prefix. For example, for the input data stored at\n s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform\n stores the transformed data at\n s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out.\n Batch transform doesn't upload partially processed objects. For an input S3 object that\n contains multiple records, it creates an .out file only if the transform\n job succeeds on the entire file. When the input contains multiple S3 objects, the batch\n transform job processes the listed S3 objects and uploads only the output for\n successfully processed objects. If any object fails in the transform job batch transform\n marks the job as failed to prompt investigation.
The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix.
For every S3 object used as input for the transform job, batch transform stores the transformed data with an .out suffix in a corresponding subfolder in the location in the output prefix. For example, for the input data stored at s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform stores the transformed data at s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch transform doesn't upload partially processed objects. For an input S3 object that contains multiple records, it creates an .out file only if the transform job succeeds on the entire file. When the input contains multiple S3 objects, the batch transform job processes the listed S3 objects and uploads only the output for successfully processed objects. If any object fails in the transform job batch transform marks the job as failed to prompt investigation.
The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http\n call to transfer data from the transform job.
" + "smithy.api#documentation": "The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
" } }, "AssembleWith": { "target": "com.amazonaws.sagemaker#AssemblyType", "traits": { - "smithy.api#documentation": "Defines how to assemble the results of the transform job as a single S3 object. Choose\n a format that is most convenient to you. To concatenate the results in binary format,\n specify None. To add a newline character at the end of every transformed\n record, specify\n Line.
Defines how to assemble the results of the transform job as a single S3 object. Choose a format that is most convenient to you. To concatenate the results in binary format, specify None. To add a newline character at the end of every transformed record, specify Line.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using\n Amazon S3 server-side encryption. The KmsKeyId can be any of the following\n formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your\n role's account. For more information, see KMS-Managed Encryption Keys in the\n Amazon Simple Storage Service\n Developer Guide.\n
\nThe KMS key policy must grant permission to the IAM role that you specify in your\n\tCreateModel\n\t\trequest. For more information, see Using\n Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer\n Guide.
" + "smithy.api#documentation": "The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.
The KMS key policy must grant permission to the IAM role that you specify in your CreateModel request. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.
" } } }, @@ -71842,7 +71827,7 @@ "target": "com.amazonaws.sagemaker#TransformInstanceType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The ML compute instance type for the transform job. If you are using built-in\n algorithms to\n transform\n moderately sized datasets, we recommend using ml.m4.xlarge or\n ml.m5.largeinstance types.
The ML compute instance type for the transform job. If you are using built-in algorithms to transform moderately sized datasets, we recommend using ml.m4.xlarge or ml.m5.largeinstance types.
The number of\n ML\n compute instances to use in the transform job. The default value is\n 1, and the maximum is 100. For distributed transform jobs,\n specify a value greater than 1.
The number of ML compute instances to use in the transform job. The default value is 1, and the maximum is 100. For distributed transform jobs, specify a value greater than 1.
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume\n attached to the ML compute instance(s) that run the batch transform job.
\nCertain Nitro-based instances include local storage, dependent on the instance\n type. Local storage volumes are encrypted using a hardware module on the instance.\n You can't request a VolumeKmsKeyId when using an instance type with\n local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
\nFor more information about local instance storage encryption, see SSD\n Instance Store Volumes.
\n\n The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab\n
Key ARN:\n arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab\n
Alias name: alias/ExampleAlias\n
Alias name ARN:\n arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias\n
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a VolumeKmsKeyId when using an instance type with local storage.
For a list of instance types that support local instance storage, see Instance Store Volumes.
For more information about local instance storage encryption, see SSD Instance Store Volumes.
The VolumeKmsKeyId can be any of the following formats:
Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
Alias name: alias/ExampleAlias
Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
Specifies an option from a collection of preconfigured Amazon Machine Image (AMI)\n images. Each image is configured by Amazon Web Services with a set of software and driver\n versions.
\nAccelerator: GPU
\nNVIDIA driver version: 470
\nAccelerator: GPU
\nNVIDIA driver version: 535
\nSpecifies an option from a collection of preconfigured Amazon Machine Image (AMI) images. Each image is configured by Amazon Web Services with a set of software and driver versions.
Accelerator: GPU
NVIDIA driver version: 470
Accelerator: GPU
NVIDIA driver version: 535
Describes the resources, including ML instance types and ML instance count, to use for\n transform job.
" + "smithy.api#documentation": "Describes the resources, including ML instance types and ML instance count, to use for transform job.
" } }, "com.amazonaws.sagemaker#TransformS3DataSource": { @@ -71878,7 +71863,7 @@ "target": "com.amazonaws.sagemaker#S3DataType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "If you choose S3Prefix, S3Uri identifies a key name prefix.\n Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that\n is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch\n transform.
The following values are compatible: ManifestFile,\n S3Prefix\n
The following value is not compatible: AugmentedManifestFile\n
If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.
If you choose ManifestFile, S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.
The following values are compatible: ManifestFile, S3Prefix
The following value is not compatible: AugmentedManifestFile
Depending on the value specified for the S3DataType, identifies either a\n key name prefix or a manifest. For example:
A key name prefix might look like this:\n\t\ts3://bucketname/exampleprefix/.
A manifest might look like this:\n s3://bucketname/example.manifest\n
The manifest is an S3 object which is a JSON file with the following format:
\n\n [ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},\n
\n \"relative/path/to/custdata-1\",\n
\n \"relative/path/custdata-2\",\n
\n ...\n
\n \"relative/path/custdata-N\"\n
\n ]\n
The preceding JSON matches the following S3Uris:
\n s3://customer_bucket/some/prefix/relative/path/to/custdata-1\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-2\n
\n ...\n
\n s3://customer_bucket/some/prefix/relative/path/custdata-N\n
The complete set of S3Uris in this manifest constitutes the\n input data for the channel for this datasource. The object that each\n S3Uris points to must be readable by the IAM role that Amazon SageMaker\n uses to perform tasks on your behalf.
Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest. For example:
A key name prefix might look like this: s3://bucketname/exampleprefix/.
A manifest might look like this: s3://bucketname/example.manifest
The manifest is an S3 object which is a JSON file with the following format:
[ {\"prefix\": \"s3://customer_bucket/some/prefix/\"},
\"relative/path/to/custdata-1\",
\"relative/path/custdata-2\",
...
\"relative/path/custdata-N\"
]
The preceding JSON matches the following S3Uris:
s3://customer_bucket/some/prefix/relative/path/to/custdata-1
s3://customer_bucket/some/prefix/relative/path/custdata-2
...
s3://customer_bucket/some/prefix/relative/path/custdata-N
The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.
The name of the trial as displayed. If DisplayName isn't specified,\n TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
The list of tags that are associated with the trial. You can use Search\n API to search on the tags.
" + "smithy.api#documentation": "The list of tags that are associated with the trial. You can use Search API to search on the tags.
" } }, "TrialComponentSummaries": { "target": "com.amazonaws.sagemaker#TrialComponentSimpleSummaries", "traits": { - "smithy.api#documentation": "A list of the components associated with the trial. For each component, a summary of the\n component's properties is included.
" + "smithy.api#documentation": "A list of the components associated with the trial. For each component, a summary of the component's properties is included.
" } } }, @@ -71997,7 +71982,7 @@ "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the component as displayed. If DisplayName isn't specified,\n TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
An array of the parents of the component. A parent is a trial the component is associated\n with and the experiment the trial is part of. A component might not have any parents.
" + "smithy.api#documentation": "An array of the parents of the component. A parent is a trial the component is associated with and the experiment the trial is part of. A component might not have any parents.
" } }, "RunName": { @@ -72107,7 +72092,7 @@ } }, "traits": { - "smithy.api#documentation": "The properties of a trial component as returned by the Search\n API.
" + "smithy.api#documentation": "The properties of a trial component as returned by the Search API.
" } }, "com.amazonaws.sagemaker#TrialComponentArn": { @@ -72126,7 +72111,7 @@ "MediaType": { "target": "com.amazonaws.sagemaker#MediaType", "traits": { - "smithy.api#documentation": "The media type of the artifact, which indicates the type of data in the artifact file. The\n media type consists of a type and a subtype\n concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The\n type specifies the category of the media. The subtype specifies the kind of data.
" + "smithy.api#documentation": "The media type of the artifact, which indicates the type of data in the artifact file. The media type consists of a type and a subtype concatenated with a slash (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies the category of the media. The subtype specifies the kind of data.
" } }, "Value": { @@ -72139,7 +72124,7 @@ } }, "traits": { - "smithy.api#documentation": "Represents an input or output artifact of a trial component. You specify\n TrialComponentArtifact as part of the InputArtifacts and\n OutputArtifacts parameters in the CreateTrialComponent\n request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and\n instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
" + "smithy.api#documentation": "Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request.
Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
" } }, "com.amazonaws.sagemaker#TrialComponentArtifactValue": { @@ -72271,18 +72256,18 @@ "StringValue": { "target": "com.amazonaws.sagemaker#StringParameterValue", "traits": { - "smithy.api#documentation": "The string value of a categorical hyperparameter. If you specify a value for this\n parameter, you can't specify the NumberValue parameter.
The string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the NumberValue parameter.
The numeric value of a numeric hyperparameter. If you specify a value for this parameter,\n you can't specify the StringValue parameter.
The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the StringValue parameter.
The value of a hyperparameter. Only one of NumberValue or\n StringValue can be specified.
This object is specified in the CreateTrialComponent request.
" + "smithy.api#documentation": "The value of a hyperparameter. Only one of NumberValue or StringValue can be specified.
This object is specified in the CreateTrialComponent request.
" } }, "com.amazonaws.sagemaker#TrialComponentParameters": { @@ -72434,7 +72419,7 @@ } }, "traits": { - "smithy.api#documentation": "Detailed information about the source of a trial component. Either\n ProcessingJob or TrainingJob is returned.
Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
The name of the component as displayed. If DisplayName isn't specified,\n TrialComponentName is displayed.
The name of the component as displayed. If DisplayName isn't specified, TrialComponentName is displayed.
The status of the component. States include:
\nInProgress
\nCompleted
\nFailed
\nThe status of the component. States include:
InProgress
Completed
Failed
A summary of the properties of a trial component. To get all the properties, call the\n DescribeTrialComponent API and provide the\n TrialComponentName.
A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.
The name of the trial as displayed. If DisplayName isn't specified,\n TrialName is displayed.
The name of the trial as displayed. If DisplayName isn't specified, TrialName is displayed.
A summary of the properties of a trial. To get the complete set of properties, call the\n DescribeTrial API and provide the TrialName.
A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.
\n TtlDuration time unit.
TtlDuration time unit.
\n TtlDuration time value.
TtlDuration time value.
Time to live duration, where the record is hard deleted after the expiration time is\n reached; ExpiresAt = EventTime + TtlDuration. For\n information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
Time to live duration, where the record is hard deleted after the expiration time is reached; ExpiresAt = EventTime + TtlDuration. For information on HardDelete, see the DeleteRecord API in the Amazon SageMaker API Reference guide.
A flag to stop your hyperparameter tuning job if model performance fails to improve as\n evaluated against an objective function.
" + "smithy.api#documentation": "A flag to stop your hyperparameter tuning job if model performance fails to improve as evaluated against an objective function.
" } }, "ConvergenceDetected": { "target": "com.amazonaws.sagemaker#ConvergenceDetected", "traits": { - "smithy.api#documentation": "A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has\n detected that your model has converged as evaluated against your objective\n function.
" + "smithy.api#documentation": "A flag to top your hyperparameter tuning job if automatic model tuning (AMT) has detected that your model has converged as evaluated against your objective function.
" } } }, @@ -72764,18 +72749,18 @@ "UiTemplateS3Uri": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The Amazon S3 bucket location of the UI template, or worker task template. This is the\n template used to render the worker UI and tools for labeling job tasks. For more\n information about the contents of a UI template, see Creating Your Custom\n Labeling Task Template.
" + "smithy.api#documentation": "The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.
" } }, "HumanTaskUiArn": { "target": "com.amazonaws.sagemaker#HumanTaskUiArn", "traits": { - "smithy.api#documentation": "The ARN of the worker task template used to render the worker UI and tools for\n labeling job tasks.
\nUse this parameter when you are creating a labeling job for named entity recognition,\n 3D point cloud and video frame labeling jobs. Use your labeling job task type to select\n one of the following ARNs and use it with this parameter when you create a labeling job.\n Replace aws-region with the Amazon Web Services Region you are creating your labeling job\n in. For example, replace aws-region with us-west-1 if you\n create a labeling job in US West (N. California).
\n Named Entity Recognition\n
\nUse the following HumanTaskUiArn for named entity recognition labeling\n jobs:
\n arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition\n
\n 3D Point Cloud HumanTaskUiArns\n
\nUse this HumanTaskUiArn for 3D point cloud object detection and 3D point\n cloud object detection adjustment labeling jobs.
\n arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection\n
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point\n cloud object tracking adjustment labeling jobs.
\n arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking\n
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D\n point cloud semantic segmentation adjustment labeling jobs.
\n arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation\n
\n Video Frame HumanTaskUiArns\n
\nUse this HumanTaskUiArn for video frame object detection and video frame\n object detection adjustment labeling jobs.
\n arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection\n
Use this HumanTaskUiArn for video frame object tracking and video frame\n object tracking adjustment labeling jobs.
\n arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking\n
The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.
Use this parameter when you are creating a labeling job for named entity recognition, 3D point cloud and video frame labeling jobs. Use your labeling job task type to select one of the following ARNs and use it with this parameter when you create a labeling job. Replace aws-region with the Amazon Web Services Region you are creating your labeling job in. For example, replace aws-region with us-west-1 if you create a labeling job in US West (N. California).
Named Entity Recognition
Use the following HumanTaskUiArn for named entity recognition labeling jobs:
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
3D Point Cloud HumanTaskUiArns
Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
Video Frame HumanTaskUiArns
Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.
arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.
arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
Provided configuration information for the worker UI for a labeling job. Provide\n either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use\n HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use\n UiTemplateS3Uri to specify the location of a worker task template in\n Amazon S3.
Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri.
For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn.
For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.
Sets whether you can access the domain in Amazon SageMaker Studio:
\nYou can access the domain in Amazon SageMaker Studio. If you migrate the domain to\n Amazon SageMaker Unified Studio, you can access it in both studio interfaces.
\nYou can't access the domain in Amazon SageMaker Studio. If you migrate the domain to\n Amazon SageMaker Unified Studio, you can access it only in that studio interface.
\nTo migrate a domain to Amazon SageMaker Unified Studio, you specify the\n UnifiedStudioSettings data type when you use the UpdateDomain action.
" + "smithy.api#documentation": "Sets whether you can access the domain in Amazon SageMaker Studio:
You can access the domain in Amazon SageMaker Studio. If you migrate the domain to Amazon SageMaker Unified Studio, you can access it in both studio interfaces.
You can't access the domain in Amazon SageMaker Studio. If you migrate the domain to Amazon SageMaker Unified Studio, you can access it only in that studio interface.
To migrate a domain to Amazon SageMaker Unified Studio, you specify the UnifiedStudioSettings data type when you use the UpdateDomain action.
" } }, "DomainAccountId": { "target": "com.amazonaws.sagemaker#AccountId", "traits": { - "smithy.api#documentation": "The ID of the Amazon Web Services account that has the Amazon SageMaker Unified Studio\n domain. The default value, if you don't specify an ID, is the ID of the account that has the\n Amazon SageMaker AI domain.
" + "smithy.api#documentation": "The ID of the Amazon Web Services account that has the Amazon SageMaker Unified Studio domain. The default value, if you don't specify an ID, is the ID of the account that has the Amazon SageMaker AI domain.
" } }, "DomainRegion": { "target": "com.amazonaws.sagemaker#RegionName", "traits": { - "smithy.api#documentation": "The Amazon Web Services Region where the domain is located in Amazon SageMaker Unified\n Studio. The default value, if you don't specify a Region, is the Region where the Amazon SageMaker AI domain is located.
" + "smithy.api#documentation": "The Amazon Web Services Region where the domain is located in Amazon SageMaker Unified Studio. The default value, if you don't specify a Region, is the Region where the Amazon SageMaker AI domain is located.
" } }, "DomainId": { @@ -72871,24 +72856,24 @@ "ProjectId": { "target": "com.amazonaws.sagemaker#UnifiedStudioProjectId", "traits": { - "smithy.api#documentation": "The ID of the Amazon SageMaker Unified Studio project that corresponds to the\n domain.
" + "smithy.api#documentation": "The ID of the Amazon SageMaker Unified Studio project that corresponds to the domain.
" } }, "EnvironmentId": { "target": "com.amazonaws.sagemaker#UnifiedStudioEnvironmentId", "traits": { - "smithy.api#documentation": "The ID of the environment that Amazon SageMaker Unified Studio associates with the\n domain.
" + "smithy.api#documentation": "The ID of the environment that Amazon SageMaker Unified Studio associates with the domain.
" } }, "ProjectS3Path": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The location where Amazon S3 stores temporary execution data and other artifacts\n for the project that corresponds to the domain.
" + "smithy.api#documentation": "The location where Amazon S3 stores temporary execution data and other artifacts for the project that corresponds to the domain.
" } } }, "traits": { - "smithy.api#documentation": "The settings that apply to an Amazon SageMaker AI domain when you use it in Amazon\n SageMaker Unified Studio.
" + "smithy.api#documentation": "The settings that apply to an Amazon SageMaker AI domain when you use it in Amazon SageMaker Unified Studio.
" } }, "com.amazonaws.sagemaker#UpdateAction": { @@ -73149,7 +73134,7 @@ "InstanceGroupsToDelete": { "target": "com.amazonaws.sagemaker#ClusterInstanceGroupsToDelete", "traits": { - "smithy.api#documentation": "Specify the names of the instance groups to delete. \n Use a single , as the separator between multiple names.
