2025-07-02 17:29:58 +02:00
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#!/usr/bin/env python
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# Copyright 2025 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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2025-07-04 13:07:58 +02:00
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2025-07-23 18:41:53 +02:00
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from .batch_processor import ToBatchProcessor
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2025-08-11 11:07:55 +02:00
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from .delta_action_processor import MapDeltaActionToRobotAction
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2025-07-04 13:07:58 +02:00
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from .device_processor import DeviceProcessor
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2025-08-11 11:07:55 +02:00
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from .hil_processor import (
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AddTeleopActionAsComplimentaryData,
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AddTeleopEventsAsInfo,
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GripperPenaltyProcessor,
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ImageCropResizeProcessor,
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InterventionActionProcessor,
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Numpy2TorchActionProcessor,
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RewardClassifierProcessor,
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TimeLimitProcessor,
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Torch2NumpyActionProcessor,
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)
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from .joint_observations_processor import JointVelocityProcessor, MotorCurrentProcessor
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2025-08-01 08:55:38 +02:00
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from .normalize_processor import NormalizerProcessor, UnnormalizerProcessor, hotswap_stats
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2025-08-06 14:00:13 +02:00
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from .observation_processor import VanillaObservationProcessor
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2025-07-04 11:07:18 +02:00
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from .pipeline import (
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ActionProcessor,
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DoneProcessor,
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EnvTransition,
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2025-07-06 21:29:51 +02:00
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IdentityProcessor,
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2025-07-04 11:07:18 +02:00
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InfoProcessor,
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ObservationProcessor,
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ProcessorStep,
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2025-07-06 21:29:51 +02:00
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ProcessorStepRegistry,
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2025-07-04 11:07:18 +02:00
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RewardProcessor,
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RobotProcessor,
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2025-07-21 14:54:31 +02:00
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TransitionKey,
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2025-07-04 11:07:18 +02:00
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TruncatedProcessor,
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2025-07-02 17:29:58 +02:00
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)
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2025-07-04 10:53:40 +02:00
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from .rename_processor import RenameProcessor
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feature(pipeline): port tokenizer pipeline for VLA (#1645)
* feat(tokenizer): Introduce TokenizerProcessor for text tokenization
- Added TokenizerProcessor class to handle tokenization of task strings using Hugging Face's AutoTokenizer.
- Supports both string and list inputs, with customizable parameters for task key, output key, and tokenization settings.
- Implemented comprehensive unit tests to validate functionality, including handling of various input scenarios and integration with RobotProcessor.
- Updated types.py to include LANGUAGE feature type and modified __init__.py to register the new processor.
* feat(language): Enhance language processing in TokenizerProcessor
- Added OBS_LANGUAGE constant to define the observation language key.
- Updated TokenizerProcessor to store tokenized task data in the observation dictionary, ensuring compatibility with the new language feature.
- Introduced Pi0NewLineProcessor to append newlines to tasks for proper tokenization.
- Modified tests to validate the integration of language tokens and attention masks in the observation structure.
* feat(tokenizer): Add padding configuration to TokenizerProcessor
- Introduced `padding_side` parameter to the TokenizerProcessor for customizable padding direction.
- Updated the `make_pi0_processor` function to include the new padding configuration.
- Enhanced unit tests to validate the functionality of the `padding_side` parameter in various scenarios.
* feat(processor): Add state management methods to Pi0NewLineProcessor
* feat(normalization): Track normalization and unnormalization info in complementary data
- Updated NormalizerProcessor and UnnormalizerProcessor to accept additional parameters for tracking normalization modes.
- Enhanced the __call__ methods to store normalization and unnormalization information in the complementary data of transitions.
- Added unit tests to verify the correct tracking of normalization info, including scenarios with missing stats and selective normalization keys.
* feat(factory): Add preprocessor and postprocessor overrides to ProcessorConfigKwargs
- Updated ProcessorConfigKwargs to include optional overrides for preprocessor and postprocessor configurations.
- Enhanced the make_processor function to utilize the new overrides, allowing for more flexible processor initialization.
* feat(processors): Integrate RenameProcessor into various processor configurations
- Added RenameProcessor to the input steps of multiple processor functions, including make_act_processor, make_diffusion_processor, make_pi0_processor, make_sac_processor, make_tdmpc_processor, make_vqbet_processor, and make_smolvla_processor.
- Consolidated normalization features from input and output into a single NormalizerProcessor for improved efficiency.
- Updated the input steps to ensure compatibility with the new RenameProcessor integration.
