- Added the ability to provide non-serializable objects when loading processors from saved configurations using the `overrides` parameter.
- Enhanced error handling for invalid override keys and instantiation errors.
- Updated documentation and examples to illustrate the usage of overrides for both registered and unregistered steps.
- Added comprehensive tests to validate the new functionality and ensure backward compatibility.
- Renamed `ObservationNormalizer` to `NormalizerProcessor` and `ActionUnnormalizer` to `UnnormalizerProcessor` for clarity.
- Consolidated normalization logic for both observations and actions into `NormalizerProcessor` and `UnnormalizerProcessor`.
- Updated tests to reflect the new class names and ensure proper functionality of normalization and unnormalization processes.
- Enhanced handling of missing statistics in normalization processes.
- Added `RenameProcessor` to facilitate key renaming in observations, improving data handling flexibility.
- Updated `__init__.py` to include `RenameProcessor` in module exports.
- Refactored `NormalizationProcessor` and `ObservationNormalizer` to use `rsplit` for better key handling.
- Introduced comprehensive tests for `NormalizationProcessor` and `RenameProcessor` to ensure functionality and robustness.
- Introduced `NormalizationProcessor` to handle both observation normalization and action unnormalization.
- Added `ObservationNormalizer` and `ActionUnnormalizer` classes for specific normalization tasks.
- Updated `__init__.py` to include the new `NormalizationProcessor` in the module exports.
- Enhanced `ObservationProcessor` with registration in the `ProcessorStepRegistry` for better modularity.
- Created `RenameProcessor` for renaming keys in observations, improving flexibility in data processing.
- Introduced a new tutorial on using RobotProcessor for preprocessing robot data.
- Added a section in the table of contents for easy navigation to the new tutorial.
- The tutorial covers key concepts, real-world scenarios, and practical examples for effective use of the RobotProcessor pipeline.
- Replaced instances of RobotPipeline with RobotProcessor across the codebase for improved modularity and clarity.
- Introduced ProcessorStepRegistry for better management of processing steps.
- Updated relevant documentation and tests to reflect the new processing structure.
- Enhanced the save/load functionality to support the new processor design.
- Added a model card template for RobotProcessor to facilitate sharing and documentation.
- Updated `ObservationProcessor` to enhance the modular design for processing observations.
- Cleaned up imports and improved code readability by removing unnecessary lines and comments.
- Ensured backward compatibility while integrating new processing components.
- Added tests to validate the functionality of the updated processing architecture.
- Introduced `RobotPipeline` and `ObservationProcessor` for handling observation transformations.
- Updated `preprocess_observation` to maintain backward compatibility while leveraging the new pipeline.
- Added tests for the new processing components and ensured they match the original functionality.
- Removed hardcoded logic in favor of a more flexible, composable architecture.
* fix(policies): remove action from batch for offline evaluation in diffusion, tdmpc, and vqbet policies
* style(diffusion): correct comment capitalization for clarity in modeling_diffusion.py
Prevent VAE inference when running in offline mode. In the lerobot dataset, the presence of the 'action' field incorrectly triggers the VAE inference block. This leads to a RuntimeError due to mismatched tensor dimensions (3 vs 2) when concatenating cls_embed, robot_state_embed, and action_embed—since action_embed lacks the chunk_size dimension. Additionally, this aligns with the original paper, where variational inference is skipped during inference.
* Merge together proto files and refactor Async inference
* Fixup for Async inference
* Drop not reuqired changes
* Fix tests
* Drop old async files
* Drop chunk_size param
* Fix versions
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix wrong fix
Co-authored-by: Ben Zhang <ben.zhang@uwaterloo.ca>
* Fixup
---------
Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co>
Co-authored-by: Ben Zhang <ben.zhang@uwaterloo.ca>
Co-authored-by: Francesco Capuano <74058581+fracapuano@users.noreply.github.com>
Adil Zouitine