Specify the names of the instance groups to delete. Use a single , as the separator between multiple names.
Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to\n use this API, see Update the SageMaker HyperPod platform software of a cluster.
\nThe UpgradeClusterSoftware API call may impact your SageMaker HyperPod cluster\n uptime and availability. Plan accordingly to mitigate potential disruptions to your\n workloads.
Updates the platform software of a SageMaker HyperPod cluster for security patching. To learn how to use this API, see Update the SageMaker HyperPod platform software of a cluster.
The UpgradeClusterSoftware API call may impact your SageMaker HyperPod cluster uptime and availability. Plan accordingly to mitigate potential disruptions to your workloads.
Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security\n patching.
", + "smithy.api#documentation": "Specify the name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster you want to update for security patching.
", "smithy.api#required": {} } }, @@ -73379,7 +73364,7 @@ "GitConfig": { "target": "com.amazonaws.sagemaker#GitConfigForUpdate", "traits": { - "smithy.api#documentation": "The configuration of the git repository, including the URL and the Amazon Resource\n Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the\n credentials used to access the repository. The secret must have a staging label of\n AWSCURRENT and must be in the following format:
\n {\"username\": UserName, \"password\":\n Password}\n
The configuration of the git repository, including the URL and the Amazon Resource Name (ARN) of the Amazon Web Services Secrets Manager secret that contains the credentials used to access the repository. The secret must have a staging label of AWSCURRENT and must be in the following format:
{\"username\": UserName, \"password\": Password}
Configuration of the compute allocation definition. This includes the resource sharing\n option, and the setting to preempt low priority tasks.
" + "smithy.api#documentation": "Configuration of the compute allocation definition. This includes the resource sharing option, and the setting to preempt low priority tasks.
" } }, "ComputeQuotaTarget": { @@ -73460,7 +73445,7 @@ "ActivationState": { "target": "com.amazonaws.sagemaker#ActivationState", "traits": { - "smithy.api#documentation": "The state of the compute allocation being described. Use to enable or disable compute\n allocation.
\nDefault is Enabled.
The state of the compute allocation being described. Use to enable or disable compute allocation.
Default is Enabled.
Output configuration for storing sample data collected by the fleet.
", + "smithy.api#documentation": "Output configuration for storing sample data collected by the fleet.
", "smithy.api#required": {} } }, "EnableIotRoleAlias": { "target": "com.amazonaws.sagemaker#EnableIotRoleAlias", "traits": { - "smithy.api#documentation": "Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. \n The name of the role alias generated will match this pattern: \n \"SageMakerEdge-{DeviceFleetName}\".
\nFor example, if your device fleet is called \"demo-fleet\", the name of \n the role alias will be \"SageMakerEdge-demo-fleet\".
" + "smithy.api#documentation": "Whether to create an Amazon Web Services IoT Role Alias during device fleet creation. The name of the role alias generated will match this pattern: \"SageMakerEdge-{DeviceFleetName}\".
For example, if your device fleet is called \"demo-fleet\", the name of the role alias will be \"SageMakerEdge-demo-fleet\".
" } } }, @@ -73710,7 +73695,7 @@ "AppSecurityGroupManagement": { "target": "com.amazonaws.sagemaker#AppSecurityGroupManagement", "traits": { - "smithy.api#documentation": "The entity that creates and manages the required security groups for inter-app\n communication in VPCOnly mode. Required when\n CreateDomain.AppNetworkAccessType is VPCOnly and\n DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is\n provided. If setting up the domain for use with RStudio, this value must be set to\n Service.
The entity that creates and manages the required security groups for inter-app communication in VPCOnly mode. Required when CreateDomain.AppNetworkAccessType is VPCOnly and DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided. If setting up the domain for use with RStudio, this value must be set to Service.
The VPC subnets that Studio uses for communication.
\nIf removing subnets, ensure there are no apps in the InService,\n Pending, or Deleting state.
The VPC subnets that Studio uses for communication.
If removing subnets, ensure there are no apps in the InService, Pending, or Deleting state.
Specifies the VPC used for non-EFS traffic.
\n\n PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access.
\n VpcOnly - All Studio traffic is through the specified VPC and\n subnets.
This configuration can only be modified if there are no apps in the\n InService, Pending, or Deleting state. The\n configuration cannot be updated if\n DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already\n set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is\n provided as part of the same request.
Specifies the VPC used for non-EFS traffic.
PublicInternetOnly - Non-EFS traffic is through a VPC managed by Amazon SageMaker AI, which allows direct internet access.
VpcOnly - All Studio traffic is through the specified VPC and subnets.
This configuration can only be modified if there are no apps in the InService, Pending, or Deleting state. The configuration cannot be updated if DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is already set or DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn is provided as part of the same request.
Indicates whether custom tag propagation is supported for the domain. Defaults to\n DISABLED.
Indicates whether custom tag propagation is supported for the domain. Defaults to DISABLED.
Deploys the EndpointConfig specified in the request to a new fleet of\n instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint\n configuration and then deletes the old instances using the previous\n EndpointConfig (there is no availability loss). For more information\n about how to control the update and traffic shifting process, see Update\n models in production.
When SageMaker receives the request, it sets the endpoint status to Updating.\n After updating the endpoint, it sets the status to InService. To check the\n status of an endpoint, use the DescribeEndpoint API.\n \n
You must not delete an EndpointConfig in use by an endpoint that is\n live or while the UpdateEndpoint or CreateEndpoint\n operations are being performed on the endpoint. To update an endpoint, you must\n create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or\n being created or updated you may lose visibility into the instance type the endpoint\n is using. The endpoint must be deleted in order to stop incurring charges.
Deploys the EndpointConfig specified in the request to a new fleet of instances. SageMaker shifts endpoint traffic to the new instances with the updated endpoint configuration and then deletes the old instances using the previous EndpointConfig (there is no availability loss). For more information about how to control the update and traffic shifting process, see Update models in production.
When SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To\n retain the variant properties of an endpoint when updating it, set\n RetainAllVariantProperties to true. To use the variant\n properties specified in a new EndpointConfig call when updating an\n endpoint, set RetainAllVariantProperties to false. The default\n is false.
When updating endpoint resources, enables or disables the retention of variant properties, such as the instance count or the variant weight. To retain the variant properties of an endpoint when updating it, set RetainAllVariantProperties to true. To use the variant properties specified in a new EndpointConfig call when updating an endpoint, set RetainAllVariantProperties to false. The default is false.
When you are updating endpoint resources with RetainAllVariantProperties,\n whose value is set to true, ExcludeRetainedVariantProperties\n specifies the list of type VariantProperty\n to override with the values provided by EndpointConfig. If you don't\n specify a value for ExcludeRetainedVariantProperties, no variant properties\n are overridden.
When you are updating endpoint resources with RetainAllVariantProperties, whose value is set to true, ExcludeRetainedVariantProperties specifies the list of type VariantProperty to override with the values provided by EndpointConfig. If you don't specify a value for ExcludeRetainedVariantProperties, no variant properties are overridden.
The deployment configuration for an endpoint, which contains the desired deployment\n strategy and rollback configurations.
" + "smithy.api#documentation": "The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.
" } }, "RetainDeploymentConfig": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Specifies whether to reuse the last deployment configuration. The default value is\n false (the configuration is not reused).
" + "smithy.api#documentation": "Specifies whether to reuse the last deployment configuration. The default value is false (the configuration is not reused).
" } } }, @@ -73851,7 +73836,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates variant weight of one or more variants associated with an existing\n endpoint, or capacity of one variant associated with an existing endpoint. When it\n receives the request, SageMaker sets the endpoint status to Updating. After\n updating the endpoint, it sets the status to InService. To check the status\n of an endpoint, use the DescribeEndpoint API.
Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.
Adds, updates, or removes the description of an experiment. Updates the display name of an\n experiment.
" + "smithy.api#documentation": "Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.
" } }, "com.amazonaws.sagemaker#UpdateExperimentRequest": { @@ -73928,7 +73913,7 @@ "DisplayName": { "target": "com.amazonaws.sagemaker#ExperimentEntityName", "traits": { - "smithy.api#documentation": "The name of the experiment as displayed. The name doesn't need to be unique. If\n DisplayName isn't specified, ExperimentName is displayed.
The name of the experiment as displayed. The name doesn't need to be unique. If DisplayName isn't specified, ExperimentName is displayed.
Updates the feature group by either adding features or updating the online store\n configuration. Use one of the following request parameters at a time while using the\n UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions\n request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the\n OnlineStoreConfig request parameter. If a TtlDuration is\n specified, the default TtlDuration applies for all records added to the\n feature group after the feature group is updated. If a record level\n TtlDuration exists from using the PutRecord API, the record\n level TtlDuration applies to that record instead of the default\n TtlDuration. To remove the default TtlDuration from an\n existing feature group, use the UpdateFeatureGroup API and set the\n TtlDuration\n Unit and Value to null.
Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the UpdateFeatureGroup API.
You can add features for your feature group using the FeatureAdditions request parameter. Features cannot be removed from a feature group.
You can update the online store configuration by using the OnlineStoreConfig request parameter. If a TtlDuration is specified, the default TtlDuration applies for all records added to the feature group after the feature group is updated. If a record level TtlDuration exists from using the PutRecord API, the record level TtlDuration applies to that record instead of the default TtlDuration. To remove the default TtlDuration from an existing feature group, use the UpdateFeatureGroup API and set the TtlDuration Unit and Value to null.
Updates the feature group. Updating a feature group is an asynchronous operation. When\n you get an HTTP 200 response, you've made a valid request. It takes some time after you've\n made a valid request for Feature Store to update the feature group.
" + "smithy.api#documentation": "Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.
" } }, "OnlineStoreConfig": { @@ -74047,7 +74032,7 @@ "target": "com.amazonaws.sagemaker#FeatureGroupNameOrArn", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the feature group containing the feature that\n you're updating.
", + "smithy.api#documentation": "The name or Amazon Resource Name (ARN) of the feature group containing the feature that you're updating.
", "smithy.api#required": {} } }, @@ -74074,7 +74059,7 @@ "ParameterRemovals": { "target": "com.amazonaws.sagemaker#FeatureParameterRemovals", "traits": { - "smithy.api#documentation": "A list of parameter keys that you can specify to remove parameters that describe your\n feature.
" + "smithy.api#documentation": "A list of parameter keys that you can specify to remove parameters that describe your feature.
" } } }, @@ -74116,7 +74101,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates SageMaker hub content (either a Model or Notebook\n resource).
You can update the metadata that describes the resource. In addition to the required request\n fields, specify at least one of the following fields to update:
\n\n HubContentDescription\n
\n HubContentDisplayName\n
\n HubContentMarkdown\n
\n HubContentSearchKeywords\n
\n SupportStatus\n
For more information about hubs, see Private curated hubs for foundation model access control in JumpStart.
\nIf you want to update a ModelReference resource in your hub, use the\n UpdateHubContentResource API instead.
Updates SageMaker hub content (either a Model or Notebook resource).
You can update the metadata that describes the resource. In addition to the required request fields, specify at least one of the following fields to update:
HubContentDescription
HubContentDisplayName
HubContentMarkdown
HubContentSearchKeywords
SupportStatus
For more information about hubs, see Private curated hubs for foundation model access control in JumpStart.
If you want to update a ModelReference resource in your hub, use the UpdateHubContentResource API instead.
Updates the contents of a SageMaker hub for a ModelReference resource.\n A ModelReference allows you to access public SageMaker JumpStart\n models from within your private hub.
When using this API, you can update the\n MinVersion field for additional flexibility in the model version. You shouldn't update\n any additional fields when using this API, because the metadata in your private hub\n should match the public JumpStart model's metadata.
If you want to update a Model or Notebook\n resource in your hub, use the UpdateHubContent API instead.
For more information about adding model references to your hub, see\n \n Add models to a private hub.
" + "smithy.api#documentation": "Updates the contents of a SageMaker hub for a ModelReference resource. A ModelReference allows you to access public SageMaker JumpStart models from within your private hub.
When using this API, you can update the MinVersion field for additional flexibility in the model version. You shouldn't update any additional fields when using this API, because the metadata in your private hub should match the public JumpStart model's metadata.
If you want to update a Model or Notebook resource in your hub, use the UpdateHubContent API instead.
For more information about adding model references to your hub, see Add models to a private hub.
" } }, "com.amazonaws.sagemaker#UpdateHubContentReferenceRequest": { @@ -74162,14 +74147,14 @@ "target": "com.amazonaws.sagemaker#HubContentType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The content type of the resource that you want to update. Only specify a\n ModelReference resource for this API. To update a Model\n or Notebook resource, use the UpdateHubContent API instead.
The content type of the resource that you want to update. Only specify a ModelReference resource for this API. To update a Model or Notebook resource, use the UpdateHubContent API instead.
The minimum hub content version of the referenced model that you want to use.\n The minimum version must be older than the latest available version of the referenced model.\n To support all versions of a model, set the value to 1.0.0.
The minimum hub content version of the referenced model that you want to use. The minimum version must be older than the latest available version of the referenced model. To support all versions of a model, set the value to 1.0.0.
The name of the SageMaker hub that contains the hub content you want to update.\n You can optionally use the hub ARN instead.
", + "smithy.api#documentation": "The name of the SageMaker hub that contains the hub content you want to update. You can optionally use the hub ARN instead.
", "smithy.api#required": {} } }, @@ -74224,7 +74209,7 @@ "target": "com.amazonaws.sagemaker#HubContentType", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The content type of the resource that you want to update. Only specify a\n Model or Notebook resource for this API. To\n update a ModelReference, use the\n UpdateHubContentReference API instead.
The content type of the resource that you want to update. Only specify a Model or Notebook resource for this API. To update a ModelReference, use the UpdateHubContentReference API instead.
The hub content version that you want to update. For example, if you have\n two versions of a resource in your hub, you can update the second version.
", + "smithy.api#documentation": "The hub content version that you want to update. For example, if you have two versions of a resource in your hub, you can update the second version.
", "smithy.api#required": {} } }, @@ -74362,7 +74347,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates the properties of a SageMaker AI image. To change the image's tags, use the\n AddTags and DeleteTags APIs.
" + "smithy.api#documentation": "Updates the properties of a SageMaker AI image. To change the image's tags, use the AddTags and DeleteTags APIs.
" } }, "com.amazonaws.sagemaker#UpdateImageRequest": { @@ -74371,7 +74356,7 @@ "DeleteProperties": { "target": "com.amazonaws.sagemaker#ImageDeletePropertyList", "traits": { - "smithy.api#documentation": "A list of properties to delete. Only the Description and\n DisplayName properties can be deleted.
A list of properties to delete. Only the Description and DisplayName properties can be deleted.
The availability of the image version specified by the maintainer.
\n\n NOT_PROVIDED: The maintainers did not provide a status for image version stability.
\n STABLE: The image version is stable.
\n TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
\n ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
The availability of the image version specified by the maintainer.
NOT_PROVIDED: The maintainers did not provide a status for image version stability.
STABLE: The image version is stable.
TO_BE_ARCHIVED: The image version is set to be archived. Custom image versions that are set to be archived are automatically archived after three months.
ARCHIVED: The image version is archived. Archived image versions are not searchable and are no longer actively supported.
Indicates SageMaker AI job type compatibility.
\n\n TRAINING: The image version is compatible with SageMaker AI training jobs.
\n INFERENCE: The image version is compatible with SageMaker AI inference jobs.
\n NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates SageMaker AI job type compatibility.
TRAINING: The image version is compatible with SageMaker AI training jobs.
INFERENCE: The image version is compatible with SageMaker AI inference jobs.
NOTEBOOK_KERNEL: The image version is compatible with SageMaker AI notebook kernels.
Indicates CPU or GPU compatibility.
\n\n CPU: The image version is compatible with CPU.
\n GPU: The image version is compatible with GPU.
Indicates CPU or GPU compatibility.
CPU: The image version is compatible with CPU.
GPU: The image version is compatible with GPU.
Details about the resources to deploy with this inference component, including the\n model, container, and compute resources.
" + "smithy.api#documentation": "Details about the resources to deploy with this inference component, including the model, container, and compute resources.
" } }, "RuntimeConfig": { @@ -74578,7 +74563,7 @@ "DeploymentConfig": { "target": "com.amazonaws.sagemaker#InferenceComponentDeploymentConfig", "traits": { - "smithy.api#documentation": "The deployment configuration for the inference component. The configuration contains the\n desired deployment strategy and rollback settings.
" + "smithy.api#documentation": "The deployment configuration for the inference component. The configuration contains the desired deployment strategy and rollback settings.
" } } }, @@ -74676,7 +74661,7 @@ } ], "traits": { - "smithy.api#documentation": "\n Updates an inference experiment that you created. The status of the inference experiment has to be either\n Created, Running. For more information on the status of an inference experiment,\n see DescribeInferenceExperiment.\n
Updates an inference experiment that you created. The status of the inference experiment has to be either Created, Running. For more information on the status of an inference experiment, see DescribeInferenceExperiment.
\n The duration for which the inference experiment will run. If the status of the inference experiment is\n Created, then you can update both the start and end dates. If the status of the inference\n experiment is Running, then you can update only the end date.\n
The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.
\n An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure\n configuration you want to update.\n
An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.
\n The configuration of ShadowMode inference experiment type. Use this field to specify a\n production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a\n percentage of the inference requests. For the shadow variant also specify the percentage of requests that\n Amazon SageMaker replicates.\n
The configuration of ShadowMode inference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.
The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow\n Tracking Server.
" + "smithy.api#documentation": "The new S3 URI for the general purpose bucket to use as the artifact store for the MLflow Tracking Server.
" } }, "TrackingServerSize": { @@ -74790,13 +74775,13 @@ "AutomaticModelRegistration": { "target": "com.amazonaws.sagemaker#Boolean", "traits": { - "smithy.api#documentation": "Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. \n To enable automatic model registration, set this value to True. \n To disable automatic model registration, set this value to False. \n If not specified, AutomaticModelRegistration defaults to False\n
Whether to enable or disable automatic registration of new MLflow models to the SageMaker Model Registry. To enable automatic model registration, set this value to True. To disable automatic model registration, set this value to False. If not specified, AutomaticModelRegistration defaults to False
The new weekly maintenance window start day and time to update. The maintenance window day and time should be \n in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
" + "smithy.api#documentation": "The new weekly maintenance window start day and time to update. The maintenance window day and time should be in Coordinated Universal Time (UTC) 24-hour standard time. For example: TUE:03:30.
" } } }, @@ -74838,7 +74823,7 @@ } ], "traits": { - "smithy.api#documentation": "Update an Amazon SageMaker Model Card.
\nYou cannot update both model card content and model card status in a single call.
\nUpdate an Amazon SageMaker Model Card.
You cannot update both model card content and model card status in a single call.
The updated model card content. Content must be in model card JSON schema and provided as a string.
\nWhen updating model card content, be sure to include the full content and not just updated content.
" + "smithy.api#documentation": "The updated model card content. Content must be in model card JSON schema and provided as a string.
When updating model card content, be sure to include the full content and not just updated content.
" } }, "ModelCardStatus": { "target": "com.amazonaws.sagemaker#ModelCardStatus", "traits": { - "smithy.api#documentation": "The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
\n\n Draft: The model card is a work in progress.
\n PendingReview: The model card is pending review.
\n Approved: The model card is approved.
\n Archived: The model card is archived. No more updates should be made to the model\n card, but it can still be exported.
The approval status of the model card within your organization. Different organizations might have different criteria for model card review and approval.
Draft: The model card is a work in progress.
PendingReview: The model card is pending review.
Approved: The model card is approved.
Archived: The model card is archived. No more updates should be made to the model card, but it can still be exported.
An array of additional Inference Specification objects to be added to the \n existing array additional Inference Specification. Total number of additional \n Inference Specifications can not exceed 15. Each additional Inference Specification \n specifies artifacts based on this model package that can be used on inference endpoints. \n Generally used with SageMaker Neo to store the compiled artifacts.
" + "smithy.api#documentation": "An array of additional Inference Specification objects to be added to the existing array additional Inference Specification. Total number of additional Inference Specifications can not exceed 15. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
" } }, "InferenceSpecification": { "target": "com.amazonaws.sagemaker#InferenceSpecification", "traits": { - "smithy.api#documentation": "Specifies details about inference jobs that you can run with models based on this\n model package, including the following information:
\nThe Amazon ECR paths of containers that contain the inference code and model\n artifacts.
\nThe instance types that the model package supports for transform jobs and\n real-time endpoints used for inference.
\nThe input and output content formats that the model package supports for\n inference.
\nSpecifies details about inference jobs that you can run with models based on this model package, including the following information:
The Amazon ECR paths of containers that contain the inference code and model artifacts.
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
The input and output content formats that the model package supports for inference.
The model card associated with the model package. Since\n ModelPackageModelCard is tied to a model package, it is a specific\n usage of a model card and its schema is simplified compared to the schema of\n ModelCard. The ModelPackageModelCard schema does not\n include model_package_details, and model_overview is composed\n of the model_creator and model_artifact properties. For more\n information about the model package model card schema, see Model\n package model card schema. For more information about the model card\n associated with the model package, see View the Details of a Model\n Version.
The model card associated with the model package. Since ModelPackageModelCard is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard. The ModelPackageModelCard schema does not include model_package_details, and model_overview is composed of the model_creator and model_artifact properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
Within EvaluationPeriod, how many execution failures will raise an\n alert.
Within EvaluationPeriod, how many execution failures will raise an alert.
The number of most recent monitoring executions to consider when evaluating alert\n status.
", + "smithy.api#documentation": "The number of most recent monitoring executions to consider when evaluating alert status.
", "smithy.api#required": {} } } @@ -75103,7 +75088,7 @@ "target": "com.amazonaws.sagemaker#MonitoringScheduleName", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services \n Region within an Amazon Web Services account.
", + "smithy.api#documentation": "The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.
", "smithy.api#required": {} } }, @@ -75111,7 +75096,7 @@ "target": "com.amazonaws.sagemaker#MonitoringScheduleConfig", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring \n job.
", + "smithy.api#documentation": "The configuration object that specifies the monitoring schedule and defines the monitoring job.
", "smithy.api#required": {} } } @@ -75150,7 +75135,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates a notebook instance. NotebookInstance updates include upgrading or\n downgrading the ML compute instance used for your notebook instance to accommodate\n changes in your workload requirements.
" + "smithy.api#documentation": "Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.
" } }, "com.amazonaws.sagemaker#UpdateNotebookInstanceInput": { @@ -75173,67 +75158,67 @@ "RoleArn": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The Amazon Resource Name (ARN) of the IAM role that SageMaker AI can assume to\n access the notebook instance. For more information, see SageMaker AI Roles.
\nTo be able to pass this role to SageMaker AI, the caller of this API must\n have the iam:PassRole permission.
The Amazon Resource Name (ARN) of the IAM role that SageMaker AI can assume to access the notebook instance. For more information, see SageMaker AI Roles.
To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
The name of a lifecycle configuration to associate with the notebook instance. For\n information about lifestyle configurations, see Step 2.1: (Optional)\n Customize a Notebook Instance.
" + "smithy.api#documentation": "The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
" } }, "DisassociateLifecycleConfig": { "target": "com.amazonaws.sagemaker#DisassociateNotebookInstanceLifecycleConfig", "traits": { - "smithy.api#documentation": "Set to true to remove the notebook instance lifecycle configuration\n currently associated with the notebook instance. This operation is idempotent. If you\n specify a lifecycle configuration that is not associated with the notebook instance when\n you call this method, it does not throw an error.
Set to true to remove the notebook instance lifecycle configuration currently associated with the notebook instance. This operation is idempotent. If you specify a lifecycle configuration that is not associated with the notebook instance when you call this method, it does not throw an error.
The size, in GB, of the ML storage volume to attach to the notebook instance. The\n default value is 5 GB. ML storage volumes are encrypted, so SageMaker AI can't\n determine the amount of available free space on the volume. Because of this, you can\n increase the volume size when you update a notebook instance, but you can't decrease the\n volume size. If you want to decrease the size of the ML storage volume in use, create a\n new notebook instance with the desired size.
" + "smithy.api#documentation": "The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. ML storage volumes are encrypted, so SageMaker AI can't determine the amount of available free space on the volume. Because of this, you can increase the volume size when you update a notebook instance, but you can't decrease the volume size. If you want to decrease the size of the ML storage volume in use, create a new notebook instance with the desired size.
" } }, "DefaultCodeRepository": { "target": "com.amazonaws.sagemaker#CodeRepositoryNameOrUrl", "traits": { - "smithy.api#documentation": "The Git repository to associate with the notebook instance as its default code\n repository. This can be either the name of a Git repository stored as a resource in your\n account, or the URL of a Git repository in Amazon Web Services CodeCommit\n or in any other Git repository. When you open a notebook instance, it opens in the\n directory that contains this repository. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "The Git repository to associate with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in Amazon Web Services CodeCommit or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "AdditionalCodeRepositories": { "target": "com.amazonaws.sagemaker#AdditionalCodeRepositoryNamesOrUrls", "traits": { - "smithy.api#documentation": "An array of up to three Git repositories to associate with the notebook instance.\n These can be either the names of Git repositories stored as resources in your account,\n or the URL of Git repositories in Amazon Web Services CodeCommit\n or in any other Git repository. These repositories are cloned at the same level as the\n default repository of your notebook instance. For more information, see Associating Git\n Repositories with SageMaker AI Notebook Instances.
" + "smithy.api#documentation": "An array of up to three Git repositories to associate with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in Amazon Web Services CodeCommit or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see Associating Git Repositories with SageMaker AI Notebook Instances.
" } }, "AcceleratorTypes": { "target": "com.amazonaws.sagemaker#NotebookInstanceAcceleratorTypes", "traits": { - "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify a list of the EI instance types to associate with\n this notebook instance.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types to associate with this notebook instance.
" } }, "DisassociateAcceleratorTypes": { "target": "com.amazonaws.sagemaker#DisassociateNotebookInstanceAcceleratorTypes", "traits": { - "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer\n available.
\nThis parameter was used to specify a list of the EI instance types to remove from this notebook\n instance.
" + "smithy.api#documentation": "This parameter is no longer supported. Elastic Inference (EI) is no longer available.
This parameter was used to specify a list of the EI instance types to remove from this notebook instance.
" } }, "DisassociateDefaultCodeRepository": { "target": "com.amazonaws.sagemaker#DisassociateDefaultCodeRepository", "traits": { - "smithy.api#documentation": "The name or URL of the default Git repository to remove from this notebook instance.\n This operation is idempotent. If you specify a Git repository that is not associated\n with the notebook instance when you call this method, it does not throw an error.
" + "smithy.api#documentation": "The name or URL of the default Git repository to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
" } }, "DisassociateAdditionalCodeRepositories": { "target": "com.amazonaws.sagemaker#DisassociateAdditionalCodeRepositories", "traits": { - "smithy.api#documentation": "A list of names or URLs of the default Git repositories to remove from this notebook\n instance. This operation is idempotent. If you specify a Git repository that is not\n associated with the notebook instance when you call this method, it does not throw an\n error.
" + "smithy.api#documentation": "A list of names or URLs of the default Git repositories to remove from this notebook instance. This operation is idempotent. If you specify a Git repository that is not associated with the notebook instance when you call this method, it does not throw an error.
" } }, "RootAccess": { "target": "com.amazonaws.sagemaker#RootAccess", "traits": { - "smithy.api#documentation": "Whether root access is enabled or disabled for users of the notebook instance. The\n default value is Enabled.
If you set this to Disabled, users don't have root access on the\n notebook instance, but lifecycle configuration scripts still run with root\n permissions.
Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.
If you set this to Disabled, users don't have root access on the notebook instance, but lifecycle configuration scripts still run with root permissions.
The shell script that runs only once, when you create a notebook instance. The shell\n script must be a base64-encoded string.
" + "smithy.api#documentation": "The shell script that runs only once, when you create a notebook instance. The shell script must be a base64-encoded string.
" } }, "OnStart": { "target": "com.amazonaws.sagemaker#NotebookInstanceLifecycleConfigList", "traits": { - "smithy.api#documentation": "The shell script that runs every time you start a notebook instance, including when\n you create the notebook instance. The shell script must be a base64-encoded\n string.
" + "smithy.api#documentation": "The shell script that runs every time you start a notebook instance, including when you create the notebook instance. The shell script must be a base64-encoded string.
" } } }, @@ -75323,7 +75308,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates all of the SageMaker Partner AI Apps in an account.
" + "smithy.api#documentation": "Updates all of the SageMaker Partner AI Apps in an account.
" } }, "com.amazonaws.sagemaker#UpdatePartnerAppRequest": { @@ -75371,7 +75356,7 @@ "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per\n resource.
" + "smithy.api#documentation": "Each tag consists of a key and an optional value. Tag keys must be unique per resource.
" } } }, @@ -75459,7 +75444,7 @@ "ParallelismConfiguration": { "target": "com.amazonaws.sagemaker#ParallelismConfiguration", "traits": { - "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration \n of the parent pipeline for this specific run.
" + "smithy.api#documentation": "This configuration, if specified, overrides the parallelism configuration of the parent pipeline for this specific run.
" } } }, @@ -75507,7 +75492,7 @@ "PipelineDefinitionS3Location": { "target": "com.amazonaws.sagemaker#PipelineDefinitionS3Location", "traits": { - "smithy.api#documentation": "The location of the pipeline definition stored in Amazon S3. If specified, \n SageMaker will retrieve the pipeline definition from this location.
" + "smithy.api#documentation": "The location of the pipeline definition stored in Amazon S3. If specified, SageMaker will retrieve the pipeline definition from this location.
" } }, "PipelineDescription": { @@ -75561,7 +75546,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates a machine learning (ML) project that is created from a template that \n sets up an ML pipeline from training to deploying an approved model.
\nYou must not update a project that is in use. If you update the\n ServiceCatalogProvisioningUpdateDetails of a project that is active\n or being created, or updated, you may lose resources already created by the\n project.
Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
You must not update a project that is in use. If you update the ServiceCatalogProvisioningUpdateDetails of a project that is active or being created, or updated, you may lose resources already created by the project.
The product ID and provisioning artifact ID to provision a service catalog. \n The provisioning artifact ID will default to the latest provisioning artifact \n ID of the product, if you don't provide the provisioning artifact ID. For more \n information, see What is Amazon Web Services Service Catalog.\n
" + "smithy.api#documentation": "The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
" } }, "Tags": { "target": "com.amazonaws.sagemaker#TagList", "traits": { - "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your \n Amazon Web Services resources in different ways, for example, by purpose, owner, or \n environment. For more information, see Tagging Amazon Web Services Resources.\n In addition, the project must have tag update constraints set in order to include this \n parameter in the request. For more information, see Amazon Web Services Service \n Catalog Tag Update Constraints.
" + "smithy.api#documentation": "An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.
" } } }, @@ -75634,7 +75619,7 @@ } ], "traits": { - "smithy.api#documentation": "Updates the settings of a space.
\nYou can't edit the app type of a space in the SpaceSettings.
Updates the settings of a space.
You can't edit the app type of a space in the SpaceSettings.
Update a model training job to request a new Debugger profiling configuration or to\n change warm pool retention length.
" + "smithy.api#documentation": "Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.
" } }, "com.amazonaws.sagemaker#UpdateTrainingJobRequest": { @@ -75721,25 +75706,25 @@ "ProfilerConfig": { "target": "com.amazonaws.sagemaker#ProfilerConfigForUpdate", "traits": { - "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and\n storage paths.
" + "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
" } }, "ProfilerRuleConfigurations": { "target": "com.amazonaws.sagemaker#ProfilerRuleConfigurations", "traits": { - "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework\n metrics.
" + "smithy.api#documentation": "Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
" } }, "ResourceConfig": { "target": "com.amazonaws.sagemaker#ResourceConfigForUpdate", "traits": { - "smithy.api#documentation": "The training job ResourceConfig to update warm pool retention\n length.
The training job ResourceConfig to update warm pool retention length.
Configuration for remote debugging while the training job is running. You can update\n the remote debugging configuration when the SecondaryStatus of the job is\n Downloading or Training.To learn more about the remote\n debugging functionality of SageMaker, see Access a training container\n through Amazon Web Services Systems Manager (SSM) for remote\n debugging.
Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the SecondaryStatus of the job is Downloading or Training.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
The name of the component as displayed. The name doesn't need to be unique. If\n DisplayName isn't specified, TrialComponentName is\n displayed.
The name of the component as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialComponentName is displayed.
The name of the trial as displayed. The name doesn't need to be unique. If\n DisplayName isn't specified, TrialName is displayed.
The name of the trial as displayed. The name doesn't need to be unique. If DisplayName isn't specified, TrialName is displayed.
Use this operation to update your workforce. You can use this operation to \n require that workers use specific IP addresses to work on tasks\n and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
\nThe worker portal is now supported in VPC and public internet.
\n Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. \n You specify allowed IP addresses by creating a list of up to ten CIDRs.\n By default, a workforce isn't restricted to specific IP addresses. If you specify a\n range of IP addresses, workers who attempt to access tasks using any IP address outside\n the specified range are denied and get a Not Found error message on\n the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as \"10.0.0.0/16\".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
\nUse OidcConfig to update the configuration of a workforce created using\n your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams\n associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
\nAfter restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you\n can view details about your update workforce using the DescribeWorkforce\n operation.
\nThis operation only applies to private workforces.
\nUse this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration.
The worker portal is now supported in VPC and public internet.
Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs. By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal.
To restrict access to all the workers in public internet, add the SourceIpConfig CIDR value as \"10.0.0.0/16\".
Amazon SageMaker does not support Source Ip restriction for worker portals in VPC.
Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP.
You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the DeleteWorkteam operation.
After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the DescribeWorkforce operation.
This operation only applies to private workforces.
The name of the private workforce that you want to update. You can find your workforce\n name by using the ListWorkforces operation.
", + "smithy.api#documentation": "The name of the private workforce that you want to update. You can find your workforce name by using the ListWorkforces operation.
", "smithy.api#required": {} } }, "SourceIpConfig": { "target": "com.amazonaws.sagemaker#SourceIpConfig", "traits": { - "smithy.api#documentation": "A list of one to ten worker IP address ranges (CIDRs) that can be used to\n access tasks assigned to this workforce.
\nMaximum: Ten CIDR values
" + "smithy.api#documentation": "A list of one to ten worker IP address ranges (CIDRs) that can be used to access tasks assigned to this workforce.
Maximum: Ten CIDR values
" } }, "OidcConfig": { "target": "com.amazonaws.sagemaker#OidcConfig", "traits": { - "smithy.api#documentation": "Use this parameter to update your OIDC Identity Provider (IdP) \n configuration for a workforce made using your own IdP.
" + "smithy.api#documentation": "Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.
" } }, "WorkforceVpcConfig": { @@ -76054,7 +76039,7 @@ "target": "com.amazonaws.sagemaker#Workforce", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A single private workforce. You can create one private work force in each Amazon Web Services Region. By default,\n any workforce-related API operation used in a specific region will apply to the\n workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
", + "smithy.api#documentation": "A single private workforce. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
", "smithy.api#required": {} } } @@ -76094,7 +76079,7 @@ "MemberDefinitions": { "target": "com.amazonaws.sagemaker#MemberDefinitions", "traits": { - "smithy.api#documentation": "A list of MemberDefinition objects that contains objects that identify\n the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). \n For private workforces created using Amazon Cognito use\n CognitoMemberDefinition. For workforces created using your own OIDC identity\n provider (IdP) use OidcMemberDefinition. You should not provide input\n for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito\n user groups within the user pool used to create a workforce. All of the\n CognitoMemberDefinition objects that make up the member definition must\n have the same ClientId and UserPool values. To add a Amazon\n Cognito user group to an existing worker pool, see Adding groups to a User\n Pool. For more information about user pools, see Amazon Cognito User\n Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want\n to include in your private work team in OidcMemberDefinition by listing\n those groups in Groups. Be aware that user groups that are already in the\n work team must also be listed in Groups when you make this request to\n remain on the work team. If you do not include these user groups, they will no longer be\n associated with the work team you update.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not provide input for both of these parameters in a single request.
