[dynamo] Use the new get_unique_name_wrt helper when applicable
#146950
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This was referenced Feb 11, 2025
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/146950
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit bae3c97 with merge base 6061664 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Feb 21, 2025
zou3519
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Feb 25, 2025
| name = candidate_name | ||
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| name = get_unique_name_wrt(name, self.input_name_to_proxy) |
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is there a way to get this to always append a number, like before?
zou3519
reviewed
Feb 25, 2025
| name = candidate_name | ||
| break | ||
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| name = get_unique_name_wrt(name, self.input_name_to_proxy) |
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is there a way to get this to always append a number, like before? I'm not sure that it matters but it's nice for the invariant to be "the name is foobar_i" where i is a number
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Yeah lemme try that, otherwise there's too many tests to update lol.
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Sad -- either way we'll need to update a bunch of test so I added a requires_suffix=False flag to preserve the existing behavior.
zou3519
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Feb 25, 2025
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Starting merge as part of PR stack under #147572 |
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As title, also see 1. new test `test_nonstrict_trace_on_method` for example. 2. newly added comments for why we need special treatment on methods. Pull Request resolved: #147571 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367, #146950
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…`-ed function (#147572) As title. Without this patch we get the following error: Tweaking the `allow_non_fake_inputs` flag on tensor mode doesn't quite work for AOTAutograd, which also needs to fake-tensor-propagate the `nonstrict_trace`-ed function, but that's _after_ Dynamo has handled the `nonstrict_trace` processing and put the `flat_apply(...)` node into the graph. So we can't easily to temporarily enable the `allow_non_fake_inputs` flag on current fake mode, when AOTAutograd processes a `flat_apply` node from Dynamo's `nonstrict_trace` handling. And after discussing with zou3519, I decided to add a global `FakeTensorTLS` that contains a `allow_non_fake_inputs_override` flag, and patch the `nonstrict_trace`-ed function to temporarily tweak this flag during its execution. Pull Request resolved: #147572 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367, #146950, #147571
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Feb 27, 2025
Summary: This patch removes some duplicated name generation logic in Dynamo. X-link: pytorch/pytorch#146950 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367 Reviewed By: wdvr Differential Revision: D70270821 fbshipit-source-id: cc8a04342adb2056f19709007ef45e3ad6ee34f8
aditew01
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Feb 28, 2025
…46950) This patch removes some duplicated name generation logic in Dynamo. Pull Request resolved: #146950 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367
aditew01
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As title, also see 1. new test `test_nonstrict_trace_on_method` for example. 2. newly added comments for why we need special treatment 9E12 on methods. Pull Request resolved: #147571 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367, #146950
aditew01
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Feb 28, 2025
…`-ed function (#147572) As title. Without this patch we get the following error: Tweaking the `allow_non_fake_inputs` flag on tensor mode doesn't quite work for AOTAutograd, which also needs to fake-tensor-propagate the `nonstrict_trace`-ed function, but that's _after_ Dynamo has handled the `nonstrict_trace` processing and put the `flat_apply(...)` node into the graph. So we can't easily to temporarily enable the `allow_non_fake_inputs` flag on current fake mode, when AOTAutograd processes a `flat_apply` node from Dynamo's `nonstrict_trace` handling. And after discussing with zou3519, I decided to add a global `FakeTensorTLS` that contains a `allow_non_fake_inputs_override` flag, and patch the `nonstrict_trace`-ed function to temporarily tweak this flag during its execution. Pull Request resolved: #147572 Approved by: https://github.com/zou3519 ghstack dependencies: #146714, #146367, #146950, #147571
majing921201
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Mar 4, 2025
…torch#146950) This patch removes some duplicated name generation logic in Dynamo. Pull Request resolved: pytorch#146950 Approved by: https://github.com/zou3519 ghstack dependencies: pytorch#146714, pytorch#146367
majing921201
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Mar 4, 2025
As title, also see 1. new test `test_nonstrict_trace_on_method` for example. 2. newly added comments for why we need special treatment on methods. Pull Request resolved: pytorch#147571 Approved by: https://github.com/zou3519 ghstack dependencies: pytorch#146714, pytorch#146367, pytorch#146950
majing921201
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Mar 4, 2025
…`-ed function (pytorch#147572) As title. Without this patch we get the following error: Tweaking the `allow_non_fake_inputs` flag on tensor mode doesn't quite work for AOTAutograd, which also needs to fake-tensor-propagate the `nonstrict_trace`-ed function, but that's _after_ Dynamo has handled the `nonstrict_trace` processing and put the `flat_apply(...)` node into the graph. So we can't easily to temporarily enable the `allow_non_fake_inputs` flag on current fake mode, when AOTAutograd processes a `flat_apply` node from Dynamo's `nonstrict_trace` handling. And after discussing with zou3519, I decided to add a global `FakeTensorTLS` that contains a `allow_non_fake_inputs_override` flag, and patch the `nonstrict_trace`-ed function to temporarily tweak this flag during its execution. Pull Request resolved: pytorch#147572 Approved by: https://github.com/zou3519 ghstack dependencies: pytorch#146714, pytorch#146367, pytorch#146950, pytorch#147571
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Stack from ghstack (oldest at bottom):
nonstrict_trace-ed function #147572nonstrict_traceon class method #147571get_unique_name_wrthelper when applicable #146950nonstrict_trace#146367flat_apply#146714This patch removes some duplicated name generation logic in Dynamo.
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov