Files
lerobot-clone/docs
Pepijn a07f22e22c feat(envs): add LIBERO-plus robustness benchmark (#3313)
* feat(envs): add LIBERO-plus robustness benchmark integration

- LiberoPlusEnv config (subclass of LiberoEnv, same gym interface)
- Docker image installing LIBERO-plus fork via PYTHONPATH
- CI workflow: 1-episode smoke eval with pepijn223/smolvla_libero_plus
- pyproject.toml: libero_plus extra

* fix(libero): use suite's perturbation-aware init_states loader

LIBERO-plus's Benchmark class exposes a `get_task_init_states(i)` method that
strips perturbation suffixes (`_table_N`, `_tb_N`, `_view_`, `_language_`,
`_light_`, `_add_`, `_level`) and loads the underlying base `.pruned_init`
file — the on-disk name for a perturbation variant doesn't exist as a file,
only the base does. lerobot's loader was bypassing that logic and trying to
read the suffix-bearing filename directly, which failed for every non-zero
task id and killed the eval before any rollout video could be written.

Delegate to the suite's method when it exists; fall back to the path-based
loader for vanilla LIBERO (which does not provide the method).

Also drop the hf-libero install + init_files copy from the LIBERO-plus
Dockerfile — the LIBERO-plus clone already ships both `bddl_files/` and
`init_files/` for all five suites, so the copy was unnecessary and the
`cp -r` into an existing dir produced a confusing nested layout.

* fix(libero): resolve LIBERO-plus perturbation init_states path ourselves

Delegating to `task_suite.get_task_init_states(i)` works for path resolution
but LIBERO-plus's method calls `torch.load(path)` without `weights_only=False`,
which fails on PyTorch 2.6+ because the pickled init_states contains numpy
objects not in the default allowlist:

    _pickle.UnpicklingError: Weights only load failed.
    WeightsUnpickler error: Unsupported global:
      GLOBAL numpy.core.multiarray._reconstruct was not an allowed global.

Mirror LIBERO-plus's suffix-stripping logic (`_table_N`, `_tb_N`, `_view_`,
`_language_`, `_light_`, `_add_`, `_level`) in our own helper so we can pass
`weights_only=False` ourselves. Vanilla LIBERO task names don't contain any
of these patterns except for `_table_` when followed by the word `center`
(e.g. `pick_up_the_black_bowl_from_table_center_...`), and the regex
requires `_table_\\d+` so semantic uses are preserved.

* fix(libero-plus): download perturbation assets from Sylvest/LIBERO-plus

LIBERO-plus's bddl_base_domain.py resolves scene XMLs with
`os.path.join(DIR_PATH, "../assets")`, so the `assets` key in config.yaml
has no effect on scene lookup — MuJoCo always opens
`<clone>/libero/libero/assets/scenes/...`. With no such directory present,
every perturbation task fails on:

    FileNotFoundError: No such file or directory:
      .../libero-plus/libero/libero/assets/scenes/tabletop_table_Cobblestone01_GLOSS_6K.xml

These textures, views, and extra objects ship only in the 6.4 GB `assets.zip`
published at `Sylvest/LIBERO-plus` (the LIBERO-plus README explicitly says
to download and unzip it into the package dir). Fetch it via `hf_hub_download`,
unzip into `${LIBERO_PLUS_ROOT}/`, install `unzip`, and point config.yaml at
the extracted dir so everything stays consistent. The download lives in its
own Docker layer so subsequent rebuilds reuse the cached assets.

Drops the lerobot/libero-assets snapshot_download — that mirror only has
vanilla LIBERO textures and is ignored for scene loading anyway.

* fix(libero-plus): flatten deep path prefix from Sylvest/LIBERO-plus assets.zip

The 6.4 GB zip ships with every entry prefixed by
`inspire/hdd/project/embodied-multimodality/public/syfei/libero_new/release/dataset/LIBERO-plus-0/assets/...`
(the author's internal filesystem layout, not the layout the LIBERO-plus
README promises), so the previous `unzip -d ${LIBERO_PLUS_ROOT}/` created
`${LIBERO_PLUS_ROOT}/inspire/.../assets/` — robosuite still opened
`${LIBERO_PLUS_ROOT}/assets/scenes/tabletop_table_Cobblestone01_GLOSS_6K.xml`
and hit the same FileNotFoundError.

Extract to a scratch dir, then `mv` the nested `assets/` subtree to the
expected location. Verified the target file exists in the zip central
directory under that exact prefix.

* refactor(libero): inline init_states resolver behind single regex

Collapse the three-style suffix stripper (split/re.sub/in) into one
compiled regex, drop the (Path, bool) tuple return, and move the
`_add_`/`_level` reshape branch into the caller so each branch loads
its own file and returns directly. Net: -11 lines, one fewer helper.

