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add fault-tolerance for global random state in map-style datasets #8950

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merged 108 commits into from
Aug 26, 2021

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@awaelchli awaelchli commented Aug 17, 2021

What does this PR do?

Follow up to #3022 and #8891

Add support for reloading global random state in a map-style dataset when fault-tolerant training is enabled.

Not implemented (will be addressed in future PR):

  • iterable datasets
  • multiple training dataloaders (combined loader)
  • local random state through generators inside the dataset
  • when num_workers=N, we cannot be fault-tolerant during the first N batches being processed/fetched.

Future follow up PRs will cover:

  • the above listed items
  • benchmarking

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I made sure I had fun coding 🙃

@awaelchli awaelchli changed the title Thomas/fault tolerant rng state add fault-tolerance for global random state in map-style datasets Aug 17, 2021
@awaelchli awaelchli added the feature Is an improvement or enhancement label Aug 17, 2021
@awaelchli awaelchli added this to the v1.5 milestone Aug 17, 2021
@awaelchli awaelchli force-pushed the thomas/fault-tolerant-rng-state branch from fd66d1f to db9acb7 Compare August 17, 2021 12:25
@Borda Borda requested a review from ananthsub August 24, 2021 16:44
@mergify mergify bot removed the has conflicts label Aug 25, 2021
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LGTM :]

pytorch_lightning/trainer/supporters.py Outdated Show resolved Hide resolved
@awaelchli awaelchli mentioned this pull request Aug 26, 2021
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@tchaton tchaton enabled auto-merge (squash) August 26, 2021 10:45
@tchaton tchaton merged commit b13749b into master Aug 26, 2021
@tchaton tchaton deleted the thomas/fault-tolerant-rng-state branch August 26, 2021 12:13
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6 participants