fix(train): guard checkpoint saving against save_freq=0 (#4112)

is_saving_step was the only step-frequency check without a `> 0` guard,
so save_freq=0 raised ZeroDivisionError from `step % 0` on the first
step. Route the decision through a should_save_checkpoint helper that
treats a non-positive save_freq as "save only the final checkpoint",
matching how log_freq/eval_freq handle non-positive values.

Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>

docs/source/cameras.mdx

@@ -164,8 +164,8 @@ includes the range reported by the sensor. Requesting an unsupported control als
 Omitted controls leave the sensor's existing automatic or manual setting unchanged. These options
 require `use_rgb=True`.
 
-On the RealSense D405, the color stream is provided by the Stereo Module, so changing manual
+Manual color controls require a dedicated RGB module. Cameras without one, such as the RealSense
-exposure or gain also affects the depth stream.
+D405, do not support them and raise an error at connection time.
 
 </hfoption>
 </hfoptions>

docs/source/hil_data_collection.mdx

@@ -59,6 +59,7 @@ The `lerobot-rollout --strategy.type=dagger` mode requires **teleoperators with
 
 - `bi_openarm_mini` - Bimanual OpenArm Mini
 - `so_leader` - SO100 / SO101 leader arm
+- `bi_so_leader` - Bimanual SO100 / SO101 leader arms
 
 > [!IMPORTANT]
 > The provided commands default to `bi_openarm_follower` + `bi_openarm_mini`.

docs/source/robocasa.mdx

@@ -82,6 +82,8 @@ By default the env samples objects only from the `lightwheel` registry (what `--
 
 All eval snippets below mirror the CI command (see `.github/workflows/benchmark_tests.yml`). The `--rename_map` argument maps RoboCasa's native camera keys (`robot0_agentview_left` / `robot0_eye_in_hand` / `robot0_agentview_right`) onto the three-camera (`camera1` / `camera2` / `camera3`) input layout the released `smolvla_robocasa` policy was trained on.
 
+By default, each task uses the rollout horizon registered by RoboCasa. Set `--env.episode_length=<steps>` to apply the same explicit horizon to every selected task.
+
 ### Single-task evaluation (recommended for quick iteration)
 
 ```bash

docs/source/so101.mdx

@@ -338,7 +338,7 @@ It is advisable to install one 3-pin cable in the motor after placing them befor
 <hfoption id="Leader">
 
 - Mount the leader holder onto the wrist and secure it with 4 M3x6mm screws.
-- Attach the handle to motor 5 using 1 M2x6mm screw.
+- Attach the handle to the leader holder using 1 M2x6mm screw.
 - Insert the gripper motor, secure it with 2 M2x6mm screws on each side, attach a motor horn using a M3x6mm horn screw.
 - Attach the follower trigger with 4 M3x6mm screws.
 

examples/isaac_teleop_to_so101/common.py

@@ -44,6 +44,7 @@ from typing import Protocol
 
 import numpy as np
 
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -56,7 +57,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
     EEBoundsAndSafety,
     InverseKinematicsEEToJoints,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import HF_LEROBOT_CALIBRATION, HF_LEROBOT_HOME, TELEOPERATORS
 from lerobot.utils.robot_utils import precise_sleep
 

examples/isaac_teleop_to_so101/isaac_teleop/teleop_so101_leader_arm.py

@@ -38,7 +38,7 @@ from typing import TYPE_CHECKING
 
 import numpy as np
 
-from lerobot.types import RobotAction
+from lerobot.lerobot_types import RobotAction
 
 from .base import _GRIPPER_MOTOR_SCALE, IsaacTeleopTeleoperator, _isaacteleop_available
 from .config_isaac_teleop import SO101LeaderArmConfig

examples/isaac_teleop_to_so101/isaac_teleop/teleop_xr_controller.py

@@ -32,7 +32,7 @@ from typing import TYPE_CHECKING, Any
 
 import numpy as np
 
-from lerobot.types import RobotAction
+from lerobot.lerobot_types import RobotAction
 
 from .base import IsaacTeleopTeleoperator, _isaacteleop_available
 from .config_isaac_teleop import XRControllerConfig

examples/isaac_teleop_to_so101/isaac_teleop/xr_controller_processor.py

@@ -26,8 +26,8 @@ from __future__ import annotations
 from dataclasses import dataclass
 
 from lerobot.configs.types import FeatureType, PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import RobotAction
 from lerobot.processor import ProcessorStepRegistry, RobotActionProcessorStep
-from lerobot.types import RobotAction
 from lerobot.utils.rotation import Rotation
 
 from .base import _GRIPPER_MOTOR_SCALE

examples/phone_to_so100/evaluate.py

@@ -21,6 +21,7 @@ from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.common.control_utils import predict_action
 from lerobot.configs import FeatureType, PolicyFeature
 from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.policies import make_pre_post_processors
 from lerobot.policies.act import ACTPolicy
@@ -38,7 +39,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
     ForwardKinematicsJointsToEE,
     InverseKinematicsEEToJoints,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame, combine_feature_dicts
 from lerobot.utils.keyboard_input import init_keyboard_listener

examples/phone_to_so100/record.py

@@ -16,6 +16,7 @@
 
 from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -36,7 +37,6 @@ from lerobot.scripts.lerobot_record import record_loop
 from lerobot.teleoperators.phone import Phone, PhoneConfig
 from lerobot.teleoperators.phone.config_phone import PhoneOS
 from lerobot.teleoperators.phone.phone_processor import MapPhoneActionToRobotAction
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.feature_utils import combine_feature_dicts
 from lerobot.utils.keyboard_input import init_keyboard_listener
 from lerobot.utils.utils import log_say

examples/phone_to_so100/replay.py

@@ -17,6 +17,7 @@
 import time
 
 from lerobot.datasets import LeRobotDataset
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -27,7 +28,6 @@ from lerobot.robots.so_follower import SO100Follower, SO100FollowerConfig
 from lerobot.robots.so_follower.robot_kinematic_processor import (
     InverseKinematicsEEToJoints,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION
 from lerobot.utils.robot_utils import precise_sleep
 from lerobot.utils.utils import log_say

examples/phone_to_so100/rollout.py

@@ -27,6 +27,7 @@ Highlight, or DAgger via ``lerobot-rollout --strategy.type=...``.
