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[DataPipe] Full graph fast-forwarding #79658
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This was referenced Jun 15, 2022
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❌ 1 New FailuresAs of commit df95128 (more details on the Dr. CI page): Expand to see more
🕵️ 1 new failure recognized by patternsThe following CI failures do not appear to be due to upstream breakages
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WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: 1. Source (e.g. IterableWrapper) 2. Stateless (e.g. Mapper) 3. Statefull (e.g. Shuffler) [ghstack-poisoned]
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Looks like this PR hasn't been updated in a while so we're going to go ahead and mark this as |
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/easycla As part of the transition to the PyTorch Foundation, this project now requires contributions be covered under the new CLA. See #85559 for additional details. This comment will trigger a new check of this PR. If you are already covered, you will simply see a new "EasyCLA" check that passes. If you are not covered, a bot will leave a new comment with a link to sign. |
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cla signed
module: data
torch.utils.data
module: dataloader
Related to torch.utils.data.DataLoader and Sampler
Stale
topic: new features
topic category
2 participants
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Stack from ghstack:
WIP - this will be a more efficient implementation of snapshotting. In particular, it will differentiate between three types of DataPipes: