* add initial modeling * make rewind pretrained policy * add annotation * small fix * add sarm * subtasks * fix spawn * fix rewind discrepancies * Add script to generate embedding for dataset (#2138) * Add generate and validate script * fix precommit * Improve generate embeddings function by using dataset tools (#2206) --------- Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co> * cleanup * change order train log * print batch size * update sarm processor * add reward output * change expected features * add image validation * change validation * get state input from dataset stats * raise if no state key is found * pass stats * cleanup and refactor * add episode inddex to complementary data * add subtask init and detection * revert lerobot_train changes * pass dataset metadata to policy * change loadig subtasks * add small logging * fix progress conversion and adding initial frame * use large offset for initial frame (ugly) * Remove rewind, use clip tokenizer * add tests, implement formula 1,2 correctly and cleanup * use task from dataset, cleanup visualizer * simplify * simplify and cleanup code and move compute_temporal_proportions to utils * fix normalization in visualization * Fix visualization and change prompt * fix formatting * add visualize subtask annotations * use qwen thinking * try different prompt * format * update prompt * higher temp, long output * different settings * use instruct * show full resp * split message * Temp: increase tolerance dataset * Fix RA-BC (#2572) * Add next observation loading for RA-BC progress deltas * Compute weights based on temporal progress deltas instead of static rewards * Add hard-masking for negative progress deltas in weight computation * Feat/add dual head (#2582) * Add dual dense sparse head and annotation * Add docs * add dual to procesor * cleanup * change sampling in visualize and cleanup * remove validation * remove compile * Feat/test uniform (#2587) * test uniform * add different string for misaligned * Fix rewind and add tests * uncomment text implementation * run precommit * Add head mode for ra-bc * fix visalization of single task * add * return per sample loss * Fix RA_BC (#2602) * update rabc implementation * compute rabc beforehand * fix import * add only progress calulation * use precomputed progress * multi gpu processing * import * fix dataset meta data extraction * add logging * logging * log * progress per episode * split differently * move clip to gpu * pre decode frames for an episode * fix cuda initalization * fix import * multi processing * rename * fix import * fix * fix rabc * use last known progress if oob * use last known progress if oob * add misalignment loss with random embeddings * discard previous changes * add selection of models to docs for ra_bc * add transformers dep * extend tolerance * initial commit with new codebase * add tests * fix * remove temporal sampler * drop last frame for sampler * use original ref * some fixes * fix visualization * remove smoothing and fix order subtasks * add stride rabc computation * add push to hub * add explanation * add kappa expllaination * better rabc logging * feedback pr * remove dataset tolerance * revert dataset tool * revert dataset changes * add credit * run precommit * change path for generate ra_bc * fix type * include sarm in all in pyproject * fix precommit * lazy import matplotlib * lazy import qwen * remove rich console * skip if transformers is not installed? * run only when we have faker * place transformer lazy loading * Dont test if low transformer version * fix * increase transformer * increase as 4.57.0 is yanked * remove pi from all * go back --------- Co-authored-by: Michel Aractingi <michel.aractingi@huggingface.co> Co-authored-by: s1lent4gnt <kmeftah.khalil@gmail.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.