* feat(smolvla): Refactor language processing and introduce new line processor (#1658)
- Removed the prepare_language method and directly accessed language tokens and masks from the batch using the OBS_LANGUAGE constant.
- Added SmolVLANewLineProcessor to ensure tasks end with a newline, enhancing tokenization compatibility.
- Updated the make_smolvla_processor function to include the new line processor and tokenizer processor for improved input handling.
* feture(policies): add device processor (#1659)
* feat(processors): Integrate DeviceProcessor into multiple processor configurations
- Added DeviceProcessor to the input and output steps of various processor functions, including make_act_processor, make_diffusion_processor, make_pi0_processor, make_pi0fast_processor, make_sac_processor, make_tdmpc_processor, make_vqbet_processor, and make_smolvla_processor.
- Enhanced the DeviceProcessor class with state management methods and ensured compatibility with existing processor pipelines.
- Introduced unit tests for DeviceProcessor to validate functionality across different scenarios, including CPU and CUDA operations.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* refactor(pipeline): Remove to() method for device management
- Eliminated the to() method from RobotProcessor, which was responsible for moving tensor states to specified devices.
- Removed associated unit tests that validated the functionality of the to() method across various scenarios.
- Streamlined the pipeline code by focusing on other device management strategies.
* feat(processor): Enhance DeviceProcessor with float dtype conversion
- Added support for optional float dtype conversion in DeviceProcessor, allowing tensors to be converted to specified floating-point types while preserving non-float types.
- Implemented validation for float dtype input and updated the processor's configuration methods to include float dtype.
- Refactored tensor processing logic to streamline device movement and dtype conversion.
- Introduced comprehensive unit tests to validate the new float dtype functionality across various scenarios.
* feat(policies): Add new line processors and update module exports
* feat(processor): Enhance batch and device processors to handle index and task_index fields
- Added logic to ToBatchProcessor for unsqueezing 0D tensors for index and task_index fields, ensuring they are processed as 1D tensors.
- Updated DeviceProcessor to process index and task_index fields in complementary data, preserving their tensor types and ensuring non-tensor fields remain unchanged.
- Enhanced unit tests to validate the correct handling of index and task_index fields across various scenarios, including device compatibility and dtype preservation.
2025-08-05 10:53:08 +02:00
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from .tokenizer_processor import TokenizerProcessor
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2025-07-02 17:29:58 +02:00
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__all__ = [
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"ActionProcessor",
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"AddTeleopActionAsComplimentaryData",
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"AddTeleopEventsAsInfo",
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2025-07-04 13:07:58 +02:00
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"DeviceProcessor",
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2025-07-04 11:07:18 +02:00
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"DoneProcessor",
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2025-08-11 11:07:55 +02:00
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"MapDeltaActionToRobotAction",
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2025-07-02 17:29:58 +02:00
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"EnvTransition",
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2025-08-11 11:07:55 +02:00
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"GripperPenaltyProcessor",
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2025-07-06 21:29:51 +02:00
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"IdentityProcessor",
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2025-08-11 11:07:55 +02:00
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"ImageCropResizeProcessor",
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2025-07-04 11:07:18 +02:00
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"InfoProcessor",
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2025-08-11 11:07:55 +02:00
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"InterventionActionProcessor",
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"JointVelocityProcessor",
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"MapDeltaActionToRobotAction",
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"MotorCurrentProcessor",
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2025-07-04 12:09:40 +02:00
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"NormalizerProcessor",
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"UnnormalizerProcessor",
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2025-08-01 08:55:38 +02:00
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"hotswap_stats",
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2025-07-04 11:07:18 +02:00
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"ObservationProcessor",
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"ProcessorStep",
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2025-07-06 21:29:51 +02:00
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"ProcessorStepRegistry",
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2025-07-04 10:53:40 +02:00
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"RenameProcessor",
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2025-08-11 11:07:55 +02:00
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"RewardClassifierProcessor",
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2025-07-04 11:07:18 +02:00
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"RewardProcessor",
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"RobotProcessor",
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2025-07-23 18:41:53 +02:00
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"ToBatchProcessor",
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feature(pipeline): port tokenizer pipeline for VLA (#1645)
* feat(tokenizer): Introduce TokenizerProcessor for text tokenization
- Added TokenizerProcessor class to handle tokenization of task strings using Hugging Face's AutoTokenizer.
- Supports both string and list inputs, with customizable parameters for task key, output key, and tokenization settings.
- Implemented comprehensive unit tests to validate functionality, including handling of various input scenarios and integration with RobotProcessor.
- Updated types.py to include LANGUAGE feature type and modified __init__.py to register the new processor.