For workforces created using Amazon Cognito, private work teams correspond to Amazon Cognito user groups within the user pool used to create a workforce. All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values. To add a Amazon Cognito user group to an existing worker pool, see Adding groups to a User Pool. For more information about user pools, see Amazon Cognito User Pools.
For workforces created using your own OIDC IdP, specify the user groups that you want to include in your private work team in OidcMemberDefinition by listing those groups in Groups. Be aware that user groups that are already in the work team must also be listed in Groups when you make this request to remain on the work team. If you do not include these user groups, they will no longer be associated with the work team you update.
The IAM Identity details associated with the user. These details are\n associated with model package groups, model packages, and project entities only.
" + "smithy.api#documentation": "The IAM Identity details associated with the user. These details are associated with model package groups, model packages, and project entities only.
" } } }, "traits": { - "smithy.api#documentation": "Information about the user who created or modified an experiment, trial, trial\n component, lineage group, project, or model card.
" + "smithy.api#documentation": "Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.
" } }, "com.amazonaws.sagemaker#UserProfileArn": { @@ -76312,13 +76297,13 @@ "ExecutionRole": { "target": "com.amazonaws.sagemaker#RoleArn", "traits": { - "smithy.api#documentation": "The execution role for the user.
\nSageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
" + "smithy.api#documentation": "The execution role for the user.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
" } }, "SecurityGroups": { "target": "com.amazonaws.sagemaker#SecurityGroupIds", "traits": { - "smithy.api#documentation": "The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for\n communication.
\nOptional when the CreateDomain.AppNetworkAccessType parameter is set to\n PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to\n VpcOnly, unless specified as part of the DefaultUserSettings for\n the domain.
Amazon SageMaker AI adds a security group to allow NFS traffic from Amazon SageMaker AI Studio. Therefore, the number of security groups that you can specify is one less than the\n maximum number shown.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "The security groups for the Amazon Virtual Private Cloud (VPC) that the domain uses for communication.
Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly.
Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly, unless specified as part of the DefaultUserSettings for the domain.
Amazon SageMaker AI adds a security group to allow NFS traffic from Amazon SageMaker AI Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "SharingSettings": { @@ -76348,7 +76333,7 @@ "RStudioServerProAppSettings": { "target": "com.amazonaws.sagemaker#RStudioServerProAppSettings", "traits": { - "smithy.api#documentation": "A collection of settings that configure user interaction with the\n RStudioServerPro app.
A collection of settings that configure user interaction with the RStudioServerPro app.
The Canvas app settings.
\nSageMaker applies these settings only to private spaces that SageMaker creates for the Canvas\n app.
" + "smithy.api#documentation": "The Canvas app settings.
SageMaker applies these settings only to private spaces that SageMaker creates for the Canvas app.
" } }, "CodeEditorAppSettings": { "target": "com.amazonaws.sagemaker#CodeEditorAppSettings", "traits": { - "smithy.api#documentation": "The Code Editor application settings.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "The Code Editor application settings.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "JupyterLabAppSettings": { "target": "com.amazonaws.sagemaker#JupyterLabAppSettings", "traits": { - "smithy.api#documentation": "The settings for the JupyterLab application.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "The settings for the JupyterLab application.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "SpaceStorageSettings": { "target": "com.amazonaws.sagemaker#DefaultSpaceStorageSettings", "traits": { - "smithy.api#documentation": "The storage settings for a space.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "The storage settings for a space.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "DefaultLandingUri": { "target": "com.amazonaws.sagemaker#LandingUri", "traits": { - "smithy.api#documentation": "The default experience that the user is directed to when accessing the domain. The\n supported values are:
\n\n studio::: Indicates that Studio is the default experience. This value can\n only be passed if StudioWebPortal is set to ENABLED.
\n app:JupyterServer:: Indicates that Studio Classic is the default\n experience.
The default experience that the user is directed to when accessing the domain. The supported values are:
studio::: Indicates that Studio is the default experience. This value can only be passed if StudioWebPortal is set to ENABLED.
app:JupyterServer:: Indicates that Studio Classic is the default experience.
Whether the user can access Studio. If this value is set to DISABLED, the\n user cannot access Studio, even if that is the default experience for the domain.
Whether the user can access Studio. If this value is set to DISABLED, the user cannot access Studio, even if that is the default experience for the domain.
Details about the POSIX identity that is used for file system operations.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "Details about the POSIX identity that is used for file system operations.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "CustomFileSystemConfigs": { "target": "com.amazonaws.sagemaker#CustomFileSystemConfigs", "traits": { - "smithy.api#documentation": "The settings for assigning a custom file system to a user profile. Permitted users can\n access this file system in Amazon SageMaker AI Studio.
\nSageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" + "smithy.api#documentation": "The settings for assigning a custom file system to a user profile. Permitted users can access this file system in Amazon SageMaker AI Studio.
SageMaker applies these settings only to private spaces that the user creates in the domain. SageMaker doesn't apply these settings to shared spaces.
" } }, "StudioWebPortalSettings": { "target": "com.amazonaws.sagemaker#StudioWebPortalSettings", "traits": { - "smithy.api#documentation": "Studio settings. If these settings are applied on a user level, they take priority over\n the settings applied on a domain level.
" + "smithy.api#documentation": "Studio settings. If these settings are applied on a user level, they take priority over the settings applied on a domain level.
" } }, "AutoMountHomeEFS": { "target": "com.amazonaws.sagemaker#AutoMountHomeEFS", "traits": { - "smithy.api#documentation": "Indicates whether auto-mounting of an EFS volume is supported for the user profile. The\n DefaultAsDomain value is only supported for user profiles. Do not use the\n DefaultAsDomain value when setting this parameter for a domain.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
" + "smithy.api#documentation": "Indicates whether auto-mounting of an EFS volume is supported for the user profile. The DefaultAsDomain value is only supported for user profiles. Do not use the DefaultAsDomain value when setting this parameter for a domain.
SageMaker applies this setting only to private spaces that the user creates in the domain. SageMaker doesn't apply this setting to shared spaces.
" } } }, "traits": { - "smithy.api#documentation": "A collection of settings that apply to users in a domain. These settings are specified\n when the CreateUserProfile API is called, and as DefaultUserSettings\n when the CreateDomain API is called.
\n SecurityGroups is aggregated when specified in both calls. For all other\n settings in UserSettings, the values specified in CreateUserProfile\n take precedence over those specified in CreateDomain.
A collection of settings that apply to users in a domain. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the CreateDomain API is called.
SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.
The type of variant property. The supported values are:
\n\n DesiredInstanceCount: Overrides the existing variant instance\n counts using the InitialInstanceCount values in the\n ProductionVariants of CreateEndpointConfig.
\n DesiredWeight: Overrides the existing variant weights using the\n InitialVariantWeight values in the\n ProductionVariants of CreateEndpointConfig.
\n DataCaptureConfig: (Not currently supported.)
The type of variant property. The supported values are:
DesiredInstanceCount: Overrides the existing variant instance counts using the InitialInstanceCount values in the ProductionVariants of CreateEndpointConfig.
DesiredWeight: Overrides the existing variant weights using the InitialVariantWeight values in the ProductionVariants of CreateEndpointConfig.
DataCaptureConfig: (Not currently supported.)
Specifies a production variant property type for an Endpoint.
\nIf you are updating an endpoint with the RetainAllVariantProperties\n option of UpdateEndpointInput set to true, the\n VariantProperty objects listed in the\n ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the\n endpoint.
Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the RetainAllVariantProperties option of UpdateEndpointInput set to true, the VariantProperty objects listed in the ExcludeRetainedVariantProperties parameter of UpdateEndpointInput override the existing variant properties of the endpoint.
The type of the lineage entity resource. For example: DataSet, Model, Endpoint, \n etc...
The type of the lineage entity resource. For example: DataSet, Model, Endpoint, etc...
The key that specifies the tag that you're using to filter the search results. It must be\n in the following format: Tags..
The key that specifies the tag that you're using to filter the search results. It must be in the following format: Tags.<key>.
The list of key-value pairs used to filter your search results. If a search result\n contains a key from your list, it is included in the final search response if the value\n associated with the key in the result matches the value you specified. If the value doesn't\n match, the result is excluded from the search response. Any resources that don't have a key\n from the list that you've provided will also be included in the search response.
" + "smithy.api#documentation": "The list of key-value pairs used to filter your search results. If a search result contains a key from your list, it is included in the final search response if the value associated with the key in the result matches the value you specified. If the value doesn't match, the result is excluded from the search response. Any resources that don't have a key from the list that you've provided will also be included in the search response.
" } }, "com.amazonaws.sagemaker#VisibilityConditionsKey": { @@ -76746,7 +76731,7 @@ "target": "com.amazonaws.sagemaker#VpcSecurityGroupIds", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security\n groups for the VPC that is specified in the Subnets field.
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
The ID of the subnets in the VPC to which you want to connect your training job or\n model. For information about the availability of specific instance types, see Supported\n Instance Types and Availability Zones.
", + "smithy.api#documentation": "The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.
", "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources\n have access to. You can control access to and from your resources by configuring a VPC.\n For more information, see Give SageMaker Access to\n Resources in your Amazon VPC.
" + "smithy.api#documentation": "Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.
" } }, "com.amazonaws.sagemaker#VpcId": { @@ -76851,14 +76836,14 @@ "target": "com.amazonaws.sagemaker#WarmPoolResourceStatus", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "The status of the warm pool.
\n\n InUse: The warm pool is in use for the training job.
\n Available: The warm pool is available to reuse for a matching\n training job.
\n Reused: The warm pool moved to a matching training job for\n reuse.
\n Terminated: The warm pool is no longer available. Warm pools are\n unavailable if they are terminated by a user, terminated for a patch update, or\n terminated for exceeding the specified\n KeepAlivePeriodInSeconds.
The status of the warm pool.
InUse: The warm pool is in use for the training job.
Available: The warm pool is available to reuse for a matching training job.
Reused: The warm pool moved to a matching training job for reuse.
Terminated: The warm pool is no longer available. Warm pools are unavailable if they are terminated by a user, terminated for a patch update, or terminated for exceeding the specified KeepAlivePeriodInSeconds.
The billable time in seconds used by the warm pool. Billable time refers to the\n absolute wall-clock time.
\nMultiply ResourceRetainedBillableTimeInSeconds by the number of instances\n (InstanceCount) in your training cluster to get the total compute time\n SageMaker bills you if you run warm pool training. The formula is as follows:\n ResourceRetainedBillableTimeInSeconds * InstanceCount.
The billable time in seconds used by the warm pool. Billable time refers to the absolute wall-clock time.
Multiply ResourceRetainedBillableTimeInSeconds by the number of instances (InstanceCount) in your training cluster to get the total compute time SageMaker bills you if you run warm pool training. The formula is as follows: ResourceRetainedBillableTimeInSeconds * InstanceCount.
The most recent date that UpdateWorkforce was used to\n successfully add one or more IP address ranges (CIDRs) to a private workforce's\n allow list.
" + "smithy.api#documentation": "The most recent date that UpdateWorkforce was used to successfully add one or more IP address ranges (CIDRs) to a private workforce's allow list.
" } }, "SourceIpConfig": { "target": "com.amazonaws.sagemaker#SourceIpConfig", "traits": { - "smithy.api#documentation": "A list of one to ten IP address ranges (CIDRs) to be added to the\n workforce allow list. By default, a workforce isn't restricted to specific IP addresses.
" + "smithy.api#documentation": "A list of one to ten IP address ranges (CIDRs) to be added to the workforce allow list. By default, a workforce isn't restricted to specific IP addresses.
" } }, "SubDomain": { @@ -76946,7 +76931,7 @@ "CognitoConfig": { "target": "com.amazonaws.sagemaker#CognitoConfig", "traits": { - "smithy.api#documentation": "The configuration of an Amazon Cognito workforce. \n A single Cognito workforce is created using and corresponds to a single\n \n Amazon Cognito user pool.
" + "smithy.api#documentation": "The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
" } }, "OidcConfig": { @@ -76981,7 +76966,7 @@ } }, "traits": { - "smithy.api#documentation": "A single private workforce, which is automatically created when you create your first\n private work team. You can create one private work force in each Amazon Web Services Region. By default,\n any workforce-related API operation used in a specific region will apply to the\n workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
" + "smithy.api#documentation": "A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each Amazon Web Services Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.
" } }, "com.amazonaws.sagemaker#WorkforceArn": { @@ -77189,7 +77174,7 @@ "S3ArtifactPath": { "target": "com.amazonaws.sagemaker#S3Uri", "traits": { - "smithy.api#documentation": "The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts\n existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users\n must log out and log back in to apply the new location.
" + "smithy.api#documentation": "The Amazon S3 bucket used to store artifacts generated by Canvas. Updating the Amazon S3 location impacts existing configuration settings, and Canvas users no longer have access to their artifacts. Canvas users must log out and log back in to apply the new location.
" } }, "S3KmsKeyId": { @@ -77218,7 +77203,7 @@ "target": "com.amazonaws.sagemaker#MemberDefinitions", "traits": { "smithy.api#clientOptional": {}, - "smithy.api#documentation": "A list of MemberDefinition objects that contains objects that identify\n the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). \n For private workforces created using Amazon Cognito use\n CognitoMemberDefinition. For workforces created using your own OIDC identity\n provider (IdP) use OidcMemberDefinition.
A list of MemberDefinition objects that contains objects that identify the workers that make up the work team.
Workforces can be created using Amazon Cognito or your own OIDC Identity Provider (IdP). For private workforces created using Amazon Cognito use CognitoMemberDefinition. For workforces created using your own OIDC identity provider (IdP) use OidcMemberDefinition.
The URI of the labeling job's user interface. Workers open this URI to start labeling\n your data objects.
" + "smithy.api#documentation": "The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.
" } }, "CreateDate": { @@ -77271,7 +77256,7 @@ "NotificationConfiguration": { "target": "com.amazonaws.sagemaker#NotificationConfiguration", "traits": { - "smithy.api#documentation": "Configures SNS notifications of available or expiring work items for work\n teams.
" + "smithy.api#documentation": "Configures SNS notifications of available or expiring work items for work teams.
" } }, "WorkerAccessConfiguration": { diff --git a/codegen/sdk-codegen/aws-models/supplychain.json b/codegen/sdk-codegen/aws-models/supplychain.json index bde2cae0a89b..a8de0902cc4b 100644 --- a/codegen/sdk-codegen/aws-models/supplychain.json +++ b/codegen/sdk-codegen/aws-models/supplychain.json @@ -372,7 +372,22 @@ "target": { "targetType": "DATASET", "datasetTarget": { - "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + "options": { + "loadType": "REPLACE", + "dedupeRecords": true, + "dedupeStrategy": { + "type": "FIELD_PRIORITY", + "fieldPriority": { + "fields": [ + { + "name": "eff_start_date", + "sortOrder": "DESC" + } + ] + } + } + } } }, "tags": { @@ -487,6 +502,9 @@ { "target": "com.amazonaws.supplychain#InternalServerException" }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, { "target": "com.amazonaws.supplychain#ServiceQuotaExceededException" }, @@ -708,6 +726,32 @@ "name": "creation_time", "type": "TIMESTAMP", "isRequired": false + }, + { + "name": "quantity", + "type": "LONG", + "isRequired": false + } + ], + "primaryKeys": [ + { + "name": "id" + } + ] + }, + "partitionSpec": { + "fields": [ + { + "name": "creation_time", + "transform": { + "type": "DAY" + } + }, + { + "name": "description", + "transform": { + "type": "IDENTITY" + } } ] }, @@ -747,6 +791,32 @@ "name": "creation_time", "type": "TIMESTAMP", "isRequired": false + }, + { + "name": "quantity", + "type": "LONG", + "isRequired": false + } + ], + "primaryKeys": [ + { + "name": "id" + } + ] + }, + "partitionSpec": { + "fields": [ + { + "name": "creation_time", + "transform": { + "type": "DAY" + } + }, + { + "name": "description", + "transform": { + "type": "IDENTITY" + } } ] } @@ -774,9 +844,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of the dataset.
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe custom schema of the data lake dataset and is only required when the name space is default.
" + "smithy.api#documentation": "The custom schema of the data lake dataset and required for dataset in default and custom namespaces.
" } }, "description": { @@ -801,6 +871,12 @@ "smithy.api#documentation": "The description of the dataset.
" } }, + "partitionSpec": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionSpec", + "traits": { + "smithy.api#documentation": "The partition specification of the dataset. Partitioning can effectively improve the dataset query performance by reducing the amount of data scanned during query execution. But partitioning or not will affect how data get ingested by data ingestion methods, such as SendDataIntegrationEvent's dataset UPSERT will upsert records within partition (instead of within whole dataset). For more details, refer to those data ingestion documentations.
" + } + }, "tags": { "target": "com.amazonaws.supplychain#TagMap", "traits": { @@ -831,6 +907,123 @@ "smithy.api#output": {} } }, + "com.amazonaws.supplychain#CreateDataLakeNamespace": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#CreateDataLakeNamespaceRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#CreateDataLakeNamespaceResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#ConflictException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ServiceQuotaExceededException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically create an Amazon Web Services Supply Chain data lake namespace. Developers can create the namespaces for a given instance ID.
