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Update full finetune distributed for MM #1628

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merged 2 commits into from
Sep 23, 2024
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Context

What is the purpose of this PR? Is it to

  • add a new feature
  • fix a bug
  • update tests and/or documentation
  • other (please add here)

Updated fullfinetune_distributed to match the changes from #1548 . This adds gradient norm clipping, a configurable collate function, and batch unpacking for the model.

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Please make sure to do each of the following if applicable to your PR. If you're unsure about any one of these just ask and we will happily help. We also have a contributing page for some guidance on contributing.

  • run pre-commit hooks and linters (make sure you've first installed via pre-commit install)
  • add unit tests for any new functionality
  • update docstrings for any new or updated methods or classes
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  • run recipe tests via pytest tests -m integration_test
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If your function changed a public API, please add a dummy example of what the user experience will look like when calling it.
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  • I did not change any public API
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pytorch-bot bot commented Sep 19, 2024

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchtune/1628

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@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Sep 19, 2024
@@ -131,6 +137,7 @@ def __init__(self, cfg: DictConfig) -> None:
self.total_epochs = cfg.epochs
self.max_steps_per_epoch = cfg.max_steps_per_epoch
self.global_step = 0
self._clip_grad_norm = cfg.get("clip_grad_norm", None)
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Can we add a test case similar to this?

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One comment, otherwise looks good

@pbontrager pbontrager merged commit f51f894 into pytorch:main Sep 23, 2024
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@pbontrager pbontrager deleted the mm_dist branch September 23, 2024 16:19
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3 participants