 
 from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.configs import PreTrainedConfig
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -43,7 +44,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
 from lerobot.rollout import BaseStrategyConfig, RolloutConfig, build_rollout_context
 from lerobot.rollout.inference import SyncInferenceConfig
 from lerobot.rollout.strategies import BaseStrategy
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.process import ProcessSignalHandler
 from lerobot.utils.utils import init_logging
 

examples/phone_to_so100/teleoperate.py

@@ -15,6 +15,7 @@
 
 import time
 
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -31,7 +32,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
 from lerobot.teleoperators.phone import Phone, PhoneConfig
 from lerobot.teleoperators.phone.config_phone import PhoneOS
 from lerobot.teleoperators.phone.phone_processor import MapPhoneActionToRobotAction
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.robot_utils import precise_sleep
 from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
 

examples/so100_to_so100_EE/evaluate.py

@@ -21,6 +21,7 @@ from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.common.control_utils import predict_action
 from lerobot.configs import FeatureType, PolicyFeature
 from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.policies import make_pre_post_processors
 from lerobot.policies.act import ACTPolicy
@@ -38,7 +39,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
     ForwardKinematicsJointsToEE,
     InverseKinematicsEEToJoints,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame, combine_feature_dicts
 from lerobot.utils.keyboard_input import init_keyboard_listener

examples/so100_to_so100_EE/record.py

@@ -17,6 +17,7 @@
 
 from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.datasets import LeRobotDataset, aggregate_pipeline_dataset_features, create_initial_features
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -33,7 +34,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
 )
 from lerobot.scripts.lerobot_record import record_loop
 from lerobot.teleoperators.so_leader import SO100Leader, SO100LeaderConfig
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.feature_utils import combine_feature_dicts
 from lerobot.utils.keyboard_input import init_keyboard_listener
 from lerobot.utils.utils import log_say

examples/so100_to_so100_EE/replay.py

@@ -18,6 +18,7 @@
 import time
 
 from lerobot.datasets import LeRobotDataset
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -28,7 +29,6 @@ from lerobot.robots.so_follower import SO100Follower, SO100FollowerConfig
 from lerobot.robots.so_follower.robot_kinematic_processor import (
     InverseKinematicsEEToJoints,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION
 from lerobot.utils.robot_utils import precise_sleep
 from lerobot.utils.utils import log_say

examples/so100_to_so100_EE/rollout.py

@@ -25,6 +25,7 @@ forward/inverse kinematics.
 
 from lerobot.cameras.opencv import OpenCVCameraConfig
 from lerobot.configs import PreTrainedConfig
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -41,7 +42,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
 from lerobot.rollout import BaseStrategyConfig, RolloutConfig, build_rollout_context
 from lerobot.rollout.inference import SyncInferenceConfig
 from lerobot.rollout.strategies import BaseStrategy
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.process import ProcessSignalHandler
 from lerobot.utils.utils import init_logging
 

examples/so100_to_so100_EE/teleoperate.py

@@ -16,6 +16,7 @@
 
 import time
 
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
     RobotProcessorPipeline,
@@ -30,7 +31,6 @@ from lerobot.robots.so_follower.robot_kinematic_processor import (
     InverseKinematicsEEToJoints,
 )
 from lerobot.teleoperators.so_leader import SO100Leader, SO100LeaderConfig
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.robot_utils import precise_sleep
 from lerobot.utils.visualization_utils import init_rerun, log_rerun_data
 

pyproject.toml

@@ -67,7 +67,7 @@ dependencies = [
     "einops>=0.8.0,<0.9.0",
 
     # Config & Hub
-    "draccus==0.10.0", # TODO: Relax version constraint
+    "draccus>=0.11.6,<0.12.0",
     "huggingface-hub>=1.0.0,<2.0.0",
     "requests>=2.32.0,<3.0.0",
 

src/lerobot/async_inference/policy_server.py

@@ -38,6 +38,7 @@ import draccus
 import grpc
 import torch
 
+from lerobot.lerobot_types import PolicyAction
 from lerobot.policies import get_policy_class, make_pre_post_processors
 from lerobot.processor import PolicyProcessorPipeline
 from lerobot.transport import (
@@ -45,7 +46,6 @@ from lerobot.transport import (
     services_pb2_grpc,  # type: ignore
 )
 from lerobot.transport.utils import receive_bytes_in_chunks
-from lerobot.types import PolicyAction
 
 from .configs import PolicyServerConfig
 from .constants import SUPPORTED_POLICIES

src/lerobot/cameras/realsense/camera_realsense.py

@@ -365,11 +365,12 @@ class RealSenseCamera(Camera):
         return self._async_read(timeout_ms=10000, read_depth=read_depth)
 
     def _get_color_sensor(self) -> "rs.sensor":
-        """Returns the sensor that controls the color stream.
+        """Returns the dedicated "RGB Camera" sensor that controls the color stream.
 
-        Most RealSense cameras expose "RGB Camera" for color. The D405 has no
+        Manual color controls are only applied to a dedicated RGB module. Cameras
-        separate RGB module — its color stream comes from "Stereo Module".
+        without one (e.g. the D405, whose color stream comes from the shared
-        We try RGB Camera first, then fall back to Stereo Module.
+        "Stereo Module") are unsupported, so we never fall back to another sensor
+        to avoid altering the depth stream.
         """
         if self.rs_profile is None:
             raise RuntimeError(f"{self}: rs_profile must be initialized before use.")
@@ -377,12 +378,14 @@ class RealSenseCamera(Camera):
         device = self.rs_profile.get_device()
         sensors = {s.get_info(rs.camera_info.name): s for s in device.query_sensors()}
 
-        for name in ("RGB Camera", "Stereo Module"):
+        if "RGB Camera" in sensors:
-            if name in sensors:
+            return sensors["RGB Camera"]
-                return sensors[name]
 
         available = list(sensors.keys())
-        raise RuntimeError(f"{self}: no color sensor found. Available sensors: {available}")
+        raise RuntimeError(
+            f"{self}: manual color controls require a dedicated 'RGB Camera' module, which this camera does not have. ",
+            f"Available sensors: {available}.",
+        )
 
     def _set_sensor_option(self, sensor: "rs.sensor", option: "rs.option", value: float, label: str) -> None:
         """Sets a sensor option, re-raising range errors with actionable diagnostics."""