", + "smithy.api#examples": [ + { + "title": "Create a data lake namespace", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "description": "This is my AWS Supply Chain namespace", + "tags": { + "tagKey1": "tagValue1", + "tagKey2": "tagValue2" + } + }, + "output": { + "namespace": { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "description": "This is my AWS Supply Chain namespace", + "createdTime": 1.736892560751e9, + "lastModifiedTime": 1.736892560751e9 + } + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "PUT", + "uri": "/api/datalake/instance/{instanceId}/namespaces/{name}" + }, + "smithy.api#idempotent": {} + } + }, + "com.amazonaws.supplychain#CreateDataLakeNamespaceRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The name of the namespace. Noted you cannot create namespace with name starting with asc, default, scn, aws, amazon, amzn\n
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "description": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceDescription", + "traits": { + "smithy.api#documentation": "The description of the namespace.
" + } + }, + "tags": { + "target": "com.amazonaws.supplychain#TagMap", + "traits": { + "smithy.api#documentation": "The tags of the namespace.
", + "smithy.api#notProperty": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters for CreateDataLakeNamespace.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#CreateDataLakeNamespaceResponse": { + "type": "structure", + "members": { + "namespace": { + "target": "com.amazonaws.supplychain#DataLakeNamespace", + "traits": { + "smithy.api#documentation": "The detail of created namespace.
", + "smithy.api#nestedProperties": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of CreateDataLakeNamespace.
", + "smithy.api#output": {} + } + }, "com.amazonaws.supplychain#CreateInstance": { "type": "operation", "input": { @@ -974,107 +1167,276 @@ "smithy.api#output": {} } }, - "com.amazonaws.supplychain#DataIntegrationEventData": { + "com.amazonaws.supplychain#DataIntegrationDatasetArn": { "type": "string", "traits": { "smithy.api#length": { - "min": 1, - "max": 1048576 + "min": 20, + "max": 1011 }, - "smithy.api#sensitive": {} - } - }, - "com.amazonaws.supplychain#DataIntegrationEventGroupId": { - "type": "string", - "traits": { - "smithy.api#length": { - "min": 1, - "max": 255 - } + "smithy.api#pattern": "^arn:aws:scn:([a-z0-9-]+):([0-9]+):instance/([a-f0-9]{8}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{4}-[a-f0-9]{12})/namespaces/[^/]+/datasets/[^/]+$" } }, - "com.amazonaws.supplychain#DataIntegrationEventResource": { - "type": "resource", - "identifiers": { + "com.amazonaws.supplychain#DataIntegrationEvent": { + "type": "structure", + "members": { "instanceId": { - "target": "com.amazonaws.supplychain#UUID" + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#required": {} + } }, "eventId": { - "target": "com.amazonaws.supplychain#UUID" - } - }, - "properties": { - "eventType": { - "target": "com.amazonaws.supplychain#DataIntegrationEventType" + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The unique event identifier.
", + "smithy.api#required": {} + } }, - "data": { - "target": "com.amazonaws.supplychain#DataIntegrationEventData" + "eventType": { + "target": "com.amazonaws.supplychain#DataIntegrationEventType", + "traits": { + "smithy.api#documentation": "The data event type.
", + "smithy.api#required": {} + } }, "eventGroupId": { - "target": "com.amazonaws.supplychain#DataIntegrationEventGroupId" + "target": "com.amazonaws.supplychain#DataIntegrationEventGroupId", + "traits": { + "smithy.api#documentation": "Event identifier (for example, orderId for InboundOrder) used for data sharding or partitioning.
", + "smithy.api#required": {} + } }, "eventTimestamp": { - "target": "smithy.api#Timestamp" + "target": "smithy.api#Timestamp", + "traits": { + "smithy.api#documentation": "The event timestamp (in epoch seconds).
", + "smithy.api#required": {} + } + }, + "datasetTargetDetails": { + "target": "com.amazonaws.supplychain#DataIntegrationEventDatasetTargetDetails", + "traits": { + "smithy.api#documentation": "The target dataset details for a DATASET event type.
" + } } }, - "create": { - "target": "com.amazonaws.supplychain#SendDataIntegrationEvent" - }, "traits": { - "aws.api#arn": { - "template": "instance/{instanceId}/data-integration-events/{eventId}" + "smithy.api#documentation": "The data integration event details.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationEventData": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 1048576 + }, + "smithy.api#sensitive": {} + } + }, + "com.amazonaws.supplychain#DataIntegrationEventDatasetLoadExecutionDetails": { + "type": "structure", + "members": { + "status": { + "target": "com.amazonaws.supplychain#DataIntegrationEventDatasetLoadStatus", + "traits": { + "smithy.api#documentation": "The event load execution status to target dataset.
", + "smithy.api#required": {} + } + }, + "message": { + "target": "smithy.api#String", + "traits": { + "smithy.api#documentation": "The failure message (if any) of failed event load execution to dataset.
" + } } + }, + "traits": { + "smithy.api#documentation": "The target dataset load execution details.
" } }, - "com.amazonaws.supplychain#DataIntegrationEventType": { + "com.amazonaws.supplychain#DataIntegrationEventDatasetLoadStatus": { "type": "enum", "members": { - "FORECAST": { + "SUCCEEDED": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.forecast" + "smithy.api#enumValue": "SUCCEEDED" } }, - "INVENTORY_LEVEL": { + "IN_PROGRESS": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.inventorylevel" + "smithy.api#enumValue": "IN_PROGRESS" } }, - "INBOUND_ORDER": { + "FAILED": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.inboundorder" + "smithy.api#enumValue": "FAILED" } - }, - "INBOUND_ORDER_LINE": { + } + } + }, + "com.amazonaws.supplychain#DataIntegrationEventDatasetOperationType": { + "type": "enum", + "members": { + "APPEND": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.inboundorderline" + "smithy.api#enumValue": "APPEND" } }, - "INBOUND_ORDER_LINE_SCHEDULE": { + "UPSERT": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.inboundorderlineschedule" + "smithy.api#enumValue": "UPSERT" } }, - "OUTBOUND_ORDER_LINE": { + "DELETE": { "target": "smithy.api#Unit", "traits": { - "smithy.api#enumValue": "scn.data.outboundorderline" + "smithy.api#enumValue": "DELETE" } - }, - "OUTBOUND_SHIPMENT": { - "target": "smithy.api#Unit", + } + } + }, + "com.amazonaws.supplychain#DataIntegrationEventDatasetTargetConfiguration": { + "type": "structure", + "members": { + "datasetIdentifier": { + "target": "com.amazonaws.supplychain#DataIntegrationDatasetArn", "traits": { - "smithy.api#enumValue": "scn.data.outboundshipment" + "smithy.api#documentation": "The datalake dataset ARN identifier.
", + "smithy.api#required": {} } }, - "PROCESS_HEADER": { - "target": "smithy.api#Unit", + "operationType": { + "target": "com.amazonaws.supplychain#DataIntegrationEventDatasetOperationType", "traits": { - "smithy.api#enumValue": "scn.data.processheader" + "smithy.api#documentation": "The target dataset load operation type.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The target dataset configuration for a DATASET event type.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationEventDatasetTargetDetails": { + "type": "structure", + "members": { + "datasetIdentifier": { + "target": "com.amazonaws.supplychain#DataIntegrationDatasetArn", + "traits": { + "smithy.api#documentation": "The datalake dataset ARN identifier.
", + "smithy.api#required": {} + } + }, + "operationType": { + "target": "com.amazonaws.supplychain#DataIntegrationEventDatasetOperationType", + "traits": { + "smithy.api#documentation": "The target dataset load operation type. The available options are:
\n\n APPEND - Add new records to the dataset. Noted that this operation type will just try to append records as-is without any primary key or partition constraints.
\n\n UPSERT - Modify existing records in the dataset with primary key configured, events for datasets without primary keys are not allowed. If event data contains primary keys that match records in the dataset within same partition, then those existing records (in that partition) will be updated. If primary keys do not match, new records will be added. Note that if dataset contain records with duplicate primary key values in the same partition, those duplicate records will be deduped into one updated record.
\n\n DELETE - Remove existing records in the dataset with primary key configured, events for datasets without primary keys are not allowed. If event data contains primary keys that match records in the dataset within same partition, then those existing records (in that partition) will be deleted. If primary keys do not match, no actions will be done. Note that if dataset contain records with duplicate primary key values in the same partition, all those duplicates will be removed.
\nThe target dataset load execution.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The target dataset details for a DATASET event type.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationEventGroupId": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 255 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationEventList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataIntegrationEvent" + } + }, + "com.amazonaws.supplychain#DataIntegrationEventMaxResults": { + "type": "integer", + "traits": { + "smithy.api#default": 10, + "smithy.api#range": { + "min": 1, + "max": 20 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationEventNextToken": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 65535 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationEventType": { + "type": "enum", + "members": { + "FORECAST": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.forecast" + } + }, + "INVENTORY_LEVEL": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.inventorylevel" + } + }, + "INBOUND_ORDER": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.inboundorder" + } + }, + "INBOUND_ORDER_LINE": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.inboundorderline" + } + }, + "INBOUND_ORDER_LINE_SCHEDULE": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.inboundorderlineschedule" + } + }, + "OUTBOUND_ORDER_LINE": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.outboundorderline" + } + }, + "OUTBOUND_SHIPMENT": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.outboundshipment" + } + }, + "PROCESS_HEADER": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.processheader" } }, "PROCESS_OPERATION": { @@ -1118,6 +1480,12 @@ "traits": { "smithy.api#enumValue": "scn.data.supplyplan" } + }, + "DATASET": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "scn.data.dataset" + } } } }, @@ -1186,13 +1554,19 @@ "loadType": { "target": "com.amazonaws.supplychain#DataIntegrationFlowLoadType", "traits": { - "smithy.api#documentation": "The dataset data load type in dataset options.
" + "smithy.api#documentation": "The target dataset's data load type. This only affects how source S3 files are selected in the S3-to-dataset flow.
\n\n REPLACE - Target dataset will get replaced with the new file added under the source s3 prefix.
\n\n INCREMENTAL - Target dataset will get updated with the up-to-date content under S3 prefix incorporating any file additions or removals there.
\nThe dataset load option to remove duplicates.
" + "smithy.api#documentation": "The option to perform deduplication on data records sharing same primary key values. If disabled, transformed data with duplicate primary key values will ingest into dataset, for datasets within asc namespace, such duplicates will cause ingestion fail. If enabled without dedupeStrategy, deduplication is done by retaining a random data record among those sharing the same primary key values. If enabled with dedupeStragtegy, the deduplication is done following the strategy.
\nNote that target dataset may have partition configured, when dedupe is enabled, it only dedupe against primary keys and retain only one record out of those duplicates regardless of its partition status.
" + } + }, + "dedupeStrategy": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowDedupeStrategy", + "traits": { + "smithy.api#documentation": "The deduplication strategy to dedupe the data records sharing same primary key values of the target dataset. This strategy only applies to target dataset with primary keys and with dedupeRecords option enabled. If transformed data still got duplicates after the dedupeStrategy evaluation, a random data record is chosen to be retained.
" } } }, @@ -1200,6 +1574,21 @@ "smithy.api#documentation": "The dataset options used in dataset source and target configurations.
" } }, + "com.amazonaws.supplychain#DataIntegrationFlowDatasetSource": { + "type": "structure", + "members": { + "datasetIdentifier": { + "target": "com.amazonaws.supplychain#DataIntegrationDatasetArn", + "traits": { + "smithy.api#documentation": "The ARN of the dataset source.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The details of a flow execution with dataset source.
" + } + }, "com.amazonaws.supplychain#DataIntegrationFlowDatasetSourceConfiguration": { "type": "structure", "members": { @@ -1227,19 +1616,290 @@ "datasetIdentifier": { "target": "com.amazonaws.supplychain#DatasetIdentifier", "traits": { - "smithy.api#documentation": "The dataset ARN.
", + "smithy.api#documentation": "The dataset ARN.
", + "smithy.api#required": {} + } + }, + "options": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowDatasetOptions", + "traits": { + "smithy.api#documentation": "The dataset DataIntegrationFlow target options.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The dataset DataIntegrationFlow target configuration parameters.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowDedupeStrategy": { + "type": "structure", + "members": { + "type": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowDedupeStrategyType", + "traits": { + "smithy.api#documentation": "The type of the deduplication strategy.
\n\n FIELD_PRIORITY - Field priority configuration for the deduplication strategy specifies an ordered list of fields used to tie-break the data records sharing the same primary key values. Fields earlier in the list have higher priority for evaluation. For each field, the sort order determines whether to retain data record with larger or smaller field value.
\nThe field priority deduplication strategy.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The deduplication strategy details.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowDedupeStrategyType": { + "type": "enum", + "members": { + "FIELD_PRIORITY": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "FIELD_PRIORITY" + } + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecution": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The flow execution's instanceId.
", + "smithy.api#required": {}, + "smithy.api#resourceIdentifier": "instanceId" + } + }, + "flowName": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowName", + "traits": { + "smithy.api#documentation": "The flow execution's flowName.
", + "smithy.api#required": {}, + "smithy.api#resourceIdentifier": "flowName" + } + }, + "executionId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The flow executionId.
", + "smithy.api#required": {}, + "smithy.api#resourceIdentifier": "executionId" + } + }, + "status": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionStatus", + "traits": { + "smithy.api#documentation": "The status of flow execution.
" + } + }, + "sourceInfo": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionSourceInfo", + "traits": { + "smithy.api#documentation": "The source information for a flow execution.
" + } + }, + "message": { + "target": "smithy.api#String", + "traits": { + "smithy.api#documentation": "The failure message (if any) of failed flow execution.
" + } + }, + "startTime": { + "target": "smithy.api#Timestamp", + "traits": { + "smithy.api#documentation": "The flow execution start timestamp.
" + } + }, + "endTime": { + "target": "smithy.api#Timestamp", + "traits": { + "smithy.api#documentation": "The flow execution end timestamp.
" + } + }, + "outputMetadata": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionOutputMetadata", + "traits": { + "smithy.api#documentation": "The flow execution output metadata.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The flow execution details.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionDiagnosticReportsRootS3URI": { + "type": "string", + "traits": { + "smithy.api#pattern": "^s3://[a-z0-9][a-z0-9.-]{1,61}[a-z0-9]/.{1,1024}$" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecution" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionMaxResults": { + "type": "integer", + "traits": { + "smithy.api#default": 10, + "smithy.api#range": { + "min": 1, + "max": 20 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionNextToken": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 65535 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionOutputMetadata": { + "type": "structure", + "members": { + "diagnosticReportsRootS3URI": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionDiagnosticReportsRootS3URI", + "traits": { + "smithy.api#documentation": "The S3 URI under which all diagnostic files (such as deduped records if any) are stored.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The output metadata of the flow execution.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionSourceInfo": { + "type": "structure", + "members": { + "sourceType": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowSourceType", + "traits": { + "smithy.api#documentation": "The data integration flow execution source type.
", + "smithy.api#required": {} + } + }, + "s3Source": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowS3Source", + "traits": { + "smithy.api#documentation": "The source details of a flow execution with S3 source.
" + } + }, + "datasetSource": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowDatasetSource", + "traits": { + "smithy.api#documentation": "The source details of a flow execution with dataset source.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The source information of a flow execution.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowExecutionStatus": { + "type": "enum", + "members": { + "SUCCEEDED": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "SUCCEEDED" + } + }, + "IN_PROGRESS": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "IN_PROGRESS" + } + }, + "FAILED": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "FAILED" + } + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeField": { + "type": "structure", + "members": { + "name": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeFieldName", + "traits": { + "smithy.api#documentation": "The name of the deduplication field. Must exist in the dataset and not be a primary key.
", + "smithy.api#required": {} + } + }, + "sortOrder": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeSortOrder", + "traits": { + "smithy.api#documentation": "The sort order for the deduplication field.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The field used in the field priority deduplication strategy.
" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeFieldList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeField" + }, + "traits": { + "smithy.api#length": { + "min": 1, + "max": 10 + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeFieldName": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 100 + }, + "smithy.api#pattern": "^[a-z0-9_]+$" + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeSortOrder": { + "type": "enum", + "members": { + "ASC": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "ASC" + } + }, + "DESC": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "DESC" + } + } + } + }, + "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeStrategyConfiguration": { + "type": "structure", + "members": { + "fields": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowFieldPriorityDedupeFieldList", + "traits": { + "smithy.api#documentation": "The list of field names and their sort order for deduplication, arranged in descending priority from highest to lowest.
", "smithy.api#required": {} } - }, - "options": { - "target": "com.amazonaws.supplychain#DataIntegrationFlowDatasetOptions", - "traits": { - "smithy.api#documentation": "The dataset DataIntegrationFlow target options.
" - } } }, "traits": { - "smithy.api#documentation": "The dataset DataIntegrationFlow target configuration parameters.
" + "smithy.api#documentation": "The field priority deduplication strategy details.
" } }, "com.amazonaws.supplychain#DataIntegrationFlowFileType": { @@ -1392,6 +2052,28 @@ "smithy.api#pattern": "^[/A-Za-z0-9._-]+$" } }, + "com.amazonaws.supplychain#DataIntegrationFlowS3Source": { + "type": "structure", + "members": { + "bucketName": { + "target": "com.amazonaws.supplychain#S3BucketName", + "traits": { + "smithy.api#documentation": "The S3 bucket name of the S3 source.
", + "smithy.api#required": {} + } + }, + "key": { + "target": "com.amazonaws.supplychain#DataIntegrationS3ObjectKey", + "traits": { + "smithy.api#documentation": "The S3 object key of the S3 source.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The details of a flow execution with S3 source.
" + } + }, "com.amazonaws.supplychain#DataIntegrationFlowS3SourceConfiguration": { "type": "structure", "members": { @@ -1405,7 +2087,7 @@ "prefix": { "target": "com.amazonaws.supplychain#DataIntegrationFlowS3Prefix", "traits": { - "smithy.api#documentation": "The prefix of the S3 source objects.
