Skip to content
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

Misc bug fixes in Zero optimizer: handling differentiable argument, optimizer_dtype #6454

Closed
wants to merge 2 commits into from

Conversation

amithrm
Copy link
Collaborator

@amithrm amithrm commented Feb 2, 2024

This a cumulative PR with misc bug fixes and updates to Zero Redundancy Optimizer from all the authors (AWS): Guangtai Huang, Rahul Solanki, Fei Wu, Amith Mamidala

@amithrm amithrm changed the title Fixing bug Misc bug fixes in Zero optimizer: handling differentiable argument, optimizer_dtype Feb 2, 2024
# Here we pop the differentiable default because the adam family of
# optimizers don't have differentiable as an argument. This should
# be fixed by this commit https://github.com/pytorch/pytorch/pull/86183
# and should be available in torch==2.0. For 1.13, we are patching it here.
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Hi @amithrm , here it says "This should be fixed by this commit pytorch/pytorch#86183 and should be available in torch==2.0." Can you remove this patch?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

yes

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Copy link
Collaborator

@alanwaketan alanwaketan left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Can we have a test case to cover the change?

pin_layout=self.pin_layout,
groups=self.sharding_groups,
)
sharded_data.append(shard_data)
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Is this gathering all the parameters into one bucket?

@jeffhataws
Copy link
Collaborator

The changes here should already be in #6025 , as confirmed by Guangtai.

@jeffhataws jeffhataws closed this Mar 22, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

3 participants