src/lerobot/common/control_utils.py

@@ -35,9 +35,9 @@ else:
 
 if TYPE_CHECKING:
     from lerobot.datasets import LeRobotDataset
+from lerobot.lerobot_types import PolicyAction
 from lerobot.processor import PolicyProcessorPipeline
 from lerobot.robots import Robot
-from lerobot.types import PolicyAction
 
 
 def predict_action(

src/lerobot/common/train_utils.py

@@ -52,6 +52,17 @@ def get_step_checkpoint_dir(output_dir: Path, total_steps: int, step: int) -> Pa
     return output_dir / CHECKPOINTS_DIR / step_identifier
 
 
+def should_save_checkpoint(step: int, save_freq: int, total_steps: int) -> bool:
+    """Whether a checkpoint should be saved at ``step``.
+
+    A checkpoint is saved every ``save_freq`` steps and always after the final step. A
+    non-positive ``save_freq`` disables periodic saving (only the final checkpoint is
+    written), mirroring how ``log_freq``/``eval_freq`` treat non-positive values and
+    avoiding a ``ZeroDivisionError`` from ``step % 0``.
+    """
+    return (save_freq > 0 and step % save_freq == 0) or step == total_steps
+
+
 def save_training_step(
     step: int, save_dir: Path, num_processes: int | None = None, batch_size: int | None = None
 ) -> None:

src/lerobot/configs/policies.py

@@ -163,8 +163,10 @@ class PreTrainedConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):  # type: igno
         return None
 
     def _save_pretrained(self, save_directory: Path) -> None:
-        with open(save_directory / CONFIG_NAME, "w") as f, draccus.config_type("json"):
+        # Encode against the base class so draccus includes the choice "type" key,
-            draccus.dump(self, f, indent=4)
+        # which `from_pretrained` needs to resolve the concrete subclass.
+        with open(save_directory / CONFIG_NAME, "w") as f:
+            json.dump(draccus.encode(self, PreTrainedConfig), f, indent=4)
 
     @classmethod
     def from_pretrained(

src/lerobot/configs/rewards.py

@@ -103,8 +103,10 @@ class RewardModelConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):
         pass
 
     def _save_pretrained(self, save_directory: Path) -> None:
-        with open(save_directory / CONFIG_NAME, "w") as f, draccus.config_type("json"):
+        # Encode against the base class so draccus includes the choice "type" key,
-            draccus.dump(self, f, indent=4)
+        # which `from_pretrained` needs to resolve the concrete subclass.
+        with open(save_directory / CONFIG_NAME, "w") as f:
+            json.dump(draccus.encode(self, RewardModelConfig), f, indent=4)
 
     @classmethod
     def from_pretrained(

src/lerobot/configs/train.py

@@ -119,6 +119,7 @@ class TrainPipelineConfig(HubMixin):
     tolerance_s: float = 1e-4
     save_checkpoint: bool = True
     # Checkpoint is saved every `save_freq` training iterations and after the last training step.
+    # A non-positive value disables periodic saving, keeping only the final checkpoint.
     save_freq: int = 20_000
     use_policy_training_preset: bool = True
     optimizer: OptimizerConfig | None = None
@@ -194,7 +195,11 @@ class TrainPipelineConfig(HubMixin):
             )
 
         if Path(config_path).resolve().exists():
-            policy_dir = Path(config_path).parent
+            # `config_path` may point at the checkpoint's train_config.json or at its
+            # pretrained_model/ directory (both documented above) — resolve either to
+            # the pretrained_model/ directory.
+            config_path_obj = Path(config_path)
+            policy_dir = config_path_obj.parent if config_path_obj.is_file() else config_path_obj
             self.checkpoint_path = policy_dir.parent
         elif self.job.is_remote:
             return

src/lerobot/datasets/dataset_writer.py

@@ -386,6 +386,9 @@ class DatasetWriter:
                 self._episodes_since_last_encoding = 0
 
         if episode_data is None:
+            # Post-save cleanup deliberately does not go through clear_episode_buffer():
+            # staging frames of video cameras must survive here — the (possibly batched)
+            # encoder still needs them and deletes them once each video is written.
             if len(self._meta.image_keys) > 0:
                 self._delete_camera_frame_dirs(self._meta.image_keys)
             self.episode_buffer = self._create_episode_buffer()

src/lerobot/datasets/pipeline_features.py

@@ -17,8 +17,8 @@ from collections.abc import Sequence
 from typing import Any
 
 from lerobot.configs import PipelineFeatureType
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.processor import DataProcessorPipeline
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION, OBS_IMAGES, OBS_STATE, OBS_STR
 from lerobot.utils.feature_utils import hw_to_dataset_features
 

src/lerobot/datasets/streaming_dataset.py

@@ -58,6 +58,10 @@ class LookAheadError(Exception):
     pass
 
 
+class _ShardExhaustedError(Exception):
+    """Raised when a streaming dataset shard has no more items."""
+
+
 class Backtrackable[T]:
     """
     Wrap any iterator/iterable so you can step back up to `history` items
@@ -178,7 +182,7 @@ class Backtrackable[T]:
         """
         Check if we can go back `steps` items without raising an IndexError.
         """
-        return steps <= len(self._back_buf) + self._cursor
+        return steps < len(self._back_buf) + self._cursor
 
     def can_peek_ahead(self, steps: int = 1) -> bool:
         """
@@ -422,10 +426,7 @@ class StreamingLeRobotDataset(torch.utils.data.IterableDataset):
                     else:
                         frames_buffer.append(frame)
                     break  # random shard sampled, switch shard
-            except (
+            except _ShardExhaustedError:
-                RuntimeError,
-                StopIteration,
-            ):  # NOTE: StopIteration inside a generator throws a RuntimeError since python 3.7
                 del idx_to_backtrack_dataset[shard_key]  # Remove exhausted shard, onto another shard
 
         # Once shards are all exhausted, shuffle the buffer and yield the remaining frames
@@ -503,7 +504,11 @@ class StreamingLeRobotDataset(torch.utils.data.IterableDataset):
 
     def make_frame(self, dataset_iterator: Backtrackable) -> Generator:
         """Makes a frame starting from a dataset iterator"""
-        item = next(dataset_iterator)
+        try:
+            item = next(dataset_iterator)
+        except StopIteration as e:
+            # Translate exhaustion here, before PEP 479 turns it into an indistinguishable RuntimeError.
