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| from copy import deepcopy
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| from dataclasses import dataclass, field
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| from typing import Any
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| from lerobot.configs.types import PipelineFeatureType, PolicyFeature
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| from .pipeline import ObservationProcessorStep, ProcessorStepRegistry
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| @dataclass
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| @ProcessorStepRegistry.register(name="rename_observations_processor")
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| class RenameObservationsProcessorStep(ObservationProcessorStep):
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| """
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| A processor step that renames keys in an observation dictionary.
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| This step is useful for creating a standardized data interface by mapping keys
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| from an environment's format to the format expected by a LeRobot policy or
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| other downstream components.
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| Attributes:
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| rename_map: A dictionary mapping from old key names to new key names.
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| Keys present in an observation that are not in this map will
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| be kept with their original names.
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| """
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| rename_map: dict[str, str] = field(default_factory=dict)
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| def observation(self, observation):
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| processed_obs = {}
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| for key, value in observation.items():
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| if key in self.rename_map:
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| processed_obs[self.rename_map[key]] = value
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| else:
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| processed_obs[key] = value
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| return processed_obs
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| def get_config(self) -> dict[str, Any]:
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| return {"rename_map": self.rename_map}
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| def transform_features(
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| self, features: dict[PipelineFeatureType, dict[str, PolicyFeature]]
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| ) -> dict[PipelineFeatureType, dict[str, PolicyFeature]]:
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| """Transforms:
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| - Each key in the observation that appears in `rename_map` is renamed to its value.
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| - Keys not in `rename_map` remain unchanged.
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| """
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| new_features: dict[PipelineFeatureType, dict[str, PolicyFeature]] = features.copy()
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| new_features[PipelineFeatureType.OBSERVATION] = {
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| self.rename_map.get(k, k): v for k, v in features[PipelineFeatureType.OBSERVATION].items()
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| }
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| return new_features
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| def rename_stats(stats: dict[str, dict[str, Any]], rename_map: dict[str, str]) -> dict[str, dict[str, Any]]:
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| """
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| Renames the top-level keys in a statistics dictionary using a provided mapping.
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| This is a helper function typically used to keep normalization statistics
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| consistent with renamed observation or action features. It performs a defensive
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| deep copy to avoid modifying the original `stats` dictionary.
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| Args:
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| stats: A nested dictionary of statistics, where top-level keys are
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| feature names (e.g., `{"observation.state": {"mean": 0.5}}`).
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| rename_map: A dictionary mapping old feature names to new feature names.
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| Returns:
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| A new statistics dictionary with its top-level keys renamed. Returns an
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| empty dictionary if the input `stats` is empty.
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| """
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| if not stats:
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| return {}
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| renamed: dict[str, dict[str, Any]] = {}
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| for old_key, sub_stats in stats.items():
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| new_key = rename_map.get(old_key, old_key)
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| renamed[new_key] = deepcopy(sub_stats) if sub_stats is not None else {}
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| return renamed
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|