", + "smithy.api#documentation": "The prefix of the S3 source objects. To trigger data ingestion, S3 files need to be put under s3://bucketName/prefix/.
The dataset DataIntegrationFlow target.
" + "smithy.api#documentation": "The dataset DataIntegrationFlow target. Note that for AWS Supply Chain dataset under asc namespace, it has a connection_id internal field that is not allowed to be provided by client directly, they will be auto populated.
" } } }, @@ -1627,6 +2310,16 @@ } } }, + "com.amazonaws.supplychain#DataIntegrationS3ObjectKey": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 1024 + }, + "smithy.api#pattern": "^[/A-Za-z0-9._:*()'!=?&+;@-]+$" + } + }, "com.amazonaws.supplychain#DataLakeDataset": { "type": "structure", "members": { @@ -1639,9 +2332,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of the dataset. The available values are:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", + "smithy.api#documentation": "The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", "smithy.api#required": {}, "smithy.api#resourceIdentifier": "name" } @@ -1674,6 +2367,9 @@ "smithy.api#documentation": "The description of the dataset.
" } }, + "partitionSpec": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionSpec" + }, "createdTime": { "target": "smithy.api#Timestamp", "traits": { @@ -1709,7 +2405,7 @@ }, "traits": { "smithy.api#length": { - "min": 1, + "min": 0, "max": 20 } } @@ -1734,22 +2430,138 @@ "smithy.api#pattern": "^[a-z0-9_]+$" } }, - "com.amazonaws.supplychain#DataLakeDatasetNamespace": { + "com.amazonaws.supplychain#DataLakeDatasetNextToken": { "type": "string", "traits": { "smithy.api#length": { "min": 1, - "max": 50 + "max": 65535 + } + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPartitionField": { + "type": "structure", + "members": { + "name": { + "target": "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldName", + "traits": { + "smithy.api#documentation": "The name of the partition field.
", + "smithy.api#required": {} + } }, - "smithy.api#pattern": "^[a-z]+$" + "transform": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionFieldTransform", + "traits": { + "smithy.api#documentation": "The transformation of the partition field. A transformation specifies how to partition on a given field. For example, with timestamp you can specify that you'd like to partition fields by day, e.g. data record with value 2025-01-03T00:00:00Z in partition field is in 2025-01-03 partition. Also noted that data record without any value in optional partition field is in NULL partition.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The detail of the partition field.
" } }, - "com.amazonaws.supplychain#DataLakeDatasetNextToken": { - "type": "string", + "com.amazonaws.supplychain#DataLakeDatasetPartitionFieldList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionField" + }, "traits": { "smithy.api#length": { "min": 1, - "max": 65535 + "max": 10 + } + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPartitionFieldTransform": { + "type": "structure", + "members": { + "type": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionTransformType", + "traits": { + "smithy.api#documentation": "The type of partitioning transformation for this field. The available options are:
\n\n IDENTITY - Partitions data on a given field by its exact values.
\n\n YEAR - Partitions data on a timestamp field using year granularity.
\n\n MONTH - Partitions data on a timestamp field using month granularity.
\n\n DAY - Partitions data on a timestamp field using day granularity.
\n\n HOUR - Partitions data on a timestamp field using hour granularity.
\nThe detail of the partition field transformation.
" + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPartitionSpec": { + "type": "structure", + "members": { + "fields": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionFieldList", + "traits": { + "smithy.api#documentation": "The fields on which to partition a dataset. The partitions will be applied hierarchically based on the order of this list.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The partition specification for a dataset.
" + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPartitionTransformType": { + "type": "enum", + "members": { + "YEAR": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "YEAR" + } + }, + "MONTH": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "MONTH" + } + }, + "DAY": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "DAY" + } + }, + "HOUR": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "HOUR" + } + }, + "IDENTITY": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "IDENTITY" + } + } + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPrimaryKeyField": { + "type": "structure", + "members": { + "name": { + "target": "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldName", + "traits": { + "smithy.api#documentation": "The name of the primary key field.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The detail of the primary key field.
" + } + }, + "com.amazonaws.supplychain#DataLakeDatasetPrimaryKeyFieldList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPrimaryKeyField" + }, + "traits": { + "smithy.api#length": { + "min": 1, + "max": 20 } } }, @@ -1760,7 +2572,7 @@ "target": "com.amazonaws.supplychain#UUID" }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace" + "target": "com.amazonaws.supplychain#DataLakeNamespaceName" }, "name": { "target": "com.amazonaws.supplychain#DataLakeDatasetName" @@ -1781,6 +2593,9 @@ }, "lastModifiedTime": { "target": "smithy.api#Timestamp" + }, + "partitionSpec": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPartitionSpec" } }, "put": { @@ -1824,10 +2639,16 @@ "smithy.api#documentation": "The list of field details of the dataset schema.
", "smithy.api#required": {} } + }, + "primaryKeys": { + "target": "com.amazonaws.supplychain#DataLakeDatasetPrimaryKeyFieldList", + "traits": { + "smithy.api#documentation": "The list of primary key fields for the dataset. Primary keys defined can help data ingestion methods to ensure data uniqueness: CreateDataIntegrationFlow's dedupe strategy will leverage primary keys to perform records deduplication before write to dataset; SendDataIntegrationEvent's UPSERT and DELETE can only work with dataset with primary keys. For more details, refer to those data ingestion documentations.
\nNote that defining primary keys does not necessarily mean the dataset cannot have duplicate records, duplicate records can still be ingested if CreateDataIntegrationFlow's dedupe disabled or through SendDataIntegrationEvent's APPEND operation.
" + } } }, "traits": { - "smithy.api#documentation": "The schema details of the dataset.
" + "smithy.api#documentation": "The schema details of the dataset. Note that for AWS Supply Chain dataset under asc namespace, it may have internal fields like connection_id that will be auto populated by data ingestion methods.
" } }, "com.amazonaws.supplychain#DataLakeDatasetSchemaField": { @@ -1865,59 +2686,212 @@ "target": "com.amazonaws.supplychain#DataLakeDatasetSchemaField" }, "traits": { - "smithy.api#length": { + "smithy.api#length": { + "min": 1, + "max": 500 + } + } + }, + "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldName": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 100 + }, + "smithy.api#pattern": "^[a-z0-9_]+$" + } + }, + "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldType": { + "type": "enum", + "members": { + "INT": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "INT" + } + }, + "DOUBLE": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "DOUBLE" + } + }, + "STRING": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "STRING" + } + }, + "TIMESTAMP": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "TIMESTAMP" + } + }, + "LONG": { + "target": "smithy.api#Unit", + "traits": { + "smithy.api#enumValue": "LONG" + } + } + } + }, + "com.amazonaws.supplychain#DataLakeDatasetSchemaName": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 100 + }, + "smithy.api#pattern": "^[A-Za-z0-9]+$" + } + }, + "com.amazonaws.supplychain#DataLakeNamespace": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", + "smithy.api#required": {}, + "smithy.api#resourceIdentifier": "instanceId" + } + }, + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The name of the namespace.
", + "smithy.api#required": {}, + "smithy.api#resourceIdentifier": "name" + } + }, + "arn": { + "target": "com.amazonaws.supplychain#AscResourceArn", + "traits": { + "smithy.api#documentation": "The arn of the namespace.
", + "smithy.api#required": {} + } + }, + "description": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceDescription", + "traits": { + "smithy.api#documentation": "The description of the namespace.
" + } + }, + "createdTime": { + "target": "smithy.api#Timestamp", + "traits": { + "smithy.api#documentation": "The creation time of the namespace.
", + "smithy.api#required": {} + } + }, + "lastModifiedTime": { + "target": "smithy.api#Timestamp", + "traits": { + "smithy.api#documentation": "The last modified time of the namespace.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The data lake namespace details.
" + } + }, + "com.amazonaws.supplychain#DataLakeNamespaceDescription": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 500 + } + } + }, + "com.amazonaws.supplychain#DataLakeNamespaceList": { + "type": "list", + "member": { + "target": "com.amazonaws.supplychain#DataLakeNamespace" + }, + "traits": { + "smithy.api#length": { + "min": 1, + "max": 20 + } + } + }, + "com.amazonaws.supplychain#DataLakeNamespaceMaxResults": { + "type": "integer", + "traits": { + "smithy.api#default": 10, + "smithy.api#range": { "min": 1, - "max": 500 + "max": 20 } } }, - "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldName": { + "com.amazonaws.supplychain#DataLakeNamespaceName": { "type": "string", "traits": { "smithy.api#length": { "min": 1, - "max": 100 + "max": 50 }, "smithy.api#pattern": "^[a-z0-9_]+$" } }, - "com.amazonaws.supplychain#DataLakeDatasetSchemaFieldType": { - "type": "enum", - "members": { - "INT": { - "target": "smithy.api#Unit", - "traits": { - "smithy.api#enumValue": "INT" - } + "com.amazonaws.supplychain#DataLakeNamespaceNextToken": { + "type": "string", + "traits": { + "smithy.api#length": { + "min": 1, + "max": 65535 + } + } + }, + "com.amazonaws.supplychain#DataLakeNamespaceResource": { + "type": "resource", + "identifiers": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID" }, - "DOUBLE": { - "target": "smithy.api#Unit", - "traits": { - "smithy.api#enumValue": "DOUBLE" - } + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName" + } + }, + "properties": { + "arn": { + "target": "com.amazonaws.supplychain#AscResourceArn" }, - "STRING": { - "target": "smithy.api#Unit", - "traits": { - "smithy.api#enumValue": "STRING" - } + "description": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceDescription" }, - "TIMESTAMP": { - "target": "smithy.api#Unit", - "traits": { - "smithy.api#enumValue": "TIMESTAMP" - } + "createdTime": { + "target": "smithy.api#Timestamp" + }, + "lastModifiedTime": { + "target": "smithy.api#Timestamp" } - } - }, - "com.amazonaws.supplychain#DataLakeDatasetSchemaName": { - "type": "string", + }, + "put": { + "target": "com.amazonaws.supplychain#CreateDataLakeNamespace" + }, + "read": { + "target": "com.amazonaws.supplychain#GetDataLakeNamespace" + }, + "update": { + "target": "com.amazonaws.supplychain#UpdateDataLakeNamespace" + }, + "delete": { + "target": "com.amazonaws.supplychain#DeleteDataLakeNamespace" + }, + "list": { + "target": "com.amazonaws.supplychain#ListDataLakeNamespaces" + }, "traits": { - "smithy.api#length": { - "min": 1, - "max": 100 + "aws.api#arn": { + "template": "instance/{instanceId}/namespaces/{name}" }, - "smithy.api#pattern": "^[A-Za-z0-9]+$" + "smithy.api#noReplace": {} } }, "com.amazonaws.supplychain#DatasetIdentifier": { @@ -2098,9 +3072,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of the dataset. The available values are:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", + "smithy.api#documentation": "The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -2130,9 +3104,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of deleted dataset.
", + "smithy.api#documentation": "The namespace of deleted dataset.
", "smithy.api#required": {} } }, @@ -2149,6 +3123,102 @@ "smithy.api#output": {} } }, + "com.amazonaws.supplychain#DeleteDataLakeNamespace": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#DeleteDataLakeNamespaceRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#DeleteDataLakeNamespaceResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically delete an Amazon Web Services Supply Chain data lake namespace and its underling datasets. Developers can delete the existing namespaces for a given instance ID and namespace name.
", + "smithy.api#examples": [ + { + "title": "Delete an AWS Supply Chain namespace", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace" + }, + "output": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace" + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "DELETE", + "uri": "/api/datalake/instance/{instanceId}/namespaces/{name}" + }, + "smithy.api#idempotent": {} + } + }, + "com.amazonaws.supplychain#DeleteDataLakeNamespaceRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The name of the namespace. Noted you cannot delete pre-defined namespace like asc, default which are only deleted through instance deletion.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters of DeleteDataLakeNamespace.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#DeleteDataLakeNamespaceResponse": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#required": {} + } + }, + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The name of deleted namespace.
", + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of DeleteDataLakeNamespace.
", + "smithy.api#output": {} + } + }, "com.amazonaws.supplychain#DeleteInstance": { "type": "operation", "input": { @@ -2243,9 +3313,24 @@ "type": "service", "version": "2024-01-01", "operations": [ + { + "target": "com.amazonaws.supplychain#GetDataIntegrationEvent" + }, + { + "target": "com.amazonaws.supplychain#GetDataIntegrationFlowExecution" + }, + { + "target": "com.amazonaws.supplychain#ListDataIntegrationEvents" + }, + { + "target": "com.amazonaws.supplychain#ListDataIntegrationFlowExecutions" + }, { "target": "com.amazonaws.supplychain#ListTagsForResource" }, + { + "target": "com.amazonaws.supplychain#SendDataIntegrationEvent" + }, { "target": "com.amazonaws.supplychain#TagResource" }, @@ -2257,15 +3342,15 @@ { "target": "com.amazonaws.supplychain#BillOfMaterialsImportJobResource" }, - { - "target": "com.amazonaws.supplychain#DataIntegrationEventResource" - }, { "target": "com.amazonaws.supplychain#DataIntegrationFlowResource" }, { "target": "com.amazonaws.supplychain#DataLakeDatasetResource" }, + { + "target": "com.amazonaws.supplychain#DataLakeNamespaceResource" + }, { "target": "com.amazonaws.supplychain#InstanceResource" } @@ -3028,17 +4113,119 @@ } }, { - "title": "Invoke GetBillOfMaterialsImportJob for an in-progress job", + "title": "Invoke GetBillOfMaterialsImportJob for an in-progress job", + "input": { + "instanceId": "60f82bbd-71f7-4fcd-a941-472f574c5243", + "jobId": "f79b359b-1515-4436-a3bf-bae7b33e47b4" + }, + "output": { + "job": { + "instanceId": "60f82bbd-71f7-4fcd-a941-472f574c5243", + "jobId": "f79b359b-1515-4436-a3bf-bae7b33e47b4", + "status": "IN_PROGRESS", + "s3uri": "s3://mybucketname/pathelemene/file.csv" + } + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api/configuration/instances/{instanceId}/bill-of-materials-import-jobs/{jobId}" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#GetBillOfMaterialsImportJobRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "jobId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The BillOfMaterialsImportJob identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters for GetBillOfMaterialsImportJob.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#GetBillOfMaterialsImportJobResponse": { + "type": "structure", + "members": { + "job": { + "target": "com.amazonaws.supplychain#BillOfMaterialsImportJob", + "traits": { + "smithy.api#documentation": "The BillOfMaterialsImportJob.
", + "smithy.api#nestedProperties": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters for GetBillOfMaterialsImportJob.
", + "smithy.api#output": {} + } + }, + "com.amazonaws.supplychain#GetDataIntegrationEvent": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#GetDataIntegrationEventRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#GetDataIntegrationEventResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically view an Amazon Web Services Supply Chain Data Integration Event. Developers can view the eventType, eventGroupId, eventTimestamp, datasetTarget, datasetLoadExecution.
", + "smithy.api#examples": [ + { + "title": "Successful GetDataIntegrationEvent", "input": { - "instanceId": "60f82bbd-71f7-4fcd-a941-472f574c5243", - "jobId": "f79b359b-1515-4436-a3bf-bae7b33e47b4" + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "eventId": "19739c8e-cd2e-4cbc-a2f7-0dc43239f042" }, "output": { - "job": { - "instanceId": "60f82bbd-71f7-4fcd-a941-472f574c5243", - "jobId": "f79b359b-1515-4436-a3bf-bae7b33e47b4", - "status": "IN_PROGRESS", - "s3uri": "s3://mybucketname/pathelemene/file.csv" + "event": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "eventId": "19739c8e-cd2e-4cbc-a2f7-0dc43239f042", + "eventType": "scn.data.dataset", + "eventGroupId": "datasetId", + "eventTimestamp": 1.515531081123e9, + "datasetTargetDetails": { + "datasetIdentifier": "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + "operationType": "APPEND", + "datasetLoadExecution": { + "status": "SUCCEEDED" + } + } } } } @@ -3046,50 +4233,50 @@ "smithy.api#http": { "code": 200, "method": "GET", - "uri": "/api/configuration/instances/{instanceId}/bill-of-materials-import-jobs/{jobId}" + "uri": "/api-data/data-integration/instance/{instanceId}/data-integration-events/{eventId}" }, "smithy.api#readonly": {} } }, - "com.amazonaws.supplychain#GetBillOfMaterialsImportJobRequest": { + "com.amazonaws.supplychain#GetDataIntegrationEventRequest": { "type": "structure", "members": { "instanceId": { "target": "com.amazonaws.supplychain#UUID", "traits": { - "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } }, - "jobId": { + "eventId": { "target": "com.amazonaws.supplychain#UUID", "traits": { - "smithy.api#documentation": "The BillOfMaterialsImportJob identifier.
", + "smithy.api#documentation": "The unique event identifier.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The request parameters for GetBillOfMaterialsImportJob.
", + "smithy.api#documentation": "The request parameters for GetDataIntegrationEvent.
", "smithy.api#input": {} } }, - "com.amazonaws.supplychain#GetBillOfMaterialsImportJobResponse": { + "com.amazonaws.supplychain#GetDataIntegrationEventResponse": { "type": "structure", "members": { - "job": { - "target": "com.amazonaws.supplychain#BillOfMaterialsImportJob", + "event": { + "target": "com.amazonaws.supplychain#DataIntegrationEvent", "traits": { - "smithy.api#documentation": "The BillOfMaterialsImportJob.
", + "smithy.api#documentation": "The details of the DataIntegrationEvent returned.
", "smithy.api#nestedProperties": {}, "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The response parameters for GetBillOfMaterialsImportJob.
", + "smithy.api#documentation": "The response parameters for GetDataIntegrationEvent.
