forked from tangger/lerobot
e82e7a02e9
* Enhance training and logging functionality with accelerator support - 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. * Initialize logging in training script for both main and non-main processes - 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. * add docs and only push model once * Place logging under accelerate and update docs * fix pre commit * only log in main process * main logging * try with local rank * add tests * change runner * fix test * dont push to hub in multi gpu tests * pre download dataset in tests * small fixes * fix path optimizer state * update docs, and small improvements in train * simplify accelerate main process detection * small improvements in train * fix OOM bug * change accelerate detection * add some debugging * always use accelerate * cleanup update method * cleanup * fix bug * scale lr decay if we reduce steps * cleanup logging * fix formatting * encorperate feedback pr * add min memory to cpu tests * use accelerate to determin logging * fix precommit and fix tests * chore: minor details --------- Co-authored-by: AdilZouitine <adilzouitinegm@gmail.com> Co-authored-by: Steven Palma <steven.palma@huggingface.co>
89 lines
2.0 KiB
YAML
89 lines
2.0 KiB
YAML
- sections:
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- local: index
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title: LeRobot
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- local: installation
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title: Installation
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title: Get started
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- sections:
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- local: il_robots
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title: Imitation Learning for Robots
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- local: cameras
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title: Cameras
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- local: integrate_hardware
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title: Bring Your Own Hardware
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- local: hilserl
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title: Train a Robot with RL
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- local: hilserl_sim
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title: Train RL in Simulation
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- local: async
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title: Use Async Inference
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- local: multi_gpu_training
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title: Multi GPU training
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title: "Tutorials"
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- sections:
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- local: lerobot-dataset-v3
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title: Using LeRobotDataset
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- local: porting_datasets_v3
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title: Porting Large Datasets
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- local: using_dataset_tools
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title: Using the Dataset Tools
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title: "Datasets"
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- sections:
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- local: act
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title: ACT
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- local: smolvla
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title: SmolVLA
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- local: pi0
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title: π₀ (Pi0)
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- local: pi05
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title: π₀.₅ (Pi05)
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title: "Policies"
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- sections:
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- local: il_sim
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title: Imitation Learning in Sim
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- local: libero
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title: Using Libero
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- local: metaworld
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title: Using MetaWorld
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title: "Simulation"
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- sections:
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- local: introduction_processors
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title: Introduction to Robot Processors
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- local: debug_processor_pipeline
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title: Debug your processor pipeline
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- local: implement_your_own_processor
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title: Implement your own processor
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- local: processors_robots_teleop
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title: Processors for Robots and Teleoperators
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title: "Robot Processors"
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- sections:
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- local: so101
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title: SO-101
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- local: so100
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title: SO-100
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- local: koch
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title: Koch v1.1
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- local: lekiwi
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title: LeKiwi
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- local: hope_jr
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title: Hope Jr
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- local: reachy2
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title: Reachy 2
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title: "Robots"
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- sections:
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- local: phone_teleop
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title: Phone
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title: "Teleoperators"
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- sections:
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- local: notebooks
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title: Notebooks
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- local: feetech
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title: Updating Feetech Firmware
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title: "Resources"
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- sections:
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- local: contributing
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title: Contribute to LeRobot
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- local: backwardcomp
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title: Backward compatibility
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title: "About"
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