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refactor(policies): rename policies/sac → policies/gaussian_actor

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Khalil Meftah
2026-04-23 19:13:18 +02:00
parent 8065bf15c7
commit 06255996ea
24 changed files with 185 additions and 168 deletions
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@@ -820,10 +820,10 @@ The LeRobot system uses a distributed actor-learner architecture for training. T
Create a training configuration file (example available [here](https://huggingface.co/datasets/lerobot/config_examples/resolve/main/rl/train_config.json)). The training config is based on the main `TrainRLServerPipelineConfig` class in `lerobot/configs/train.py`.
1. Configure the policy settings (`type="sac"`, `device`, etc.)
1. Configure the policy settings (`type="gaussian_actor"`, `device`, etc.)
2. Set `dataset` to your cropped dataset
3. Configure environment settings with crop parameters
4. Check the other parameters related to SAC in [configuration_sac.py](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/sac/configuration_sac.py#L79).
4. Check the other parameters related to the Gaussian Actor in [configuration_gaussian_actor.py](https://github.com/huggingface/lerobot/blob/main/src/lerobot/policies/gaussian_actor/configuration_gaussian_actor.py#L79).
5. Verify that the `policy` config is correct with the right `input_features` and `output_features` for your task.
**Starting the Learner**