", "smithy.api#output": {} } }, @@ -3167,6 +4354,142 @@ "smithy.api#readonly": {} } }, + "com.amazonaws.supplychain#GetDataIntegrationFlowExecution": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#GetDataIntegrationFlowExecutionRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#GetDataIntegrationFlowExecutionResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Get the flow execution.
", + "smithy.api#examples": [ + { + "title": "Successful GetDataIntegrationFlowExecution for S3 source", + "input": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "source-product", + "executionId": "edbbdd3f-c0f9-49d9-ab01-f64542f803b7" + }, + "output": { + "flowExecution": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "source-product", + "executionId": "edbbdd3f-c0f9-49d9-ab01-f64542f803b7", + "status": "SUCCEEDED", + "sourceInfo": { + "sourceType": "S3", + "s3Source": { + "bucketName": "galaxy-raw-input-test-data-prod-pdx-1", + "key": "sources/product-sources.csv" + } + }, + "startTime": 1.515531081123e9, + "endTime": 1.515531090123e9 + } + } + }, + { + "title": "Successful GetDataIntegrationFlowExecution for DATASET source", + "input": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "target-product", + "executionId": "9daf6071-d12c-4eef-864c-73cea2557825" + }, + "output": { + "flowExecution": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "target-product", + "executionId": "9daf6071-d12c-4eef-864c-73cea2557825", + "status": "SUCCEEDED", + "sourceInfo": { + "sourceType": "DATASET", + "datasetSource": { + "datasetIdentifier": "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/default/datasets/product" + } + }, + "startTime": 1.515531081123e9, + "endTime": 1.515531090123e9 + } + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api-data/data-integration/instance/{instanceId}/data-integration-flows/{flowName}/executions/{executionId}" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#GetDataIntegrationFlowExecutionRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "flowName": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowName", + "traits": { + "smithy.api#documentation": "The flow name.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "executionId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The flow execution identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters of GetFlowExecution.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#GetDataIntegrationFlowExecutionResponse": { + "type": "structure", + "members": { + "flowExecution": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecution", + "traits": { + "smithy.api#documentation": "The flow execution details.
", + "smithy.api#nestedProperties": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of GetFlowExecution.
", + "smithy.api#output": {} + } + }, "com.amazonaws.supplychain#GetDataIntegrationFlowRequest": { "type": "structure", "members": { @@ -3412,46 +4735,192 @@ } }, { - "title": "Get proporties of an existing custom dataset", + "title": "Get proporties of an existing custom dataset", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "namespace": "default", + "name": "my_dataset" + }, + "output": { + "dataset": { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/default/datasets/my_dataset", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "namespace": "default", + "name": "my_dataset", + "description": "This is a custom dataset", + "createdTime": 1.727116807751e9, + "lastModifiedTime": 1.727116807751e9, + "schema": { + "name": "MyDataset", + "fields": [ + { + "name": "id", + "type": "INT", + "isRequired": true + }, + { + "name": "description", + "type": "STRING", + "isRequired": true + }, + { + "name": "price", + "type": "DOUBLE", + "isRequired": false + }, + { + "name": "creation_time", + "type": "TIMESTAMP", + "isRequired": false + }, + { + "name": "quantity", + "type": "LONG", + "isRequired": false + } + ], + "primaryKeys": [ + { + "name": "id" + } + ] + }, + "partitionSpec": { + "fields": [ + { + "name": "creation_time", + "transform": { + "type": "DAY" + } + }, + { + "name": "description", + "transform": { + "type": "IDENTITY" + } + } + ] + } + } + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api/datalake/instance/{instanceId}/namespaces/{namespace}/datasets/{name}" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#GetDataLakeDatasetRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "namespace": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters for GetDataLakeDataset.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#GetDataLakeDatasetResponse": { + "type": "structure", + "members": { + "dataset": { + "target": "com.amazonaws.supplychain#DataLakeDataset", + "traits": { + "smithy.api#documentation": "The fetched dataset details.
", + "smithy.api#nestedProperties": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters for GetDataLakeDataset.
", + "smithy.api#output": {} + } + }, + "com.amazonaws.supplychain#GetDataLakeNamespace": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#GetDataLakeNamespaceRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#GetDataLakeNamespaceResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically view an Amazon Web Services Supply Chain data lake namespace. Developers can view the data lake namespace information such as description for a given instance ID and namespace name.
", + "smithy.api#examples": [ + { + "title": "Get properties of an existing AWS Supply Chain namespace", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace" + }, + "output": { + "namespace": { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "description": "This is my AWS Supply Chain namespace", + "createdTime": 1.736892560751e9, + "lastModifiedTime": 1.736892560751e9 + } + } + }, + { + "title": "Get proporties of an existing pre-defined AWS Supply Chain namespace", "input": { "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", - "namespace": "default", - "name": "my_dataset" + "name": "asc" }, "output": { - "dataset": { - "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/default/datasets/my_dataset", + "namespace": { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/asc", "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", - "namespace": "default", - "name": "my_dataset", - "description": "This is a custom dataset", - "createdTime": 1.727116807751e9, - "lastModifiedTime": 1.727116807751e9, - "schema": { - "name": "MyDataset", - "fields": [ - { - "name": "id", - "type": "INT", - "isRequired": true - }, - { - "name": "description", - "type": "STRING", - "isRequired": true - }, - { - "name": "price", - "type": "DOUBLE", - "isRequired": false - }, - { - "name": "creation_time", - "type": "TIMESTAMP", - "isRequired": false - } - ] - } + "name": "asc", + "createdTime": 1.736892430234e9, + "lastModifiedTime": 1.736892430234e9 } } } @@ -3459,12 +4928,12 @@ "smithy.api#http": { "code": 200, "method": "GET", - "uri": "/api/datalake/instance/{instanceId}/namespaces/{namespace}/datasets/{name}" + "uri": "/api/datalake/instance/{instanceId}/namespaces/{name}" }, "smithy.api#readonly": {} } }, - "com.amazonaws.supplychain#GetDataLakeDatasetRequest": { + "com.amazonaws.supplychain#GetDataLakeNamespaceRequest": { "type": "structure", "members": { "instanceId": { @@ -3475,42 +4944,34 @@ "smithy.api#required": {} } }, - "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", - "traits": { - "smithy.api#documentation": "The name space of the dataset. The available values are:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", + "smithy.api#documentation": "The name of the namespace. Besides the namespaces user created, you can also specify the pre-defined namespaces:
\n\n asc - Pre-defined namespace containing Amazon Web Services Supply Chain supported datasets, see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - Pre-defined namespace containing datasets with custom user-defined schemas.
\nThe request parameters for GetDataLakeDataset.
", + "smithy.api#documentation": "The request parameters for GetDataLakeNamespace.
", "smithy.api#input": {} } }, - "com.amazonaws.supplychain#GetDataLakeDatasetResponse": { + "com.amazonaws.supplychain#GetDataLakeNamespaceResponse": { "type": "structure", "members": { - "dataset": { - "target": "com.amazonaws.supplychain#DataLakeDataset", + "namespace": { + "target": "com.amazonaws.supplychain#DataLakeNamespace", "traits": { - "smithy.api#documentation": "The fetched dataset details.
", + "smithy.api#documentation": "The fetched namespace details.
", "smithy.api#nestedProperties": {}, "smithy.api#required": {} } } }, "traits": { - "smithy.api#documentation": "The response parameters for UpdateDataLakeDataset.
", + "smithy.api#documentation": "The response parameters for GetDataLakeNamespace.
", "smithy.api#output": {} } }, @@ -3895,13 +5356,269 @@ "smithy.api#retryable": {} } }, - "com.amazonaws.supplychain#KmsKeyArn": { - "type": "string", - "traits": { - "smithy.api#length": { - "max": 2048 + "com.amazonaws.supplychain#KmsKeyArn": { + "type": "string", + "traits": { + "smithy.api#length": { + "max": 2048 + }, + "smithy.api#pattern": "^arn:[a-z0-9][-.a-z0-9]{0,62}:kms:([a-z0-9][-.a-z0-9]{0,62})?:([a-z0-9][-.a-z0-9]{0,62})?:key/.{0,1019}$" + } + }, + "com.amazonaws.supplychain#ListDataIntegrationEvents": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#ListDataIntegrationEventsRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#ListDataIntegrationEventsResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically list all data integration events for the provided Amazon Web Services Supply Chain instance.
", + "smithy.api#examples": [ + { + "title": "Successful ListDataIntegrationEvents", + "input": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a" + }, + "output": { + "events": [ + { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "eventId": "19739c8e-cd2e-4cbc-a2f7-0dc43239f042", + "eventType": "scn.data.dataset", + "eventGroupId": "datasetId", + "eventTimestamp": 1.515531081123e9, + "datasetTargetDetails": { + "datasetIdentifier": "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + "operationType": "APPEND", + "datasetLoadExecution": { + "status": "SUCCEEDED" + } + } + } + ] + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api-data/data-integration/instance/{instanceId}/data-integration-events" + }, + "smithy.api#paginated": { + "inputToken": "nextToken", + "outputToken": "nextToken", + "pageSize": "maxResults", + "items": "events" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#ListDataIntegrationEventsRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "eventType": { + "target": "com.amazonaws.supplychain#DataIntegrationEventType", + "traits": { + "smithy.api#documentation": "List data integration events for the specified eventType.
", + "smithy.api#httpQuery": "eventType" + } + }, + "nextToken": { + "target": "com.amazonaws.supplychain#DataIntegrationEventNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch the next page of the data integration events.
", + "smithy.api#httpQuery": "nextToken" + } + }, + "maxResults": { + "target": "com.amazonaws.supplychain#DataIntegrationEventMaxResults", + "traits": { + "smithy.api#default": 10, + "smithy.api#documentation": "Specify the maximum number of data integration events to fetch in one paginated request.
", + "smithy.api#httpQuery": "maxResults" + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters for ListDataIntegrationEvents.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#ListDataIntegrationEventsResponse": { + "type": "structure", + "members": { + "events": { + "target": "com.amazonaws.supplychain#DataIntegrationEventList", + "traits": { + "smithy.api#documentation": "The list of data integration events.
", + "smithy.api#required": {} + } + }, + "nextToken": { + "target": "com.amazonaws.supplychain#DataIntegrationEventNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch the next page of the ListDataIntegrationEvents.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters for ListDataIntegrationEvents.
", + "smithy.api#output": {} + } + }, + "com.amazonaws.supplychain#ListDataIntegrationFlowExecutions": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#ListDataIntegrationFlowExecutionsRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#ListDataIntegrationFlowExecutionsResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "List flow executions.
", + "smithy.api#examples": [ + { + "title": "Successful ListDataIntegrationFlowExecutions", + "input": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "source-product" + }, + "output": { + "flowExecutions": [ + { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "flowName": "source-product", + "executionId": "edbbdd3f-c0f9-49d9-ab01-f64542f803b7", + "status": "SUCCEEDED", + "sourceInfo": { + "sourceType": "S3", + "s3Source": { + "bucketName": "galaxy-raw-input-test-data-prod-pdx-1", + "key": "sources/product-sources.csv" + } + }, + "startTime": 1.515531081123e9, + "endTime": 1.515531090123e9 + } + ] + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api-data/data-integration/instance/{instanceId}/data-integration-flows/{flowName}/executions" + }, + "smithy.api#paginated": { + "inputToken": "nextToken", + "outputToken": "nextToken", + "pageSize": "maxResults", + "items": "flowExecutions" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#ListDataIntegrationFlowExecutionsRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The AWS Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "flowName": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowName", + "traits": { + "smithy.api#documentation": "The flow name.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "nextToken": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch next page of flow executions.
", + "smithy.api#httpQuery": "nextToken" + } + }, + "maxResults": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionMaxResults", + "traits": { + "smithy.api#default": 10, + "smithy.api#documentation": "The number to specify the max number of flow executions to fetch in this paginated request.
", + "smithy.api#httpQuery": "maxResults" + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters of ListFlowExecutions.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#ListDataIntegrationFlowExecutionsResponse": { + "type": "structure", + "members": { + "flowExecutions": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionList", + "traits": { + "smithy.api#documentation": "The list of flow executions.
", + "smithy.api#required": {} + } }, - "smithy.api#pattern": "^arn:[a-z0-9][-.a-z0-9]{0,62}:kms:([a-z0-9][-.a-z0-9]{0,62})?:([a-z0-9][-.a-z0-9]{0,62})?:key/.{0,1019}$" + "nextToken": { + "target": "com.amazonaws.supplychain#DataIntegrationFlowExecutionNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch next page of flow executions.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of ListFlowExecutions.
", + "smithy.api#output": {} } }, "com.amazonaws.supplychain#ListDataIntegrationFlows": { @@ -3992,7 +5709,22 @@ "target": { "targetType": "DATASET", "datasetTarget": { - "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + "options": { + "loadType": "REPLACE", + "dedupeRecords": true, + "dedupeStrategy": { + "type": "FIELD_PRIORITY", + "fieldPriority": { + "fields": [ + { + "name": "eff_start_date", + "sortOrder": "DESC" + } + ] + } + } + } } }, "createdTime": 1.723576350688e10, @@ -4313,6 +6045,32 @@ "name": "creation_time", "type": "TIMESTAMP", "isRequired": false + }, + { + "name": "quantity", + "type": "LONG", + "isRequired": false + } + ], + "primaryKeys": [ + { + "name": "id" + } + ] + }, + "partitionSpec": { + "fields": [ + { + "name": "creation_time", + "transform": { + "type": "DAY" + } + }, + { + "name": "description", + "transform": { + "type": "IDENTITY" + } } ] } @@ -4372,9 +6130,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of the dataset. The available values are:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nEnables you to programmatically view the list of Amazon Web Services Supply Chain data lake namespaces. Developers can view the namespaces and the corresponding information such as description for a given instance ID. Note that this API only return custom namespaces, instance pre-defined namespaces are not included.
", + "smithy.api#examples": [ + { + "title": "List AWS Supply Chain namespaces", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5" + }, + "output": { + "namespaces": [ + { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/custom_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "custom_namespace", + "createdTime": 1.736892060751e9, + "lastModifiedTime": 1.736892060751e9 + }, + { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "createdTime": 1.736892560751e9, + "lastModifiedTime": 1.736892586156e9 + } + ] + } + }, + { + "title": "List AWS Supply Chain namespaces using pagination", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "maxResults": 1, + "nextToken": "next_token_returned_from_previous_list_request" + }, + "output": { + "namespaces": [ + { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "createdTime": 1.736892560751e9, + "lastModifiedTime": 1.736892586156e9 + } + ], + "nextToken": "next_token_for_next_list_request" + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "GET", + "uri": "/api/datalake/instance/{instanceId}/namespaces" + }, + "smithy.api#paginated": { + "inputToken": "nextToken", + "outputToken": "nextToken", + "pageSize": "maxResults", + "items": "namespaces" + }, + "smithy.api#readonly": {} + } + }, + "com.amazonaws.supplychain#ListDataLakeNamespacesRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Supply Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "nextToken": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch next page of namespaces.
", + "smithy.api#httpQuery": "nextToken" + } + }, + "maxResults": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceMaxResults", + "traits": { + "smithy.api#default": 10, + "smithy.api#documentation": "The max number of namespaces to fetch in this paginated request.
", + "smithy.api#httpQuery": "maxResults" + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters of ListDataLakeNamespaces.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#ListDataLakeNamespacesResponse": { + "type": "structure", + "members": { + "namespaces": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceList", + "traits": { + "smithy.api#documentation": "The list of fetched namespace details. Noted it only contains custom namespaces, pre-defined namespaces are not included.
", + "smithy.api#required": {} + } + }, + "nextToken": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceNextToken", + "traits": { + "smithy.api#documentation": "The pagination token to fetch next page of namespaces.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of ListDataLakeNamespaces.
", + "smithy.api#output": {} + } + }, "com.amazonaws.supplychain#ListInstances": { "type": "operation", "input": { @@ -4751,7 +6647,7 @@ } ], "traits": { - "smithy.api#documentation": "Send the transactional data payload for the event with real-time data for analysis or monitoring. The real-time data events are stored in an Amazon Web Services service before being processed and stored in data lake. New data events are synced with data lake at 5 PM GMT everyday. The updated transactional data is available in data lake after ingestion.
", + "smithy.api#documentation": "Send the data payload for the event with real-time data for analysis or monitoring. The real-time data events are stored in an Amazon Web Services service before being processed and stored in data lake.
", "smithy.api#examples": [ { "title": "Successful SendDataIntegrationEvent for inboundorder event type", @@ -4947,6 +6843,23 @@ "output": { "eventId": "9abaee56-5dc4-4c31-8250-3206a651d8a1" } + }, + { + "title": "Successful SendDataIntegrationEvent for dataset event type", + "input": { + "instanceId": "8928ae12-15e5-4441-825d-ec2184f0a43a", + "eventType": "scn.data.dataset", + "data": "{\"dataset_id\": \"datset-id-test-123\" }", + "eventGroupId": "datasetId", + "eventTimestamp": 1.515531081123e9, + "datasetTarget": { + "datasetIdentifier": "arn:aws:scn:us-west-2:135808960812:instance/8928ae12-15e5-4441-825d-ec2184f0a43a/namespaces/asc/datasets/product", + "operationType": "APPEND" + } + }, + "output": { + "eventId": "19739c8e-cd2e-4cbc-a2f7-0dc43239f042" + } } ], "smithy.api#http": { @@ -4971,37 +6884,43 @@ "eventType": { "target": "com.amazonaws.supplychain#DataIntegrationEventType", "traits": { - "smithy.api#documentation": "The data event type.
", + "smithy.api#documentation": "The data event type.
\n\n scn.data.dataset - Send data directly to any specified dataset.
\n\n scn.data.supplyplan - Send data to supply_plan dataset.
\n\n scn.data.shipmentstoporder - Send data to shipment_stop_order dataset.
\n\n scn.data.shipmentstop - Send data to shipment_stop dataset.
\n\n scn.data.shipment - Send data to shipment dataset.
