-
Notifications
You must be signed in to change notification settings - Fork 25.7k
[DCP] Always create requests for non-tensor objects #125334
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Conversation
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/125334
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New Failures, 1 Unrelated FailureAs of commit 9cd89e4 with merge base 746da87 ( NEW FAILURES - The following jobs have failed:
FLAKY - The following job failed but was likely due to flakiness present on trunk:
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM!
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
lgtm
|
@pytorchbot merge -f "The failing tests are not related." |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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
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
* [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>
…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
…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>
Stack from ghstack (oldest at bottom):
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.
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 @LucasLLC