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97 lines
3.6 KiB
Python
97 lines
3.6 KiB
Python
#!/usr/bin/env python
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# Copyright 2024 Tony Z. Zhao and 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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from typing import Any
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import torch
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from lerobot.datasets.utils import DEFAULT_AUDIO_CHUNK_DURATION
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from lerobot.policies.act.configuration_act import ACTConfig
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from lerobot.processor import (
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AddBatchDimensionProcessorStep,
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AudioProcessorStep,
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DeviceProcessorStep,
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NormalizerProcessorStep,
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PolicyAction,
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PolicyProcessorPipeline,
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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 POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
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def make_act_pre_post_processors(
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config: ACTConfig,
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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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"""Creates the pre- and post-processing pipelines for the ACT policy.
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The pre-processing pipeline handles normalization, batching, and device placement for the model inputs.
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The post-processing pipeline handles unnormalization and moves the model outputs back to the CPU.
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Args:
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config (ACTConfig): The ACT policy configuration object.
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dataset_stats (dict[str, dict[str, torch.Tensor]] | None): A dictionary containing dataset
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statistics (e.g., mean and std) used for normalization. Defaults to None.
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Returns:
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tuple[PolicyProcessorPipeline[dict[str, Any], dict[str, Any]], PolicyProcessorPipeline[PolicyAction, PolicyAction]]: A tuple containing the
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pre-processor pipeline and the post-processor pipeline.
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"""
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input_steps = [
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RenameObservationsProcessorStep(rename_map={}),
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AddBatchDimensionProcessorStep(),
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DeviceProcessorStep(device=config.device),
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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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device=config.device,
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),
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AudioProcessorStep(
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output_height=224,
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output_width=224,
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output_channels=3,
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input_audio_chunk_duration=DEFAULT_AUDIO_CHUNK_DURATION,
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input_sample_rate=48000,
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intermediate_sample_rate=16000,
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n_fft=1024,
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),
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]
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output_steps = [
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UnnormalizerProcessorStep(
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features=config.output_features, norm_map=config.normalization_mapping, stats=dataset_stats
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),
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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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