Covers architecture overview, pretrained checkpoints, config reference,
training/eval commands for LIBERO-10, and guidance on fine-tuning for
single-camera datasets.
- Switch conftest to use `action_model_type="DiT-test"` now that
`action_num_heads` / `action_attention_head_dim` have been removed.
- Add action_head tests covering fully-padded loss (zero) and equivalence
of action_is_pad=None vs all-zeros mask.
- Remove obsolete `test_native_to_lerobot_wm_only` test.
- Remove stale `action_num_heads` / `action_attention_head_dim` config fields;
DiT head dimensions are now always derived from the preset (DiT-B/L/test).
- Add `num_target_vision_tokens` and `action_max_seq_len` config fields required
by the action head's future-token embedding and positional embedding tables.
- Fix default `qwen_model_name` to 2B (matches all released checkpoints).
- Rename `ActionEncoder` attrs w1/w2/w3 → layer1/layer2/layer3 to match
checkpoint key names; replace `nn.Sequential` decoder/state-encoder with
`_MLP2` (layer1/layer2 naming).
- Fix `VLAJEPAActionHead` to size ActionEncoder and StateEncoder at `inner_dim`
(DiT input width) rather than `action_hidden_size` (DiT output width).
- Rename `DiT.blocks` → `transformer_blocks` and `attn` → `attn1` to match
checkpoint; add alternating cross/self attention (even blocks cross-attend to
Qwen context, odd blocks self-attend).
- Add `DiT-test` preset for unit tests.
- Rewrite `ActionConditionedVideoPredictor` with explicit ViT-style blocks
(`_PredictorBlock` with fused qkv) to match checkpoint structure; rename
`encoder`/`norm`/`proj` → `predictor_blocks`/`predictor_norm`/`predictor_proj`.
* feat(rewards): add TOPReward reward model
* refactor(rewards): clean up TOPReward processor/model
* fix(rewards/topreward): add missing input keys mm_token_type_ids
* fix(rewards/topreward): fix pyproject extra typo and simplify processor (#3653)
Add lerobot[topreward] extra to all in
pyproject.toml, drop the redundant labels arg in scoring, and
collapse the dead-branch shape check in the encoder processor.
* optmize topreward input processing (#3660)
---------
Co-authored-by: Cole <91766445+jcoleharrison@users.noreply.github.com>
Co-authored-by: Haoming Song <haomingsong24@gmail.com>
PR #3145 added YAML support for policy.path but left two bugs:
1. extract_path_fields_from_config only deleted config_data[field] when
no sibling overrides existed. With siblings, the dict stayed in place
and draccus crashed decoding it as PreTrainedConfig (no 'type' key).
Sibling overrides go into _config_yaml_overrides and are applied later
by from_pretrained(), so the field can always be removed.
2. wrap() updated config_path_cli to the cleaned temp file path but
never propagated it to the draccus.parse fallback branch. cli_args
still contained --config_path=<original>, so draccus read the
original YAML with path: still present.
Tests passed because they (a) called extract_path_fields_from_config
directly and (b) included type: alongside path: in the YAML, sidestepping
both bugs.
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
* fix(deps): cap placo below 0.9.16 and harden kinematics import
placo 0.9.16 links against liburdfdom_sensor.so.4, which is unavailable
on Ubuntu 24.04 (noble ships urdfdom 3.x). Importing placo on that base
crashes with:
ImportError: liburdfdom_sensor.so.4.0: cannot open shared object file
This broke nightly Latest Deps tests (CPU and GPU) when the lockfile
upgrade picked placo 0.9.16, since lerobot.model.kinematics
unconditionally imports placo when _placo_available is true, and that
check (importlib.util.find_spec) cannot detect dlopen failures of
transitive shared libraries — so unrelated subsystems (RL actor,
gym_manipulator) became unimportable.
Two changes:
1. Pin placo to <0.9.16 in pyproject.toml + regenerate uv.lock
(0.9.16 → 0.9.15). Short-term unblock for nightly CI until system
urdfdom 4.x is broadly available.
2. Harden the import guard in src/lerobot/model/kinematics.py:
wrap 'import placo' in try/except ImportError so a missing
transitive .so no longer crashes module import. RobotKinematics
instantiation now raises an informative ImportError citing the
underlying dlopen failure via _raise_if_placo_unusable().
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* fix(kinematics): hoist _placo_runtime_error to module scope for mypy
Mypy walks the TYPE_CHECKING branch in which the runtime else-block is
not executed, so _placo_runtime_error was only defined at runtime and
mypy reported 'Name "_placo_runtime_error" is not defined' on the
three references inside _raise_if_placo_unusable. Declare the symbol
unconditionally at module scope with a default of None; the runtime
import-failure branch still assigns to it.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* style(kinematics): drop verbose comments around placo import guard
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(gr00t): sync with #3606 for fixing gr00t config crash
* fix(pi0&pi05): fix graph break caused by deepcopy of past_key_values in sample_actions
* fix(pi0&pi05): fix frequent recompile caused by compute_layer_complete
* feat(test): add compile test and benchamrk for pi0 and pi05
* feat(test): add comprehensive testing for pi0 and pi05. Including processor, forward, sample action, etc.
