Michel Aractingi
0053defa2e
* Migrate gym_manipulator to use the pipeline Added get_teleop_events function to capture relevant events from teleop devices unrelated to actions * Added the capability to record a dataset * Added the replay functionality with the pipeline * Refactored `actor.py` to use the pipeline * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * RL works at this commit - fixed actor.py and bugs in gym_manipulator * change folder structure to reduce the size of gym_manip * Refactored hilserl config * Remove dataset and mode from HilSerlEnvConfig to a GymManipulatorConfig to reduce verbose of configs during training * format docs * removed get_teleop_events from abc * Refactor environment configuration and processing pipeline for GymHIL support. Removed device attribute from HILSerlRobotEnvConfig, added DummyTeleopDevice for simulation, and updated processor creation to accommodate GymHIL environments. * Improved typing for HILRobotEnv config and GymManipulator config * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Migrated `gym_manipulator` to use a more modular structure similar to phone teleop * Refactor gripper handling and transition processing in HIL and robot kinematic processors - Updated gripper position handling to use a consistent key format across processors - Improved the EEReferenceAndDelta class to handle reference joint positions. - Added support for discrete gripper actions in the GripperVelocityToJoint processor. - Refactored the gym manipulator to improve modularity and clarity in processing steps. * Added delta_action_processor mapping wrapper * Added missing file delta_action_processor and improved imports in `gym_manipulator` * nit * Added missing file joint_observation_processor * Enhance processing architecture with new teleoperation processors - Introduced `AddTeleopActionAsComplimentaryData` and `AddTeleopEventsAsInfo` for integrating teleoperator actions and events into transitions. - Added `Torch2NumpyActionProcessor` and `Numpy2TorchActionProcessor` for seamless conversion between PyTorch tensors and NumPy arrays. - Updated `__init__.py` to include new processors in module exports, improving modularity and clarity in the processing pipeline. - GymHIL is now fully supported with HIL using the pipeline * Refactor configuration structure for gym_hil integration - Renamed sections for better readability, such as changing "Gym Wrappers Configuration" to "Processor Configuration." - Enhanced documentation with clear examples for dataset collection and policy evaluation configurations. * Enhance reset configuration and teleoperation event handling - Added `terminate_on_success` parameter to `ResetConfig` and `InterventionActionProcessor` for controlling episode termination behavior upon success detection. - Updated documentation to clarify the impact of `terminate_on_success` on data collection for reward classifier training. - Refactored teleoperation event handling to use `TeleopEvents` constants for improved readability and maintainability across various modules. * fix(keyboard teleop), delta action keys * Added transform features and feature contract * Added transform features for image crop * Enum for TeleopEvents * Update tranform_features delta action proc --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Generating the documentation
To generate the documentation, you first have to build it. Several packages are necessary to build the doc, you can install them with the following command, at the root of the code repository:
pip install -e . -r docs-requirements.txt
You will also need nodejs. Please refer to their installation page
NOTE
You only need to generate the documentation to inspect it locally (if you're planning changes and want to
check how they look before committing for instance). You don't have to git commit the built documentation.
Building the documentation
Once you have setup the doc-builder and additional packages, you can generate the documentation by
typing the following command:
doc-builder build lerobot docs/source/ --build_dir ~/tmp/test-build
You can adapt the --build_dir to set any temporary folder that you prefer. This command will create it and generate
the MDX files that will be rendered as the documentation on the main website. You can inspect them in your favorite
Markdown editor.
Previewing the documentation
To preview the docs, first install the watchdog module with:
pip install watchdog
Then run the following command:
doc-builder preview lerobot docs/source/
The docs will be viewable at http://localhost:3000. You can also preview the docs once you have opened a PR. You will see a bot add a comment to a link where the documentation with your changes lives.
NOTE
The preview command only works with existing doc files. When you add a completely new file, you need to update _toctree.yml & restart preview command (ctrl-c to stop it & call doc-builder preview ... again).
Adding a new element to the navigation bar
Accepted files are Markdown (.md).
Create a file with its extension and put it in the source directory. You can then link it to the toc-tree by putting
the filename without the extension in the _toctree.yml file.
Renaming section headers and moving sections
It helps to keep the old links working when renaming the section header and/or moving sections from one document to another. This is because the old links are likely to be used in Issues, Forums, and Social media and it'd make for a much more superior user experience if users reading those months later could still easily navigate to the originally intended information.
Therefore, we simply keep a little map of moved sections at the end of the document where the original section was. The key is to preserve the original anchor.
So if you renamed a section from: "Section A" to "Section B", then you can add at the end of the file:
Sections that were moved:
[ <a href="#section-b">Section A</a><a id="section-a"></a> ]
and of course, if you moved it to another file, then:
Sections that were moved:
[ <a href="../new-file#section-b">Section A</a><a id="section-a"></a> ]
Use the relative style to link to the new file so that the versioned docs continue to work.
For an example of a rich moved sections set please see the very end of the transformers Trainer doc.
Adding a new tutorial
Adding a new tutorial or section is done in two steps:
- Add a new file under
./source. This file can either be ReStructuredText (.rst) or Markdown (.md). - Link that file in
./source/_toctree.ymlon the correct toc-tree.
Make sure to put your new file under the proper section. If you have a doubt, feel free to ask in a Github Issue or PR.
Writing source documentation
Values that should be put in code should either be surrounded by backticks: `like so`. Note that argument names
and objects like True, None or any strings should usually be put in code.
Writing a multi-line code block
Multi-line code blocks can be useful for displaying examples. They are done between two lines of three backticks as usual in Markdown:
```
# first line of code
# second line
# etc
```
Adding an image
Due to the rapidly growing repository, it is important to make sure that no files that would significantly weigh down the repository are added. This includes images, videos, and other non-text files. We prefer to leverage a hf.co hosted dataset like
the ones hosted on hf-internal-testing in which to place these files and reference
them by URL. We recommend putting them in the following dataset: huggingface/documentation-images.
If an external contribution, feel free to add the images to your PR and ask a Hugging Face member to migrate your images
to this dataset.