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refactor(processor): clarify action types, distinguish PolicyAction, RobotAction, and EnvAction (#1908)

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* refactor(processor): split action from policy, robots and environment

- Updated function names to robot_action_to_transition and robot_transition_to_action across multiple files to better reflect their purpose in processing robot actions.
- Adjusted references in the RobotProcessorPipeline and related components to ensure compatibility with the new naming convention.
- Enhanced type annotations for action parameters to improve code readability and maintainability.

* refactor(converters): rename robot_transition_to_action to transition_to_robot_action

- Updated function names across multiple files to improve clarity and consistency in processing robot actions.
- Adjusted references in RobotProcessorPipeline and related components to align with the new naming convention.
- Simplified action handling in the AddBatchDimensionProcessorStep by removing unnecessary checks for action presence.

* refactor(converters): update references to transition_to_robot_action

- Renamed all instances of robot_transition_to_action to transition_to_robot_action across multiple files for consistency and clarity in the processing of robot actions.
- Adjusted the RobotProcessorPipeline configurations to reflect the new naming convention, enhancing code readability.

* refactor(processor): update Torch2NumpyActionProcessorStep to extend ActionProcessorStep

- Changed the base class of Torch2NumpyActionProcessorStep from PolicyActionProcessorStep to ActionProcessorStep, aligning it with the current architecture of action processing.
- This modification enhances the clarity of the class's role in the processing pipeline.

* fix(processor): main action processor can take also EnvAction

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Co-authored-by: Steven Palma <steven.palma@huggingface.co>
This commit is contained in:
Adil Zouitine
2025-09-10 22:40:37 +02:00
committed by GitHub
parent 6745958362
commit 9183083e75
22 changed files with 303 additions and 139 deletions
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tests/processor/test_sac_processor.py
+4 -4
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@@ -371,12 +371,12 @@ def test_sac_processor_edge_cases():
assert processed[TransitionKey.OBSERVATION] == {}
assert processed[TransitionKey.ACTION].shape == (1, 5)
# Test with None action
transition = create_transition(observation={OBS_STATE: torch.randn(10)}, action={})
# Test with zero action (representing "null" action)
transition = create_transition(observation={OBS_STATE: torch.randn(10)}, action=torch.zeros(5))
processed = preprocessor(transition)
assert processed[TransitionKey.OBSERVATION][OBS_STATE].shape == (1, 10)
# When action is None, it may still be present with None value
assert TransitionKey.ACTION not in processed or processed[TransitionKey.ACTION] is None
# Action should be present and batched, even if it's zeros
assert processed[TransitionKey.ACTION].shape == (1, 5)
@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")