Only make a shallow copy when loading optimizer state_dict#106082
Closed
janeyx99 wants to merge 6 commits intogh/janeyx99/78/basefrom
Closed
Only make a shallow copy when loading optimizer state_dict#106082janeyx99 wants to merge 6 commits intogh/janeyx99/78/basefrom
janeyx99 wants to merge 6 commits intogh/janeyx99/78/basefrom
Conversation
[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/106082
Note: Links to docs will display an error until the docs builds have been completed. ✅ 2 Unrelated FailuresAs of commit 8aea828: UNSTABLE - The following jobs failed but were likely due to flakiness present on trunk and has been marked as unstable:
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This should also save memory when loading from a checkpoint. [ghstack-poisoned]
This should also save memory when loading from a checkpoint. [ghstack-poisoned]
janeyx99
commented
Jul 27, 2023
Skylion007
approved these changes
Jul 27, 2023
The thing we do still deep copy is the param_groups, which is much lighter weight. This should also save memory when loading from a checkpoint. The deepcopy was introduced in ecfcf39, but module.py had only a shallow copy at that point so it did not actually bring parity. [ghstack-poisoned]
The thing we do still deep copy is the param_groups, which is much lighter weight. This should also save memory when loading from a checkpoint. The deepcopy was introduced in ecfcf39, but module.py had only a shallow copy at that point so it did not actually bring parity. [ghstack-poisoned]
Contributor
Author
|
@pytorchbot merge |
Collaborator
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 |
Collaborator
Merge failedReason: Command Details for Dev Infra teamRaised by workflow job |
The thing we do still deep copy is the param_groups, which is much lighter weight. This should also save memory when loading from a checkpoint. The deepcopy was introduced in ecfcf39, but module.py had only a shallow copy at that point so it did not actually bring parity. Incorporates an XLA fix, which is why I'm updating the pin to pytorch/xla@ca5eab8 [ghstack-poisoned]
Contributor
Author
|
@pytorchbot merge |
Collaborator
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 |
6 tasks
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
The thing we do still deep copy is the param_groups, which is much lighter weight. This should also save memory when loading from a checkpoint.
The deepcopy was introduced in ecfcf39, but module.py had only a shallow copy at that point so it did not actually bring parity.
Incorporates an XLA fix, which is why I'm updating the pin to pytorch/xla@ca5eab8
Stack from ghstack (oldest at bottom):