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fairseq[-hydra]-train torchrun compatibility: default device_id set to LOCAL_RANK if exists (#4351)
Summary: # Before submitting - [x] Was this discussed/approved via a Github issue? (no need for typos, doc improvements) - [x] Did you read the [contributor guideline](https://github.com/pytorch/fairseq/blob/main/CONTRIBUTING.md)? - [x] Did you make sure to update the docs? - [x] Did you write any new necessary tests? ## What does this PR do? Fixes https://github.com/pytorch/fairseq/issues/4302 (issue). ## PR review Anyone in the community is free to review the PR once the tests have passed. If we didn't discuss your PR in Github issues there's a high chance it will not be merged. ## Did you have fun? I had fun when I figured out why torchrun was failing :) Pull Request resolved: https://github.com/pytorch/fairseq/pull/4351 Reviewed By: shruti-bh Differential Revision: D35784181 Pulled By: dianaml0 fbshipit-source-id: 560c7af12b2f9278cba6c85711b98b9e043d0ec9
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@ -3,6 +3,7 @@
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import os
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import sys
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from dataclasses import _MISSING_TYPE, dataclass, field
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from typing import Any, List, Optional
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@ -285,9 +286,9 @@ class DistributedTrainingConfig(FairseqDataclass):
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},
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)
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device_id: int = field(
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default=0,
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default=os.getenv("LOCAL_RANK", 0),
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metadata={
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"help": "which GPU to use (usually configured automatically)",
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"help": "which GPU to use (by default looks for $LOCAL_RANK, usually configured automatically)",
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"argparse_alias": "--local_rank",
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},
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)
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