mirror of
https://github.com/huggingface/lerobot.git
synced 2026-07-25 02:36:11 +00:00
Maxime Ellerbach
103 lines
3.9 KiB
Python
103 lines
3.9 KiB
Python
# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Pre/post-processor pipelines for the LingBot-VA policy.
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The preprocessor passes inputs through (IDENTITY) and the postprocessor maps the policy's
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``[-1, 1]`` actions back to physical units with the built-in ``UnnormalizerProcessorStep``
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(QUANTILES) using per-channel q01/q99 restored from the checkpoint.
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"""
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from typing import Any
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import torch
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from lerobot.configs.types import FeatureType, NormalizationMode
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from lerobot.processor import (
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AbsoluteActionsProcessorStep,
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AddBatchDimensionProcessorStep,
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DeviceProcessorStep,
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NormalizerProcessorStep,
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PolicyAction,
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PolicyProcessorPipeline,
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ProcessorStep,
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RelativeActionsProcessorStep,
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RenameObservationsProcessorStep,
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UnnormalizerProcessorStep,
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)
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from lerobot.processor.converters import policy_action_to_transition, transition_to_policy_action
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from lerobot.utils.constants import (
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POLICY_POSTPROCESSOR_DEFAULT_NAME,
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POLICY_PREPROCESSOR_DEFAULT_NAME,
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)
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from .configuration_lingbot_va import LingBotVAConfig
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def make_lingbot_va_pre_post_processors(
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config: LingBotVAConfig,
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dataset_stats: dict[str, dict[str, torch.Tensor]] | None = None,
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) -> tuple[
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PolicyProcessorPipeline[dict[str, Any], dict[str, Any]],
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PolicyProcessorPipeline[PolicyAction, PolicyAction],
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]:
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"""Build the pre/post processor pipelines for LingBot-VA."""
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# Shared relative-action step (OpenPI order: raw -> relative -> normalize -> model ->
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# unnormalize -> absolute). The SAME instance is passed to AbsoluteActionsProcessorStep
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# below so its cached raw state (set during preprocessing) flows to postprocessing.
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relative_step = RelativeActionsProcessorStep(
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enabled=config.use_relative_actions,
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exclude_joints=getattr(config, "relative_exclude_joints", []),
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action_names=getattr(config, "action_feature_names", None),
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)
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input_steps: list[ProcessorStep] = [
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RenameObservationsProcessorStep(rename_map={}),
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AddBatchDimensionProcessorStep(),
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relative_step,
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NormalizerProcessorStep(
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features={**config.input_features, **config.output_features},
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norm_map=config.normalization_mapping,
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stats=dataset_stats,
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),
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DeviceProcessorStep(device=config.device),
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]
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# Unnormalize actions back to physical units. Config-driven norm_map (was hardcoded QUANTILES)
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# so it stays symmetric with the preprocessor's NormalizerProcessorStep — required for
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# use_relative_actions with ACTION=IDENTITY (and unchanged for QUANTILES runs).
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output_steps: list[ProcessorStep] = [
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UnnormalizerProcessorStep(
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features=config.output_features,
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norm_map=config.normalization_mapping,
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stats=dataset_stats,
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),
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AbsoluteActionsProcessorStep(enabled=config.use_relative_actions, relative_step=relative_step),
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DeviceProcessorStep(device="cpu"),
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]
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return (
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PolicyProcessorPipeline[dict[str, Any], dict[str, Any]](
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steps=input_steps,
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name=POLICY_PREPROCESSOR_DEFAULT_NAME,
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),
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PolicyProcessorPipeline[PolicyAction, PolicyAction](
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steps=output_steps,
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name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
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to_transition=policy_action_to_transition,
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to_output=transition_to_policy_action,
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),
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)
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