- Updated state filename generation to use the registry name when available, improving clarity in saved files.
- Modified the profile_steps method to include a warmup_runs parameter, allowing for more controlled performance profiling.
- Ensured consistent conditions during profiling by deep copying transitions for each run, enhancing accuracy in timing results.
- Replaced direct torch.device instantiation with get_safe_torch_device to ensure safe device handling.
- This change enhances code readability and maintains consistency in device management across the RobotProcessor class.
- Implemented a __repr__ method in the RobotProcessor class to provide a clear string representation of the processor, including step names and optional parameters like name and seed.
- Added comprehensive tests to validate the __repr__ output for various scenarios, including empty processors, single and multiple steps, custom names, and seed values.
- Ensured that the representation handles long lists of steps with truncation for better readability.
- Updated the RobotProcessor class to ensure hooks are strictly for observation and do not modify transitions, enhancing clarity and maintainability.
- Refactored hook registration methods to reflect the new behavior, ensuring they accept only functions that do not return modified transitions.
- Enhanced documentation to clearly outline the purpose of hooks and their execution semantics.
- Added tests to verify that hooks are not executed during the step_through method while ensuring they function correctly during the __call__ method.
- Implemented methods to unregister before, after, and reset hooks in the RobotProcessor class, allowing for more flexible hook management.
- Enhanced documentation to clarify hook execution semantics and the implications of modifying transitions within hooks.
- Added comprehensive tests to verify the correct behavior of hook registration and unregistration, including error handling for non-existent hooks.
- Introduced constants for observation keys to enhance readability.
- Streamlined the handling of the "pixels" key by copying observations first and processing images more clearly.
- Updated the environment state and agent position assignments to use the new constants, improving maintainability.
- Updated the EnvTransition structure to use a dictionary format instead of a tuple, enhancing readability and maintainability.
- Replaced instances of TransitionIndex with TransitionKey for accessing transition components.
- Adjusted related processing functions and tests to accommodate the new dictionary format, ensuring consistent handling of transitions across the codebase.
- 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.
- 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.
- 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
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* 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>
* fix(ci): tag of image when pushing to main
* fix(docs): remove symlink in docs folder
* chore(docs): move .mdx files to docs/ folder
* chore(docs): create symlink to docs files
* chore(ci): de-couple fast and full test pipeline
* fix(ci): skip GPU Tests for community PRs
* Update so101.mdx
Signed-off-by: Jakob Frick <jakob.maria.frick@gmail.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Update so101.mdx
Signed-off-by: Jakob Frick <jakob.maria.frick@gmail.com>
---------
Signed-off-by: Jakob Frick <jakob.maria.frick@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