+            raise _ShardExhaustedError from e
         item = item_to_torch(item)
 
         updates = []  # list of "updates" to apply to the item retrieved from hf_dataset (w/o camera features)

src/lerobot/envs/configs.py

@@ -507,7 +507,7 @@ class MetaworldEnv(EnvConfig):
 class RoboCasaEnv(EnvConfig):
     task: str = "CloseFridge"
     fps: int = 20
-    episode_length: int = 1000
+    episode_length: int | None = None
     obs_type: str = "pixels_agent_pos"
     render_mode: str = "rgb_array"
     camera_name: str = "robot0_agentview_left,robot0_eye_in_hand,robot0_agentview_right"

src/lerobot/envs/libero.py

@@ -30,7 +30,7 @@ from gymnasium import spaces
 from libero.libero import benchmark, get_libero_path
 from libero.libero.envs import OffScreenRenderEnv
 
-from lerobot.types import RobotObservation
+from lerobot.lerobot_types import RobotObservation
 
 from .utils import _LazyAsyncVectorEnv, parse_camera_names
 

src/lerobot/envs/metaworld.py

@@ -25,7 +25,7 @@ import metaworld.policies as policies
 import numpy as np
 from gymnasium import spaces
 
-from lerobot.types import RobotObservation
+from lerobot.lerobot_types import RobotObservation
 
 from .utils import _LazyAsyncVectorEnv
 

src/lerobot/envs/robocasa.py

@@ -25,7 +25,7 @@ import gymnasium as gym
 import numpy as np
 from gymnasium import spaces
 
-from lerobot.types import RobotObservation
+from lerobot.lerobot_types import RobotObservation
 
 from .utils import _LazyAsyncVectorEnv, parse_camera_names
 
@@ -98,6 +98,19 @@ def _resolve_tasks(task: str) -> tuple[list[str], str | None]:
     return names, None
 
 
+def _get_task_horizon(task: str) -> int:
+    """Return the rollout horizon registered by RoboCasa for a task."""
+    from robocasa.utils.dataset_registry_utils import get_task_horizon
+
+    try:
+        return int(get_task_horizon(task))
+    except ValueError as exc:
+        raise ValueError(
+            f"No RoboCasa horizon is registered for task '{task}'. "
+            "Set `--env.episode_length=<steps>` explicitly."
+        ) from exc
+
+
 def convert_action(flat_action: np.ndarray) -> dict[str, Any]:
     """Split a flat (12,) action vector into a RoboCasa action dict.
 
@@ -154,7 +167,7 @@ class RoboCasaEnv(gym.Env):
 
         self.camera_name = parse_camera_names(camera_name)
 
-        self._max_episode_steps = episode_length if episode_length is not None else 1000
+        self._max_episode_steps = episode_length if episode_length is not None else _get_task_horizon(task)
 
         # Deferred — created on first reset() inside the worker subprocess
         # to avoid inheriting stale GPU/EGL contexts across fork().

src/lerobot/envs/robotwin.py

@@ -28,7 +28,7 @@ import numpy as np
 import torch
 from gymnasium import spaces
 
-from lerobot.types import RobotObservation
+from lerobot.lerobot_types import RobotObservation
 from lerobot.utils.import_utils import _scipy_available
 
 from .utils import _LazyAsyncVectorEnv

src/lerobot/envs/vlabench.py

@@ -37,7 +37,7 @@ import numpy as np
 from gymnasium import spaces
 from scipy.spatial.transform import Rotation
 
-from lerobot.types import RobotObservation
+from lerobot.lerobot_types import RobotObservation
 
 from .utils import _LazyAsyncVectorEnv
 

src/lerobot/policies/eo1/processor_eo1.py

@@ -22,6 +22,7 @@ from typing import TYPE_CHECKING, Any
 import torch
 
 from lerobot.configs.types import FeatureType, PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import TransitionKey
 from lerobot.processor import (
     ComplementaryDataProcessorStep,
     PolicyAction,
@@ -31,7 +32,6 @@ from lerobot.processor import (
     make_default_policy_processor_steps,
     make_policy_processor_pipelines,
 )
-from lerobot.types import TransitionKey
 from lerobot.utils.constants import OBS_STATE
 from lerobot.utils.import_utils import _transformers_available, require_package
 

src/lerobot/policies/evo1/modeling_evo1.py

@@ -42,6 +42,9 @@ class Evo1Policy(PreTrainedPolicy):
     config_class = Evo1Config
     name = "evo1"
 
+    def supports_rtc(self) -> bool:
+        return True
+
     def __init__(self, config: Evo1Config, *, vlm_hub_kwargs: dict | None = None, **kwargs):
         super().__init__(config)
         config.validate_features()

src/lerobot/policies/evo1/processor_evo1.py

@@ -21,6 +21,7 @@ from typing import Any
 import torch
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
     DeviceProcessorStep,
@@ -40,7 +41,6 @@ from lerobot.processor.converters import (
     policy_action_to_transition,
     transition_to_policy_action,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     ACTION,
     DONE,

src/lerobot/policies/factory.py

@@ -28,6 +28,7 @@ if TYPE_CHECKING:
 
 from lerobot.configs import FeatureType, PreTrainedConfig
 from lerobot.envs import EnvConfig, env_to_policy_features
+from lerobot.lerobot_types import PolicyAction
 from lerobot.processor import (
     AbsoluteActionsProcessorStep,
     PolicyProcessorPipeline,
@@ -37,7 +38,6 @@ from lerobot.processor import (
     transition_to_batch,
     transition_to_policy_action,
 )
-from lerobot.types import PolicyAction
 from lerobot.utils.constants import (
     ACTION,
     POLICY_POSTPROCESSOR_DEFAULT_NAME,

src/lerobot/policies/groot/modeling_groot.py

@@ -68,6 +68,9 @@ class GrootPolicy(PreTrainedPolicy):
     name = "groot"
     config_class = GrootConfig
 
+    def supports_rtc(self) -> bool:
+        return True
+
     def __init__(self, config: GrootConfig, **kwargs):
         """Initialize Groot policy wrapper."""