* refactor(libero-plus): rebase docker image on huggingface/lerobot-gpu

Mirror the libero/metaworld/robomme pattern: start from the nightly GPU
image (apt deps, python, uv, venv, lerobot[all] already there) and only
layer on what LIBERO-plus uniquely needs — its wand/ImageMagick build
deps, the non-extra runtime pips (robosuite==1.4.1, bddl, …), the
PYTHONPATH-shadowed fork, and the 6.4 GB assets.zip.

Drops ~50 lines of duplicated base setup (CUDA FROM, apt python, uv
install, user creation, venv init) the nightly already provides.
123 → 73 lines.

Also:
- Add libero_plus to docs/source/_toctree.yml under Benchmarks so
  doc-builder's TOC integrity check stops failing.
- Repoint the docs dataset link from pepijn223/libero_plus_lerobot to
  the canonical lerobot/libero_plus.
- Revert the stray uv.lock churn (revision/marker diff that crept in
  from an unrelated resolve — unrelated to LIBERO-plus).

* fix(libero-plus): stop touching pyproject + uv.lock

The fast-tests job was rejecting the branch because pyproject.toml had a
[libero_plus] extra whose git dep wasn't represented in uv.lock.

The Docker image no longer needs the extra — it clones LIBERO-plus
directly and PYTHONPATH-shadows hf-libero. Drop [libero_plus] from
pyproject and restore pyproject.toml + uv.lock to exactly what's on
origin/main, so `uv sync --locked --extra test` is a no-op for this PR.

Also repoint the doc/CI/env comments that still mentioned the extra at
the Docker install path.

* fix(libero-plus): strip perturbation metadata from task descriptions

LIBERO-plus builds task.language by space-joining the perturbation-variant
filename, so every non-_language_ variant inherits a trailing blob like
"view 0 0 100 0 0 initstate 0 noise 45" or "add 16". That shows up in the
dashboard video labels and no longer matches the base instruction stored
in the training dataset.

Strip those tokens in extract_task_descriptions.py with an end-anchored
regex over the {view,initstate,noise,add,tb,table,light,level}(+digits)
vocabulary. The anchor preserves mid-sentence literal uses of those words
(e.g. "from table center and place it on the plate") — only the trailing
metadata chain is removed. _language_ variants carry real BDDL-sourced
text and are left untouched.

* ci: point benchmark eval checkpoints at the lerobot/ org mirrors

pepijn223/smolvla_* → lerobot/smolvla_* across every benchmark job in
this branch (libero, metaworld, and the per-branch benchmark). The
checkpoints were mirrored into the lerobot/ org and that's the canonical
location going forward.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix: integrate PR #3313 review feedback

- docs: fix paper link to arxiv, add benchmark image, add suite descriptions,
  add LIBERO-plus replacement warning, restructure eval section to match
  LIBERO doc style, fix policy I/O section, remove false try/except claim
- docker: fix shell grouping for hf-libero uninstall, replace hardcoded
  asset path with dynamic find
- ci: add Docker Hub login step, add HF_USER_TOKEN guard on eval step
- envs: add is_libero_plus param to get_task_init_states so vanilla LIBERO
  always takes the simple path

* fix(docs): use correct LIBERO-plus teaser image URL

* ci(libero-plus): drop redundant hf auth login step

The standalone login step ran `hf auth login` in a throwaway
`docker run --rm` container, so no credentials persisted. Auth is
already performed inside the eval step's container. Removing the
redundant step per PR #3313 review feedback.

* fix(envs): preserve AsyncVectorEnv metadata/unwrapped in lazy eval envs

Port of #3416 onto this branch. Without these attributes eval crashes
when calling `env.unwrapped.metadata["render_fps"]` with async vector
envs. Adds `metadata` / `unwrapped` to `_LazyAsyncVectorEnv` and
caches the metadata alongside obs/action spaces in the LIBERO and
MetaWorld factories.

* ci: gate Docker Hub login on secret availability

Fork PRs cannot access `secrets.DOCKERHUB_LEROBOT_{USERNAME,PASSWORD}`,
which made every benchmark job fail at the login step before any of
the actual build/eval work could run. Gate the login on the env-var
expansion of the username so the step is skipped (not failed) when
secrets are absent. Mirrors the existing pattern in the VLABench job.

* Update .github/workflows/benchmark_tests.yml

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update scripts/ci/extract_task_descriptions.py

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update .github/workflows/benchmark_tests.yml

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update docker/Dockerfile.benchmark.libero_plus

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* Update .github/workflows/benchmark_tests.yml

Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>

* fix(libero-plus): address review feedback

* ci(libero-plus): fix YAML indentation in upload-artifact steps

The `uses:` key on two upload-artifact steps was at column 0 instead
of nested under the step, causing `pre-commit run check-yaml` to fail
with "expected <block end>, but found '<block mapping start>'".


Signed-off-by: Pepijn <138571049+pkooij@users.noreply.github.com>
Co-authored-by: Khalil Meftah <khalil.meftah@huggingface.co>
2026-04-20 21:07:21 +02:00
..

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.yml on 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.