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chore(processor): add Step suffix to all processors (#1854)

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* refactor(processor): rename MapDeltaActionToRobotAction and MapTensorToDeltaActionDict for consistency

* refactor(processor): rename DeviceProcessor to DeviceProcessorStep for consistency across modules

* refactor(processor): rename Torch2NumpyActionProcessor to Torch2NumpyActionProcessorStep for consistency

* refactor(processor): rename Numpy2TorchActionProcessor to Numpy2TorchActionProcessorStep for consistency

* refactor(processor): rename AddTeleopActionAsComplimentaryData to AddTeleopActionAsComplimentaryDataStep for consistency

* refactor(processor): rename ImageCropResizeProcessor and AddTeleopEventsAsInfo for consistency

* refactor(processor): rename TimeLimitProcessor to TimeLimitProcessorStep for consistency

* refactor(processor): rename GripperPenaltyProcessor to GripperPenaltyProcessorStep for consistency

* refactor(processor): rename InterventionActionProcessor to InterventionActionProcessorStep for consistency

* refactor(processor): rename RewardClassifierProcessor to RewardClassifierProcessorStep for consistency

* refactor(processor): rename JointVelocityProcessor to JointVelocityProcessorStep for consistency

* refactor(processor): rename MotorCurrentProcessor to MotorCurrentProcessorStep for consistency

* refactor(processor): rename NormalizerProcessor and UnnormalizerProcessor to NormalizerProcessorStep and UnnormalizerProcessorStep for consistency

* refactor(processor): rename VanillaObservationProcessor to VanillaObservationProcessorStep for consistency

* refactor(processor): rename RenameProcessor to RenameProcessorStep for consistency

* refactor(processor): rename TokenizerProcessor to TokenizerProcessorStep for consistency

* refactor(processor): rename ToBatchProcessor to AddBatchDimensionProcessorStep for consistency

* refactor(processor): update config file name in test for RenameProcessorStep consistency
This commit is contained in:
Adil Zouitine
2025-09-03 18:12:11 +02:00
committed by GitHub
parent 029c4a9a76
commit ce793cde64
37 changed files with 653 additions and 628 deletions
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24
src/lerobot/processor/migrate_policy_normalization.py
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@@ -47,11 +47,11 @@ from safetensors.torch import load_file as load_safetensors
from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
from .batch_processor import ToBatchProcessor
from .device_processor import DeviceProcessor
from .normalize_processor import NormalizerProcessor, UnnormalizerProcessor
from .batch_processor import AddBatchDimensionProcessorStep
from .device_processor import DeviceProcessorStep
from .normalize_processor import NormalizerProcessorStep, UnnormalizerProcessorStep
from .pipeline import DataProcessorPipeline
from .rename_processor import RenameProcessor
from .rename_processor import RenameProcessorStep
# Policy type to class mapping
POLICY_CLASSES = {
@@ -404,8 +404,8 @@ def main():
# Now create preprocessor and postprocessor with cleaned_config available
print("Creating preprocessor and postprocessor...")
# The pattern from existing processor factories:
# - Preprocessor has two NormalizerProcessors: one for input_features, one for output_features
# - Postprocessor has one UnnormalizerProcessor for output_features only
# - Preprocessor has two NormalizerProcessorSteps: one for input_features, one for output_features
# - Postprocessor has one UnnormalizerProcessorStep for output_features only
# Get features from cleaned_config (now they're PolicyFeature objects)
input_features = cleaned_config.get("input_features", {})
@@ -413,21 +413,21 @@ def main():
# Create preprocessor with two normalizers (following the pattern from processor factories)
preprocessor_steps = [
RenameProcessor(rename_map={}),
NormalizerProcessor(
RenameProcessorStep(rename_map={}),
NormalizerProcessorStep(
features={**input_features, **output_features},
norm_map=norm_map,
stats=stats,
),
ToBatchProcessor(),
DeviceProcessor(device=policy_config.device),
AddBatchDimensionProcessorStep(),
DeviceProcessorStep(device=policy_config.device),
]
preprocessor = DataProcessorPipeline(steps=preprocessor_steps, name="robot_preprocessor")
# Create postprocessor with unnormalizer for outputs only
postprocessor_steps = [
DeviceProcessor(device="cpu"),
UnnormalizerProcessor(features=output_features, norm_map=norm_map, stats=stats),
DeviceProcessorStep(device="cpu"),
UnnormalizerProcessorStep(features=output_features, norm_map=norm_map, stats=stats),
]
postprocessor = DataProcessorPipeline(steps=postprocessor_steps, name="robot_postprocessor")