feat(train): add accelerate for multi gpu training #2154
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- Added support for multi-GPU training by introducing an `accelerator` parameter in training functions. - Updated `update_policy` to handle gradient updates based on the presence of an accelerator. - Modified logging to prevent duplicate messages in non-main processes. - Enhanced `set_seed` and `get_safe_torch_device` functions to accommodate accelerator usage. - Updated `MetricsTracker` to account for the number of processes when calculating metrics. - Introduced a new feature in `pyproject.toml` for the `accelerate` library dependency.
…esses - Added `init_logging` calls to ensure proper logging setup when using the accelerator and in standard training mode. - This change enhances the clarity and consistency of logging during training sessions.
pkooij
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
…gface/lerobot into feat/accelerate-melt-gpus
…gface/lerobot into feat/accelerate-melt-gpus
…gface/lerobot into feat/accelerate-melt-gpus
michel-aractingi
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michel-aractingi
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This PR adds accelerate integration and docs to LeRobot. We keep it basic and not yet add all accelerate options (deep speed etc)
lerobot_train.pyand so we can utilize their methods for device discovery etc.Tested