[PT2D] Ensure the trace rules are correct with distributed #125333
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/125333
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit 476470c with merge base 746da87 ( FLAKY - The following job failed but was likely due to flakiness present on trunk:
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ciflow/inductor
module: dynamo
oncall: distributed
This was referenced May 1, 2024
yanboliang
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May 2, 2024
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
petrex
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May 3, 2024
…25333) Summary: 1. Avoid using `torch._dynamo.disable`. 2. Clear the LRU cache of the trace rules. This won't do anything if rules are not evluated before PG initilization. Pull Request resolved: pytorch#125333 Approved by: https://github.com/yanboliang
pytorchmergebot
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May 7, 2024
Summary: 1. Remove gc.collect(), which is not necessary. 2. Use lru_cache to cache _get_fqns Pull Request resolved: #125501 Approved by: https://github.com/wz337, https://github.com/LucasLLC ghstack dependencies: #125333
pytorchmergebot
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May 7, 2024
Summary: If an object only exists on certain non-coordinator ranks, we still need to save them. Otherwise, we lose these objects. If they are duplicated, DCP will deduplicate them. Pull Request resolved: #125334 Approved by: https://github.com/wz337, https://github.com/LucasLLC ghstack dependencies: #125333, #125501
pytorchmergebot
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May 7, 2024
Summary: Right now DCP only flatten a mapping (e.g., dict) if that mapping has tensor objects. This behavior is odd as users may save different non-tensor objects on different ranks. Without flattening the mappings, we may lose these non-tensor objects. One use case is dataloader state_dict. We may also want to do so for a list/tuple. But this will cause extra pickles. So we don't do this for now. Pull Request resolved: #125335 Approved by: https://github.com/LucasLLC, https://github.com/wz337 ghstack dependencies: #125333, #125501, #125334
mvpatel2000
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May 17, 2024
Summary: distributed_state_dict should not try to use `getattr` to get `_extra_state` as this is not well-defined. Pull Request resolved: pytorch#125336 Approved by: https://github.com/LucasLLC ghstack dependencies: pytorch#125333, pytorch#125501, pytorch#125334, pytorch#125335
atalman
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May 27, 2024
* [DSD] Correctly handle _extra_state (#125336) Summary: distributed_state_dict should not try to use `getattr` to get `_extra_state` as this is not well-defined. Pull Request resolved: #125336 Approved by: https://github.com/LucasLLC ghstack dependencies: #125333, #125501, #125334, #125335 * lint * lint --------- Co-authored-by: Chien-Chin Huang <chienchin@fb.com> Co-authored-by: Andrey Talman <atalman@fb.com>
antoinebrl
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May 27, 2024
…ytorch#125337) Summary: Fixes pytorch#122792 state_dict includes only persistent buffers, while named_buffers() would include non_persistent buffers. Pull Request resolved: pytorch#125337 Approved by: https://github.com/awgu ghstack dependencies: pytorch#125333, pytorch#125501, pytorch#125334, pytorch#125335, pytorch#125336
huydhn
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May 27, 2024
…125337) (#127219) * [DSD] Fix to remove non_persistent buffer in distributed state dict (#125337) Summary: Fixes #122792 state_dict includes only persistent buffers, while named_buffers() would include non_persistent buffers. Pull Request resolved: #125337 Approved by: https://github.com/awgu ghstack dependencies: #125333, #125501, #125334, #125335, #125336 * lintrunner * lint --------- Co-authored-by: Chien-Chin Huang <chienchin@fb.com> Co-authored-by: Andrey Talman <atalman@fb.com>
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Stack from ghstack (oldest at bottom):
Summary:
torch._dynamo.disable.cc @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @H-Huang @kwen2501 @awgu @penguinwu @XilunWu @wanchaol @fduwjj @wz337 @tianyu-l @wconstab @yf225 @chauhang @d4l3k @voznesenskym @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @chenyang78 @kadeng