Mechanical refactor of the GR00T N1.7 policy to match the repo's architecture and
style standards. No change to policy algorithm/numerics; only UX/CLI and packaging
changes. Tests are intentionally left untouched (out of scope) and need updating
for the removed `model_version` field.
Cleanup & consolidation:
- Add `groot/utils.py` holding the pure, side-effect-free helpers (JSON I/O, value
coercion, stat flattening, rot6d/SE3 math, language/batch prep) shared by the
config and processor layers.
- Remove dead code: the unused `resolve_groot_n1_7_backbone_model` cache-resolver
cluster, `GR00TN17Config.to_filtered_dict/json`, and the `_copy_default` wrapper.
Imports & execution guards:
- Hoist nested imports to module top; relative imports within the package, absolute
for external modules. The version-gated Qwen3-VL classes import under the single
`_transformers_available` guard (transformers is pinned >=5.4, which ships them).
- No import-time side effects: `_register_with_transformers()` now runs in
`GR00TN17.__init__` (idempotent via `register(exist_ok=True)`), and the N1.5 step
stubs register lazily before pipeline deserialization (idempotent via the
registry, no run-once globals).
- Gate optional deps at the point of use with `require_package(..., extra="groot")`.
Dependencies & docs:
- Drop `flash-attn` (and its build-only dep `ninja`) from the `groot` extra; default
to SDPA (numerically equivalent) with opt-in via `--policy.use_flash_attention`.
Un-comment `lerobot[groot]` in the `all` extra and regenerate `uv.lock`.
- Rewrite the `groot.mdx` install section: flash-attn is a purely optional,
user-managed optimization that LeRobot neither installs nor requires.
Config & CLI:
- Surface previously-frozen knobs on `GrootConfig` (plumbed into `GR00TN17Config`;
no-ops at their defaults): inference — `num_inference_timesteps`, `rtc_ramp_rate`,
`use_flash_attention`; fine-tuning — `tune_top_llm_layers` (partial-LLM tuning)
and `tune_vlln` (previously hardwired to True).
- Convert the single-valued `model_version` and `n1_7_backbone_model` fields to
internal constants.
- Keep `base_model_path`: it is NOT equivalent to `pretrained_path` (raw NVIDIA
checkpoints have no LeRobot `type` field and load only via `base_model_path`) and
is genuinely user-tunable.
- Keep the deprecated Isaac-GR00T/N1.5 fields (and the dead LoRA fields) as a
back-compat block so a v0.5.1 N1.5 `config.json` still parses under draccus and is
rejected with the friendly N1.5 removal message instead of an opaque decode error.
- groot.mdx: breaking-change warning and migration path (pin lerobot==0.5.1 to
keep N1.5, or move to N1.7); the dead `huggingface-cli download` is replaced
with `hf download`.
- policy_groot_README.md: N1.5 removal note, updated paper / model-card links,
and the two-comparison (model parity + preprocessor parity) description of
the original-vs-LeRobot test, including the raw-observation artifacts and
recorded seed.
- Fixed broken API examples in Lerobot Imitation Learning Documentation
- Teleoperation with cameras improved by adding a fixed frequency in the loop (without it the cameras feed gets very slow)
- Wrapped record example script in main() to avoid problems on Mac
- Previously teleoperation example was using SO-ARM and teleoperation with cameras was using Koch. I changed it to use SO-ARM in all of the examples.
- Added section on how to train with HF Jobs - CLI and Python examples
- Replaced lerobot-record with lerobot-rollout in policies examples
* chore(video backend): renaming codec into video_backend in get_safe_default_video_backend()
* feat(pyav utils): adding suport for PyAV encoding parameters validation
* feat(VideoEncoderConfig): creating a VideoEncoderConfig to encapsulate encoding parameters
* feat(VideoEncoderConfig): propagating the VideoEncoderConfig in the codebase
* chore(docs): updating the docs
* feat(metadata): adding encoding parameters in dataset metadata
* fix(concatenation compatibility): adding compatibility check when concatenating video files
* feat(VideoEncoderConfig init): making VideoEncoderConfig more robust and adaptable to multiple backends
* feat(pyav checks): making pyav parameters checks more robust
* chore(duplicate): removing duplicate get_codec_options definition
* test(existing): adapting existing tests
* test(new): adding new tests for encoding related features
* chore(format): fixing formatting issues
* chore(PyAV): cleaning up PyAV utils and encoding parameters checks to stick to the minimun required tooling.
* chore(format): formatting code
* chore(doctrings): updating docstrings
* fix(camera_encoder_config): Removing camera_encoder_config from LeRobotDataset, as it's only required in LeRobotDatasetWriter.
* feat(default values): applying a consistent naming convention for default RGB cameras video encoder parameters
* fix(rollout): propagating VideoEncoderConfig to the latest recording modes
* chore(format): formatting code, fixing error messages and variable names
* fix(arguments order): reverting changes in arguments order in StreamingVideoEncoder
* chore(relative imports): switching to relative local imports within lerobot.datasets
* test(artifacts): cleaning up artifacts for the video encoding tests
* chore(docs): updating docs
* chore(fromat): formatting code
* fix(imports): refactoring the file architecture to avoid circular imports. VideoEncoderConfig is now defined in lerobot.configs and lazily imports av at runtime.
* fix(typos): fixing typos and small mistakes
* test(factories): updating factories
* feat(aggregate): updating dataset aggregation procedure. Encoding tuning paramters (crf, g,...) are ignored for validation and changed to None in the aggregated dataset if incompatible.
* docs(typos): fixing typos
* fix(deletion): reverting unwanted deletion
* fix(typos): fixing multiple typos
* feat(codec options): passing codec options to lerobot_edit_dataset episode deletion tool
* typo(typo): typo
* fix(typos): fixing remaining typos
* chore(rename): renaming camera_encoder_config to camera_encoder
* docs(clean): cleaning and formating docs
* docs(dataset): addind details about datasets
* chore(format): formatting code
* docs(warning): adding warning regarding encoding parameters modification
* fix(re-encoding): removing inconsistent re-encoding option in lerobot_edit_dataset
* typos(typos): typos
* chore(format): resolving prettier issues
* fix(h264_nvenc): fixing crf handling for h264_nvenc
* docs(clean): removing too technical parts of the docs
* fix(imports): fixing imports at the __init__ level
* fix(imports): fixing not very pretty imports in video config file
* feat(robots): consolidates bi SO setups
* fix(robots): solve circular dependecy
* fix(robots): teleop & record working
* feat(robots): only one SO
* fix(utils): rename bi so
* fix(scripts): bi so import
* fix(rl): remove imports
Steven Palma