         require_package("transformers", extra="groot")

src/lerobot/policies/groot/processor_groot.py

@@ -50,6 +50,7 @@ if TYPE_CHECKING or _datasets_available:
 else:
     LeRobotDataset = None
 
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AbsoluteActionsProcessorStep,
     AddBatchDimensionProcessorStep,
@@ -66,7 +67,6 @@ from lerobot.processor import (
     transition_to_batch,
     transition_to_policy_action,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     ACTION,
     OBS_IMAGE,

src/lerobot/policies/molmoact2/modeling_molmoact2.py

@@ -520,6 +520,9 @@ class MolmoAct2Policy(PreTrainedPolicy):
     config_class = MolmoAct2Config
     name = "molmoact2"
 
+    def supports_rtc(self) -> bool:
+        return self.config.inference_action_mode == "continuous"
+
     def __init__(
         self,
         config: MolmoAct2Config,

src/lerobot/policies/molmoact2/processor_molmoact2.py

@@ -36,6 +36,7 @@ import torch
 from torch import Tensor
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
     DeviceProcessorStep,
@@ -49,7 +50,6 @@ from lerobot.processor import (
     policy_action_to_transition,
     transition_to_policy_action,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     ACTION,
     OBS_IMAGES,

src/lerobot/policies/pi0/modeling_pi0.py

@@ -749,6 +749,9 @@ class PI0Policy(PreTrainedPolicy):
     config_class = PI0Config
     name = "pi0"
 
+    def supports_rtc(self) -> bool:
+        return True
+
     def __init__(
         self,
         config: PI0Config,

src/lerobot/policies/pi05/modeling_pi05.py

@@ -714,6 +714,9 @@ class PI05Policy(PreTrainedPolicy):
     config_class = PI05Config
     name = "pi05"
 
+    def supports_rtc(self) -> bool:
+        return True
+
     def __init__(
         self,
         config: PI05Config,

src/lerobot/policies/pi05/processor_pi05.py

@@ -22,6 +22,7 @@ import numpy as np
 import torch
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AbsoluteActionsProcessorStep,
     PolicyAction,
@@ -33,7 +34,6 @@ from lerobot.processor import (
     make_default_policy_processor_steps,
     make_policy_processor_pipelines,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import OBS_STATE
 
 from .configuration_pi05 import PI05Config

src/lerobot/policies/pi0_fast/processor_pi0_fast.py

@@ -22,6 +22,7 @@ import numpy as np
 import torch
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AbsoluteActionsProcessorStep,
     ActionTokenizerProcessorStep,
@@ -34,7 +35,6 @@ from lerobot.processor import (
     make_default_policy_processor_steps,
     make_policy_processor_pipelines,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import OBS_STATE
 
 from .configuration_pi0_fast import PI0FastConfig

src/lerobot/policies/pretrained.py

@@ -249,6 +249,10 @@ class PreTrainedPolicy(nn.Module, HubMixin, abc.ABC):
         """
         raise NotImplementedError
 
+    def supports_rtc(self) -> bool:
+        """Whether this policy implements Real-Time Chunking inference semantics."""
+        return False
+
     # TODO(aliberts, rcadene): split into 'forward' and 'compute_loss'?
     @abc.abstractmethod
     def forward(self, batch: dict[str, Tensor]) -> tuple[Tensor, dict | None]:

src/lerobot/policies/smolvla/modeling_smolvla.py

@@ -145,6 +145,9 @@ class SmolVLAPolicy(PreTrainedPolicy):
     config_class = SmolVLAConfig
     name = "smolvla"
 
+    def supports_rtc(self) -> bool:
+        return True
+
     def __init__(
         self,
         config: SmolVLAConfig,

src/lerobot/policies/smolvla/smolvlm_with_expert.py

@@ -168,14 +168,23 @@ class SmolVLMWithExpertModel(nn.Module):
                 last_layers.append(self.num_vlm_layers - 2)
             frozen_layers = [
                 "lm_head",
-                "text_model.model.norm.weight",
+                "text_model.norm.weight",
             ]
             for layer in last_layers:
-                frozen_layers.append(f"text_model.model.layers.{layer}.")
+                frozen_layers.append(f"text_model.layers.{layer}.")
 
+            unmatched_patterns = set(frozen_layers)
             for name, params in self.vlm.named_parameters():
-                if any(k in name for k in frozen_layers):
+                matched_patterns = [k for k in frozen_layers if k in name]
+                if matched_patterns:
                     params.requires_grad = False
+                    unmatched_patterns.difference_update(matched_patterns)
+            if unmatched_patterns:
+                raise RuntimeError(
+                    "Some frozen layer patterns matched no VLM parameters, so the corresponding layers "
+                    "would silently remain trainable (parameter naming may have changed in transformers): "
+                    f"{sorted(unmatched_patterns)}"
+                )
         # To avoid unused params issue with distributed training
         for name, params in self.lm_expert.named_parameters():
             if "lm_head" in name:

src/lerobot/policies/utils.py

@@ -22,7 +22,7 @@ import torch
 from torch import nn
 
 from lerobot.configs import FeatureType, PolicyFeature, PreTrainedConfig
-from lerobot.types import PolicyAction, RobotAction, RobotObservation
+from lerobot.lerobot_types import PolicyAction, RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION, OBS_STR
 from lerobot.utils.feature_utils import build_dataset_frame
 

src/lerobot/policies/xvla/modeling_xvla.py

@@ -150,7 +150,7 @@ class XVLAModel(nn.Module):
         # Freeze or unfreeze policy transformer
         if not self.config.train_policy_transformer:
             for name, param in self.transformer.named_parameters():
-                if "soft_prompts" not in name:
+                if "soft_prompt" not in name:
                     param.requires_grad = False
 
         # Freeze or unfreeze soft prompts

src/lerobot/policies/xvla/processor_xvla.py

@@ -21,6 +21,7 @@ import numpy as np
 import torch
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     ObservationProcessorStep,
     PolicyAction,
@@ -31,7 +32,6 @@ from lerobot.processor import (
     make_default_policy_processor_steps,
     make_policy_processor_pipelines,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     IMAGENET_STATS,
     OBS_IMAGES,

src/lerobot/processor/__init__.py

@@ -14,7 +14,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from lerobot.types import (