* feat(language): Enhance language processing in TokenizerProcessor
- Added OBS_LANGUAGE constant to define the observation language key.
- Updated TokenizerProcessor to store tokenized task data in the observation dictionary, ensuring compatibility with the new language feature.
- Introduced Pi0NewLineProcessor to append newlines to tasks for proper tokenization.
- Modified tests to validate the integration of language tokens and attention masks in the observation structure.
* feat(tokenizer): Add padding configuration to TokenizerProcessor
- Introduced `padding_side` parameter to the TokenizerProcessor for customizable padding direction.
- Updated the `make_pi0_processor` function to include the new padding configuration.
- Enhanced unit tests to validate the functionality of the `padding_side` parameter in various scenarios.
* feat(processor): Add state management methods to Pi0NewLineProcessor
* feat(normalization): Track normalization and unnormalization info in complementary data
- Updated NormalizerProcessor and UnnormalizerProcessor to accept additional parameters for tracking normalization modes.
- Enhanced the __call__ methods to store normalization and unnormalization information in the complementary data of transitions.
- Added unit tests to verify the correct tracking of normalization info, including scenarios with missing stats and selective normalization keys.
* feat(factory): Add preprocessor and postprocessor overrides to ProcessorConfigKwargs
- Updated ProcessorConfigKwargs to include optional overrides for preprocessor and postprocessor configurations.
- Enhanced the make_processor function to utilize the new overrides, allowing for more flexible processor initialization.
* feat(processors): Integrate RenameProcessor into various processor configurations
- Added RenameProcessor to the input steps of multiple processor functions, including make_act_processor, make_diffusion_processor, make_pi0_processor, make_sac_processor, make_tdmpc_processor, make_vqbet_processor, and make_smolvla_processor.
- Consolidated normalization features from input and output into a single NormalizerProcessor for improved efficiency.
- Updated the input steps to ensure compatibility with the new RenameProcessor integration.
* feat(smolvla): Refactor language processing and introduce new line processor (#1658)
- Removed the prepare_language method and directly accessed language tokens and masks from the batch using the OBS_LANGUAGE constant.
- Added SmolVLANewLineProcessor to ensure tasks end with a newline, enhancing tokenization compatibility.
- Updated the make_smolvla_processor function to include the new line processor and tokenizer processor for improved input handling.
* feture(policies): add device processor (#1659)
* feat(processors): Integrate DeviceProcessor into multiple processor configurations
- Added DeviceProcessor to the input and output steps of various processor functions, including make_act_processor, make_diffusion_processor, make_pi0_processor, make_pi0fast_processor, make_sac_processor, make_tdmpc_processor, make_vqbet_processor, and make_smolvla_processor.
- Enhanced the DeviceProcessor class with state management methods and ensured compatibility with existing processor pipelines.
- Introduced unit tests for DeviceProcessor to validate functionality across different scenarios, including CPU and CUDA operations.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* refactor(pipeline): Remove to() method for device management
- Eliminated the to() method from RobotProcessor, which was responsible for moving tensor states to specified devices.
- Removed associated unit tests that validated the functionality of the to() method across various scenarios.
- Streamlined the pipeline code by focusing on other device management strategies.
* feat(processor): Enhance DeviceProcessor with float dtype conversion
- Added support for optional float dtype conversion in DeviceProcessor, allowing tensors to be converted to specified floating-point types while preserving non-float types.
- Implemented validation for float dtype input and updated the processor's configuration methods to include float dtype.
- Refactored tensor processing logic to streamline device movement and dtype conversion.
- Introduced comprehensive unit tests to validate the new float dtype functionality across various scenarios.
* feat(policies): Add new line processors and update module exports
* feat(processor): Enhance batch and device processors to handle index and task_index fields
- Added logic to ToBatchProcessor for unsqueezing 0D tensors for index and task_index fields, ensuring they are processed as 1D tensors.
- Updated DeviceProcessor to process index and task_index fields in complementary data, preserving their tensor types and ensuring non-tensor fields remain unchanged.
- Enhanced unit tests to validate the correct handling of index and task_index fields across various scenarios, including device compatibility and dtype preservation.
2025-08-05 10:53:08 +02:00
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"TokenizerProcessor",
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2025-08-11 11:07:55 +02:00
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"TimeLimitProcessor",
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"Numpy2TorchActionProcessor",
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"Torch2NumpyActionProcessor",
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2025-07-21 14:54:31 +02:00
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"TransitionKey",
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2025-07-04 11:07:18 +02:00
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"TruncatedProcessor",
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"VanillaObservationProcessor",
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2025-07-02 17:29:58 +02:00
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]
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