\n\n scn.data.reservation - Send data to reservation dataset.
\n\n scn.data.processproduct - Send data to process_product dataset.
\n\n scn.data.processoperation - Send data to process_operation dataset.
\n\n scn.data.processheader - Send data to process_header dataset.
\n\n scn.data.forecast - Send data to forecast dataset.
\n\n scn.data.inventorylevel - Send data to inv_level dataset.
\n\n scn.data.inboundorder - Send data to inbound_order dataset.
\n\n scn.data.inboundorderline - Send data to inbound_order_line dataset.
\n\n scn.data.inboundorderlineschedule - Send data to inbound_order_line_schedule dataset.
\n\n scn.data.outboundorderline - Send data to outbound_order_line dataset.
\n\n scn.data.outboundshipment - Send data to outbound_shipment dataset.
\nThe data payload of the event. For more information on the data schema to use, see Data entities supported in AWS Supply Chain.
", + "smithy.api#documentation": "The data payload of the event, should follow the data schema of the target dataset, or see Data entities supported in AWS Supply Chain. To send single data record, use JsonObject format; to send multiple data records, use JsonArray format.
\nNote that for AWS Supply Chain dataset under asc namespace, it has a connection_id internal field that is not allowed to be provided by client directly, they will be auto populated.
", "smithy.api#required": {} } }, "eventGroupId": { "target": "com.amazonaws.supplychain#DataIntegrationEventGroupId", "traits": { - "smithy.api#documentation": "Event identifier (for example, orderId for InboundOrder) used for data sharing or partitioning.
", + "smithy.api#documentation": "Event identifier (for example, orderId for InboundOrder) used for data sharding or partitioning. Noted under one eventGroupId of same eventType and instanceId, events are processed sequentially in the order they are received by the server.
", "smithy.api#required": {} } }, "eventTimestamp": { "target": "smithy.api#Timestamp", "traits": { - "smithy.api#documentation": "The event timestamp (in epoch seconds).
", + "smithy.api#documentation": "The timestamp (in epoch seconds) associated with the event. If not provided, it will be assigned with current timestamp.
", "smithy.api#timestampFormat": "epoch-seconds" } }, "clientToken": { "target": "com.amazonaws.supplychain#ClientToken", "traits": { - "smithy.api#documentation": "The idempotent client token.
", + "smithy.api#documentation": "The idempotent client token. The token is active for 8 hours, and within its lifetime, it ensures the request completes only once upon retry with same client token. If omitted, the AWS SDK generates a unique value so that AWS SDK can safely retry the request upon network errors.
", "smithy.api#idempotencyToken": {} } + }, + "datasetTarget": { + "target": "com.amazonaws.supplychain#DataIntegrationEventDatasetTargetConfiguration", + "traits": { + "smithy.api#documentation": "The target dataset configuration for scn.data.dataset event type.
" + } } }, "traits": { @@ -5382,7 +7301,22 @@ "target": { "targetType": "DATASET", "datasetTarget": { - "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + "options": { + "loadType": "REPLACE", + "dedupeRecords": true, + "dedupeStrategy": { + "type": "FIELD_PRIORITY", + "fieldPriority": { + "fields": [ + { + "name": "eff_start_date", + "sortOrder": "ASC" + } + ] + } + } + } } } }, @@ -5415,7 +7349,22 @@ "target": { "targetType": "DATASET", "datasetTarget": { - "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner" + "datasetIdentifier": "arn:aws:scn:us-east-1:123456789012:instance/8850c54e-e187-4fa7-89d4-6370f165174d/namespaces/asc/datasets/trading_partner", + "options": { + "loadType": "REPLACE", + "dedupeRecords": true, + "dedupeStrategy": { + "type": "FIELD_PRIORITY", + "fieldPriority": { + "fields": [ + { + "name": "eff_start_date", + "sortOrder": "ASC" + } + ] + } + } + } } }, "createdTime": 1.72495640044e9, @@ -5733,6 +7682,32 @@ "name": "creation_time", "type": "TIMESTAMP", "isRequired": false + }, + { + "name": "quantity", + "type": "LONG", + "isRequired": false + } + ], + "primaryKeys": [ + { + "name": "id" + } + ] + }, + "partitionSpec": { + "fields": [ + { + "name": "creation_time", + "transform": { + "type": "DAY" + } + }, + { + "name": "description", + "transform": { + "type": "IDENTITY" + } } ] } @@ -5759,9 +7734,9 @@ } }, "namespace": { - "target": "com.amazonaws.supplychain#DataLakeDatasetNamespace", + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", "traits": { - "smithy.api#documentation": "The name space of the dataset. The available values are:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:
\n\n asc - For information on the Amazon Web Services Supply Chain supported datasets see https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
\n\n default - For datasets with custom user-defined schemas.
\nThe name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", + "smithy.api#documentation": "The name of the dataset. For asc namespace, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.
", "smithy.api#httpLabel": {}, "smithy.api#required": {} } @@ -5803,6 +7778,108 @@ "smithy.api#output": {} } }, + "com.amazonaws.supplychain#UpdateDataLakeNamespace": { + "type": "operation", + "input": { + "target": "com.amazonaws.supplychain#UpdateDataLakeNamespaceRequest" + }, + "output": { + "target": "com.amazonaws.supplychain#UpdateDataLakeNamespaceResponse" + }, + "errors": [ + { + "target": "com.amazonaws.supplychain#AccessDeniedException" + }, + { + "target": "com.amazonaws.supplychain#InternalServerException" + }, + { + "target": "com.amazonaws.supplychain#ResourceNotFoundException" + }, + { + "target": "com.amazonaws.supplychain#ThrottlingException" + }, + { + "target": "com.amazonaws.supplychain#ValidationException" + } + ], + "traits": { + "smithy.api#documentation": "Enables you to programmatically update an Amazon Web Services Supply Chain data lake namespace. Developers can update the description of a data lake namespace for a given instance ID and namespace name.
", + "smithy.api#examples": [ + { + "title": "Update description of an existing AWS Supply Chain namespace", + "input": { + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "description": "This is an updated AWS Supply Chain namespace" + }, + "output": { + "namespace": { + "arn": "arn:aws:scn:us-east-1:012345678910:instance/1877dd20-dee9-4639-8e99-cb67acf21fe5/namespaces/my_namespace", + "instanceId": "1877dd20-dee9-4639-8e99-cb67acf21fe5", + "name": "my_namespace", + "description": "This is an updated AWS Supply Chain namespace", + "createdTime": 1.736892560751e9, + "lastModifiedTime": 1.736892586156e9 + } + } + } + ], + "smithy.api#http": { + "code": 200, + "method": "PATCH", + "uri": "/api/datalake/instance/{instanceId}/namespaces/{name}" + } + } + }, + "com.amazonaws.supplychain#UpdateDataLakeNamespaceRequest": { + "type": "structure", + "members": { + "instanceId": { + "target": "com.amazonaws.supplychain#UUID", + "traits": { + "smithy.api#documentation": "The Amazon Web Services Chain instance identifier.
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "name": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceName", + "traits": { + "smithy.api#documentation": "The name of the namespace. Noted you cannot update namespace with name starting with asc, default, scn, aws, amazon, amzn\n
", + "smithy.api#httpLabel": {}, + "smithy.api#required": {} + } + }, + "description": { + "target": "com.amazonaws.supplychain#DataLakeNamespaceDescription", + "traits": { + "smithy.api#documentation": "The updated description of the data lake namespace.
" + } + } + }, + "traits": { + "smithy.api#documentation": "The request parameters of UpdateDataLakeNamespace.
", + "smithy.api#input": {} + } + }, + "com.amazonaws.supplychain#UpdateDataLakeNamespaceResponse": { + "type": "structure", + "members": { + "namespace": { + "target": "com.amazonaws.supplychain#DataLakeNamespace", + "traits": { + "smithy.api#documentation": "The updated namespace details.
", + "smithy.api#nestedProperties": {}, + "smithy.api#required": {} + } + } + }, + "traits": { + "smithy.api#documentation": "The response parameters of UpdateDataLakeNamespace.
", + "smithy.api#output": {} + } + }, "com.amazonaws.supplychain#UpdateInstance": { "type": "operation", "input": { diff --git a/codegen/smithy-aws-typescript-codegen/src/main/resources/software/amazon/smithy/aws/typescript/codegen/endpoints.json b/codegen/smithy-aws-typescript-codegen/src/main/resources/software/amazon/smithy/aws/typescript/codegen/endpoints.json index c943dc397f5f..38cc39f7b79d 100644 --- a/codegen/smithy-aws-typescript-codegen/src/main/resources/software/amazon/smithy/aws/typescript/codegen/endpoints.json +++ b/codegen/smithy-aws-typescript-codegen/src/main/resources/software/amazon/smithy/aws/typescript/codegen/endpoints.json @@ -14710,6 +14710,7 @@ "ap-southeast-3": {}, "ap-southeast-4": {}, "ap-southeast-5": {}, + "ap-southeast-7": {}, "ca-central-1": {}, "ca-west-1": {}, "eu-central-1": {}, @@ -44387,6 +44388,11 @@ } } }, + "securityhub": { + "endpoints": { + "us-isob-east-1": {} + } + }, "servicediscovery": { "endpoints": { "us-isob-east-1": {} diff --git a/lerna.json b/lerna.json index dbc63fece9f8..37e2946bacef 100644 --- a/lerna.json +++ b/lerna.json @@ -1,5 +1,5 @@ { - "version": "3.807.0", + "version": "3.808.0", "npmClient": "yarn", "useWorkspaces": true, "command": { diff --git a/lib/lib-dynamodb/CHANGELOG.md b/lib/lib-dynamodb/CHANGELOG.md index 3af70951396e..e6459df375a4 100644 --- a/lib/lib-dynamodb/CHANGELOG.md +++ b/lib/lib-dynamodb/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/lib-dynamodb + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/lib-dynamodb diff --git a/lib/lib-dynamodb/package.json b/lib/lib-dynamodb/package.json index b56aad2730da..bda9e5176829 100644 --- a/lib/lib-dynamodb/package.json +++ b/lib/lib-dynamodb/package.json @@ -1,6 +1,6 @@ { "name": "@aws-sdk/lib-dynamodb", - "version": "3.806.0", + "version": "3.808.0", "description": "The document client simplifies working with items in Amazon DynamoDB by abstracting away the notion of attribute values.", "main": "./dist-cjs/index.js", "module": "./dist-es/index.js", @@ -31,7 +31,7 @@ "@aws-sdk/core": "*", "@aws-sdk/util-dynamodb": "*", "@smithy/core": "^3.3.1", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "tslib": "^2.6.2" }, diff --git a/lib/lib-storage/CHANGELOG.md b/lib/lib-storage/CHANGELOG.md index e0124d084b5d..29dc717c32fd 100644 --- a/lib/lib-storage/CHANGELOG.md +++ b/lib/lib-storage/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/lib-storage + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/lib-storage diff --git a/lib/lib-storage/package.json b/lib/lib-storage/package.json index 5997ec59de17..4c5c596fb32f 100644 --- a/lib/lib-storage/package.json +++ b/lib/lib-storage/package.json @@ -1,6 +1,6 @@ { "name": "@aws-sdk/lib-storage", - "version": "3.806.0", + "version": "3.808.0", "description": "Storage higher order operation", "main": "./dist-cjs/index.js", "module": "./dist-es/index.js", @@ -29,8 +29,8 @@ "license": "Apache-2.0", "dependencies": { "@smithy/abort-controller": "^4.0.2", - "@smithy/middleware-endpoint": "^4.1.3", - "@smithy/smithy-client": "^4.2.3", + "@smithy/middleware-endpoint": "^4.1.4", + "@smithy/smithy-client": "^4.2.4", "buffer": "5.6.0", "events": "3.3.0", "stream-browserify": "3.0.0", diff --git a/packages/core/CHANGELOG.md b/packages/core/CHANGELOG.md index 9e782966fbbc..b5be43daca59 100644 --- a/packages/core/CHANGELOG.md +++ b/packages/core/CHANGELOG.md @@ -3,6 +3,14 @@ All notable changes to this project will be documented in this file. See [Conventional Commits](https://conventionalcommits.org) for commit guidelines. +# [3.808.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.807.0...v3.808.0) (2025-05-12) + +**Note:** Version bump only for package @aws-sdk/core + + + + + # [3.806.0](https://github.com/aws/aws-sdk-js-v3/compare/v3.805.0...v3.806.0) (2025-05-08) **Note:** Version bump only for package @aws-sdk/core diff --git a/packages/core/package.json b/packages/core/package.json index d63f0dc4b5a3..6cb9a98c1bab 100644 --- a/packages/core/package.json +++ b/packages/core/package.json @@ -1,6 +1,6 @@ { "name": "@aws-sdk/core", - "version": "3.806.0", + "version": "3.808.0", "description": "Core functions & classes shared by multiple AWS SDK clients.", "scripts": { "build": "yarn lint && concurrently 'yarn:build:cjs' 'yarn:build:es' 'yarn:build:types'", @@ -83,11 +83,11 @@ "dependencies": { "@aws-sdk/types": "*", "@smithy/core": "^3.3.1", - "@smithy/node-config-provider": "^4.1.0", + "@smithy/node-config-provider": "^4.1.1", "@smithy/property-provider": "^4.0.2", "@smithy/protocol-http": "^5.1.0", "@smithy/signature-v4": "^5.1.0", - "@smithy/smithy-client": "^4.2.3", + "@smithy/smithy-client": "^4.2.4", "@smithy/types": "^4.2.0", "@smithy/util-middleware": "^4.0.2", "fast-xml-parser": "4.4.1", diff --git a/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.spec.ts b/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.spec.ts index b11ff6f4d10e..c1ad898c14bb 100644 --- a/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.spec.ts +++ b/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.spec.ts @@ -1,15 +1,19 @@ import { afterEach, describe, expect, test as it, vi } from "vitest"; import { getArrayForCommaSeparatedString } from "../utils/getArrayForCommaSeparatedString"; +import { getBearerTokenEnvKey } from "../utils/getBearerTokenEnvKey"; import { NODE_AUTH_SCHEME_PREFERENCE_OPTIONS } from "./NODE_AUTH_SCHEME_PREFERENCE_OPTIONS"; vi.mock("../utils/getArrayForCommaSeparatedString"); +vi.mock("../utils/getBearerTokenEnvKey"); describe("NODE_AUTH_SCHEME_PREFERENCE_OPTIONS", () => { const mockInput = "a,b,c"; const mockOutput = ["a", "b", "c"]; + const mockBearerTokenEnvKey = "AWS_BEARER_TOKEN_SERVICE_NAME"; vi.mocked(getArrayForCommaSeparatedString).mockReturnValue(mockOutput); + vi.mocked(getBearerTokenEnvKey).mockReturnValue(mockBearerTokenEnvKey); afterEach(() => { vi.clearAllMocks(); @@ -19,18 +23,42 @@ describe("NODE_AUTH_SCHEME_PREFERENCE_OPTIONS", () => { it("returns undefined if no value is provided", () => { expect(func({})).toEqual(undefined); expect(getArrayForCommaSeparatedString).not.toBeCalled(); + expect(getBearerTokenEnvKey).not.toBeCalled(); }); it("returns list if value is defined", () => { expect(func({ [key]: mockInput })).toEqual(mockOutput); expect(getArrayForCommaSeparatedString).toHaveBeenCalledTimes(1); expect(getArrayForCommaSeparatedString).toBeCalledWith(mockInput); + expect(getBearerTokenEnvKey).not.toBeCalled(); }); }; describe("environmentVariableSelector", () => { const { environmentVariableSelector } = NODE_AUTH_SCHEME_PREFERENCE_OPTIONS; test(environmentVariableSelector, "AWS_AUTH_SCHEME_PREFERENCE"); + + describe("if signingName is defined", () => { + const env = { AWS_AUTH_SCHEME_PREFERENCE: mockInput }; + const options = { signingName: "Signing Name" }; + + afterEach(() => { + expect(getBearerTokenEnvKey).toHaveBeenCalledTimes(1); + expect(getBearerTokenEnvKey).toBeCalledWith(options.signingName); + }); + + it(`ignores if mockBearerTokenEnvKey is not set`, () => { + expect(environmentVariableSelector(env, options)).toEqual(mockOutput); + expect(getArrayForCommaSeparatedString).toHaveBeenCalledTimes(1); + expect(getArrayForCommaSeparatedString).toBeCalledWith(mockInput); + }); + + it("returns ['httpBearerAuth'] if mockBearerTokenEnvKey is set", () => { + const envWithToken = { ...env, [mockBearerTokenEnvKey]: "token" }; + expect(environmentVariableSelector(envWithToken, options)).toEqual(["httpBearerAuth"]); + expect(getArrayForCommaSeparatedString).not.toHaveBeenCalled(); + }); + }); }); describe("configFileSelector", () => { diff --git a/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.ts b/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.ts index 5417d122c725..c6f285b84d13 100644 --- a/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.ts +++ b/packages/core/src/submodules/httpAuthSchemes/aws_sdk/NODE_AUTH_SCHEME_PREFERENCE_OPTIONS.ts @@ -1,6 +1,7 @@ -import { LoadedConfigSelectors } from "@smithy/node-config-provider"; +import { EnvOptions, LoadedConfigSelectors } from "@smithy/node-config-provider"; import { getArrayForCommaSeparatedString } from "../utils/getArrayForCommaSeparatedString"; +import { getBearerTokenEnvKey } from "../utils/getBearerTokenEnvKey"; const NODE_AUTH_SCHEME_PREFERENCE_ENV_KEY = "AWS_AUTH_SCHEME_PREFERENCE"; const NODE_AUTH_SCHEME_PREFERENCE_CONFIG_KEY = "auth_scheme_preference"; @@ -14,7 +15,11 @@ export const NODE_AUTH_SCHEME_PREFERENCE_OPTIONS: LoadedConfigSelectors