+from lerobot.lerobot_types import (
     EnvAction,
     EnvTransition,
     PolicyAction,

src/lerobot/processor/batch_processor.py

@@ -25,7 +25,7 @@ from dataclasses import dataclass, field
 from torch import Tensor
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvTransition, PolicyAction
+from lerobot.lerobot_types import EnvTransition, PolicyAction
 from lerobot.utils.constants import OBS_ENV_STATE, OBS_IMAGE, OBS_IMAGES, OBS_STATE
 
 from .pipeline import (

src/lerobot/processor/converters.py

@@ -23,7 +23,7 @@ from typing import Any
 import numpy as np
 import torch
 
-from lerobot.types import EnvTransition, PolicyAction, RobotAction, RobotObservation, TransitionKey
+from lerobot.lerobot_types import EnvTransition, PolicyAction, RobotAction, RobotObservation, TransitionKey
 from lerobot.utils.constants import ACTION, DONE, INFO, OBS_PREFIX, REWARD, TRUNCATED
 
 

src/lerobot/processor/delta_action_processor.py

@@ -17,7 +17,7 @@
 from dataclasses import dataclass
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
-from lerobot.types import PolicyAction, RobotAction
+from lerobot.lerobot_types import PolicyAction, RobotAction
 
 from .pipeline import ActionProcessorStep, ProcessorStepRegistry, RobotActionProcessorStep
 

src/lerobot/processor/device_processor.py

@@ -25,7 +25,7 @@ from typing import Any
 import torch
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvTransition, PolicyAction, TransitionKey
+from lerobot.lerobot_types import EnvTransition, PolicyAction, TransitionKey
 from lerobot.utils.device_utils import get_safe_torch_device
 
 from .pipeline import ProcessorStep, ProcessorStepRegistry

src/lerobot/processor/factory.py

@@ -20,7 +20,7 @@ from typing import Any
 import torch
 
 from lerobot.configs.policies import PreTrainedConfig
-from lerobot.types import PolicyAction, RobotAction, RobotObservation
+from lerobot.lerobot_types import PolicyAction, RobotAction, RobotObservation
 from lerobot.utils.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 
 from .batch_processor import AddBatchDimensionProcessorStep

src/lerobot/processor/gym_action_processor.py

@@ -17,7 +17,7 @@
 from dataclasses import dataclass
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvAction, EnvTransition, PolicyAction, TransitionKey
+from lerobot.lerobot_types import EnvAction, EnvTransition, PolicyAction, TransitionKey
 
 from .converters import to_tensor
 from .hil_processor import TELEOP_ACTION_KEY

src/lerobot/processor/hil_processor.py

@@ -29,7 +29,7 @@ from lerobot.teleoperators.utils import TeleopEvents
 if TYPE_CHECKING:
     from lerobot.teleoperators.teleoperator import Teleoperator
 
-from lerobot.types import EnvTransition, PolicyAction, TransitionKey
+from lerobot.lerobot_types import EnvTransition, PolicyAction, TransitionKey
 
 from .pipeline import (
     ComplementaryDataProcessorStep,

src/lerobot/processor/normalize_processor.py

@@ -25,7 +25,7 @@ import torch
 from torch import Tensor
 
 from lerobot.configs import FeatureType, NormalizationMode, PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvTransition, PolicyAction, TransitionKey
+from lerobot.lerobot_types import EnvTransition, PolicyAction, TransitionKey
 
 if TYPE_CHECKING:
     from lerobot.datasets import LeRobotDataset

src/lerobot/processor/pipeline.py

@@ -45,7 +45,14 @@ from huggingface_hub import hf_hub_download
 from safetensors.torch import load_file, save_file
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvAction, EnvTransition, PolicyAction, RobotAction, RobotObservation, TransitionKey
+from lerobot.lerobot_types import (
+    EnvAction,
+    EnvTransition,
+    PolicyAction,
+    RobotAction,
+    RobotObservation,
+    TransitionKey,
+)
 from lerobot.utils.constants import HF_LEROBOT_HOME
 from lerobot.utils.hub import HubMixin
 

src/lerobot/processor/policy_robot_bridge.py

@@ -20,7 +20,7 @@ from typing import Any
 import torch
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
-from lerobot.types import PolicyAction, RobotAction
+from lerobot.lerobot_types import PolicyAction, RobotAction
 from lerobot.utils.constants import ACTION
 
 from .pipeline import ActionProcessorStep, ProcessorStepRegistry

src/lerobot/processor/relative_action_processor.py

@@ -20,7 +20,7 @@ import torch
 from torch import Tensor
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvTransition, TransitionKey
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.utils.constants import OBS_STATE
 
 from .delta_action_processor import MapDeltaActionToRobotActionStep, MapTensorToDeltaActionDictStep

src/lerobot/processor/render_messages_processor.py

@@ -23,7 +23,7 @@ from lerobot.configs import PipelineFeatureType, PolicyFeature
 from lerobot.configs.recipe import TrainingRecipe
 from lerobot.datasets.language import LANGUAGE_EVENTS, LANGUAGE_PERSISTENT
 from lerobot.datasets.language_render import render_sample
-from lerobot.types import EnvTransition, TransitionKey
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.utils.utils import unwrap_scalar
 
 from .pipeline import ProcessorStep, ProcessorStepRegistry

src/lerobot/processor/tokenizer_processor.py

@@ -30,7 +30,7 @@ from typing import TYPE_CHECKING, Any
 import torch
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
-from lerobot.types import EnvTransition, RobotObservation, TransitionKey
+from lerobot.lerobot_types import EnvTransition, RobotObservation, TransitionKey
 from lerobot.utils.constants import (
     ACTION_TOKEN_MASK,
     ACTION_TOKENS,

src/lerobot/rewards/robometer/compute_rabc_weights.py

@@ -57,10 +57,10 @@ import torch
 from tqdm import tqdm
 
 from lerobot.datasets import LeRobotDataset
+from lerobot.lerobot_types import TransitionKey
 from lerobot.rewards.robometer.configuration_robometer import RobometerConfig
 from lerobot.rewards.robometer.modeling_robometer import RobometerRewardModel
 from lerobot.rewards.robometer.processor_robometer import RobometerEncoderProcessorStep
-from lerobot.types import TransitionKey
 
 DEFAULT_OUTPUT_FILENAME = "robometer_progress.parquet"
 

src/lerobot/rewards/robometer/processor_robometer.py

@@ -25,6 +25,7 @@ from PIL import Image
 from torch import Tensor
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
     DeviceProcessorStep,
@@ -39,7 +40,6 @@ from lerobot.rewards.robometer.configuration_robometer import (
     RobometerConfig,
 )
 from lerobot.rewards.robometer.modeling_robometer import ROBOMETER_FEATURE_PREFIX
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     OBS_IMAGES,
     POLICY_POSTPROCESSOR_DEFAULT_NAME,

src/lerobot/rewards/sarm/processor_sarm.py

@@ -47,6 +47,7 @@ else:
     Faker = None  # type: ignore[assignment, misc]
 
 from lerobot.configs import FeatureType, PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, PolicyAction, TransitionKey
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
     DeviceProcessorStep,
@@ -58,7 +59,6 @@ from lerobot.processor import (
     policy_action_to_transition,
     transition_to_policy_action,
 )
-from lerobot.types import EnvTransition, PolicyAction, TransitionKey
 from lerobot.utils.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 
 from .configuration_sarm import SARMConfig

src/lerobot/rewards/topreward/compute_rabc_weights.py

@@ -48,10 +48,10 @@ import torch
 from tqdm import tqdm
 
 from lerobot.datasets import LeRobotDataset
+from lerobot.lerobot_types import TransitionKey
 from lerobot.rewards.topreward.configuration_topreward import TOPRewardConfig
 from lerobot.rewards.topreward.modeling_topreward import TOPRewardModel
 from lerobot.rewards.topreward.processor_topreward import TOPRewardEncoderProcessorStep
-from lerobot.types import TransitionKey
 
 DEFAULT_OUTPUT_FILENAME = "topreward_progress.parquet"
 

src/lerobot/rewards/topreward/processor_topreward.py

@@ -23,6 +23,7 @@ import torch
 from torch import Tensor
 
 from lerobot.configs import PipelineFeatureType, PolicyFeature
+from lerobot.lerobot_types import EnvTransition, TransitionKey
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
     DeviceProcessorStep,
@@ -37,7 +38,6 @@ from lerobot.rewards.topreward.configuration_topreward import (
     DEFAULT_PROMPT_SUFFIX_TEMPLATE,
     TOPRewardConfig,
 )
-from lerobot.types import EnvTransition, TransitionKey
 from lerobot.utils.constants import (
     OBS_IMAGES,
     OBS_PREFIX,

src/lerobot/rl/algorithms/base.py

@@ -28,7 +28,7 @@ from huggingface_hub.errors import HfHubHTTPError
 from safetensors.torch import load_file as load_safetensors, save_file as save_safetensors
 from torch.optim import Optimizer
 
-from lerobot.types import BatchType
+from lerobot.lerobot_types import BatchType
 from lerobot.utils.hub import HubMixin
 
 from .configs import RLAlgorithmConfig, TrainingStats

src/lerobot/rl/algorithms/configs.py

@@ -16,6 +16,7 @@ from __future__ import annotations
 
 import abc
 import builtins
+import json
 import logging
 import os
 from dataclasses import dataclass, field
@@ -78,8 +79,10 @@ class RLAlgorithmConfig(draccus.ChoiceRegistry, HubMixin, abc.ABC):
 
     def _save_pretrained(self, save_directory: Path) -> None:
         """Serialize this config as ``config.json`` inside ``save_directory``."""
-        with open(save_directory / CONFIG_NAME, "w") as f, draccus.config_type("json"):
+        # Encode against the base class so draccus includes the choice "type" key,
-            draccus.dump(self, f, indent=4)
+        # which `from_pretrained` needs to resolve the concrete subclass.
+        with open(save_directory / CONFIG_NAME, "w") as f:
+            json.dump(draccus.encode(self, RLAlgorithmConfig), f, indent=4)
 
     @classmethod
     def from_pretrained(

src/lerobot/rl/algorithms/sac/sac_algorithm.py

@@ -26,6 +26,7 @@ import torch.nn.functional as F  # noqa: N812
 from torch import Tensor
 from torch.optim import Optimizer
 
+from lerobot.lerobot_types import BatchType
 from lerobot.policies.gaussian_actor.modeling_gaussian_actor import (
     DISCRETE_DIMENSION_INDEX,
     MLP,
@@ -35,7 +36,6 @@ from lerobot.policies.gaussian_actor.modeling_gaussian_actor import (
     orthogonal_init,
 )
 from lerobot.policies.utils import get_device_from_parameters
-from lerobot.types import BatchType
 from lerobot.utils.constants import ACTION
 from lerobot.utils.transition import move_state_dict_to_device
 

src/lerobot/rl/data_sources/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from lerobot.types import BatchType
+from lerobot.lerobot_types import BatchType
 
 from .data_mixer import DataMixer, OnlineOfflineMixer
 

src/lerobot/rl/data_sources/data_mixer.py

@@ -16,7 +16,7 @@ from __future__ import annotations
 
 import abc
 
-from lerobot.types import BatchType
+from lerobot.lerobot_types import BatchType
 
 from ..buffer import ReplayBuffer, concatenate_batch_transitions
 

src/lerobot/rl/trainer.py

@@ -17,7 +17,7 @@ from __future__ import annotations
 from collections.abc import Iterator
 from typing import Any
 
-from lerobot.types import BatchType
+from lerobot.lerobot_types import BatchType
 
 from .algorithms.base import RLAlgorithm
 from .algorithms.configs import TrainingStats

src/lerobot/robots/bi_openarm_follower/bi_openarm_follower.py

@@ -17,7 +17,7 @@
 import logging
 from functools import cached_property
 
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.bimanual import BimanualMixin
 from lerobot.utils.decorators import check_if_not_connected
 

src/lerobot/robots/bi_rebot_b601_follower/bi_rebot_b601_follower.py

@@ -17,7 +17,7 @@
 import logging
 from functools import cached_property
 
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.bimanual import BimanualMixin
 from lerobot.utils.decorators import check_if_not_connected
 

src/lerobot/robots/bi_so_follower/bi_so_follower.py

@@ -17,7 +17,7 @@
 import logging
 from functools import cached_property
 
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.bimanual import BimanualMixin
 from lerobot.utils.decorators import check_if_not_connected
 
@@ -62,6 +62,7 @@ class BiSOFollower(BimanualMixin, Robot):
             position_i_coefficient=config.left_arm_config.position_i_coefficient,
             position_d_coefficient=config.left_arm_config.position_d_coefficient,
             use_degrees=config.left_arm_config.use_degrees,
+            num_read_retries=config.left_arm_config.num_read_retries,
             cameras=left_arm_cameras,
         )
 
@@ -75,6 +76,7 @@ class BiSOFollower(BimanualMixin, Robot):
             position_i_coefficient=config.right_arm_config.position_i_coefficient,
             position_d_coefficient=config.right_arm_config.position_d_coefficient,
             use_degrees=config.right_arm_config.use_degrees,
+            num_read_retries=config.right_arm_config.num_read_retries,
             cameras=config.right_arm_config.cameras,
         )
 

src/lerobot/robots/earthrover_mini_plus/robot_earthrover_mini_plus.py

@@ -23,7 +23,7 @@ import cv2
 import numpy as np
 import requests
 
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 from lerobot.utils.errors import DeviceNotConnectedError
 

src/lerobot/robots/hope_jr/hope_jr_arm.py

@@ -19,12 +19,12 @@ import time
 from functools import cached_property
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorNormMode
 from lerobot.motors.calibration_gui import RangeFinderGUI
 from lerobot.motors.feetech import (
     FeetechMotorsBus,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/hope_jr/hope_jr_hand.py

@@ -19,12 +19,12 @@ import time
 from functools import cached_property
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorNormMode
 from lerobot.motors.calibration_gui import RangeFinderGUI
 from lerobot.motors.feetech import (
     FeetechMotorsBus,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/koch_follower/koch_follower.py

@@ -19,12 +19,12 @@ import time
 from functools import cached_property
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.dynamixel import (
     DynamixelMotorsBus,
     OperatingMode,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/lekiwi/config_lekiwi.py

@@ -23,10 +23,20 @@ from ..config import RobotConfig
 def lekiwi_cameras_config() -> dict[str, CameraConfig]:
     return {
         "front": OpenCVCameraConfig(
-            index_or_path="/dev/video0", fps=30, width=640, height=480, rotation=Cv2Rotation.ROTATE_180
+            index_or_path="/dev/video0",
+            fps=30,
+            width=640,
+            height=480,
+            fourcc="MJPG",
+            rotation=Cv2Rotation.ROTATE_180,
         ),
         "wrist": OpenCVCameraConfig(
-            index_or_path="/dev/video2", fps=30, width=480, height=640, rotation=Cv2Rotation.ROTATE_90
+            index_or_path="/dev/video2",
+            fps=30,
+            width=480,
+            height=640,
+            fourcc="MJPG",
+            rotation=Cv2Rotation.ROTATE_90,
         ),
     }
 

src/lerobot/robots/lekiwi/lekiwi.py

@@ -23,12 +23,12 @@ from typing import Any
 import numpy as np
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.feetech import (
     FeetechMotorsBus,
     OperatingMode,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/lekiwi/lekiwi_client.py

@@ -14,7 +14,6 @@
 
 # TODO(aliberts, Steven, Pepijn): use gRPC calls instead of zmq?
 
-import base64
 import json
 import logging
 from functools import cached_property
@@ -22,7 +21,7 @@ from functools import cached_property
 import cv2
 import numpy as np
 
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.constants import ACTION, OBS_STATE
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 from lerobot.utils.errors import DeviceNotConnectedError
@@ -134,7 +133,9 @@ class LeKiwiClient(Robot):
         self.zmq_observation_socket = self.zmq_context.socket(zmq.PULL)
         zmq_observations_locator = f"tcp://{self.remote_ip}:{self.port_zmq_observations}"
         self.zmq_observation_socket.connect(zmq_observations_locator)
-        self.zmq_observation_socket.setsockopt(zmq.CONFLATE, 1)
+        # CONFLATE does not support multipart messages; a small receive queue plus
+        # the existing drain-to-latest loop keeps newest-only semantics.
+        self.zmq_observation_socket.setsockopt(zmq.RCVHWM, 2)
 
         poller = zmq.Poller()
         poller.register(self.zmq_observation_socket, zmq.POLLIN)
@@ -147,8 +148,8 @@ class LeKiwiClient(Robot):
     def calibrate(self) -> None:
         pass
 
-    def _poll_and_get_latest_message(self) -> str | None:
+    def _poll_and_get_latest_message(self) -> list[bytes] | None:
-        """Polls the ZMQ socket for a limited time and returns the latest message string."""
+        """Polls the ZMQ socket for a limited time and returns the latest message's frames."""
         zmq = self._zmq
         poller = zmq.Poller()
         poller.register(self.zmq_observation_socket, zmq.POLLIN)
@@ -166,7 +167,7 @@ class LeKiwiClient(Robot):
         last_msg = None
         while True:
             try:
-                msg = self.zmq_observation_socket.recv_string(zmq.NOBLOCK)
+                msg = self.zmq_observation_socket.recv_multipart(zmq.NOBLOCK)
                 last_msg = msg
             except zmq.Again:
                 break
@@ -176,28 +177,27 @@ class LeKiwiClient(Robot):
 
         return last_msg
 
-    def _parse_observation_json(self, obs_string: str) -> RobotObservation | None:
+    def _parse_observation(self, frames: list[bytes]) -> RobotObservation | None:
-        """Parses the JSON observation string."""
+        """Parses a multipart observation: JSON header + one raw JPEG frame per camera."""
         try:
-            return json.loads(obs_string)
+            header = json.loads(frames[0])
-        except json.JSONDecodeError as e:
+            cam_names = header.pop("_cams")
-            logging.error(f"Error decoding JSON observation: {e}")
+            observation: RobotObservation = header
+            for cam_name, jpeg in zip(cam_names, frames[1:], strict=True):
+                observation[cam_name] = jpeg
+            return observation
+        except (json.JSONDecodeError, KeyError, ValueError) as e:
+            logging.error(f"Error decoding observation: {e}")
             return None
 
-    def _decode_image_from_b64(self, image_b64: str) -> np.ndarray | None:
+    def _decode_image(self, jpeg: bytes) -> np.ndarray | None:
-        """Decodes a base64 encoded image string to an OpenCV image."""
+        """Decodes a raw JPEG buffer to an OpenCV image."""
-        if not image_b64:
+        if not jpeg:
-            return None
-        try:
-            jpg_data = base64.b64decode(image_b64)
-            np_arr = np.frombuffer(jpg_data, dtype=np.uint8)
-            frame = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
-            if frame is None:
-                logging.warning("cv2.imdecode returned None for an image.")
-            return frame
-        except (TypeError, ValueError) as e:
-            logging.error(f"Error decoding base64 image data: {e}")
             return None
+        frame = cv2.imdecode(np.frombuffer(jpeg, dtype=np.uint8), cv2.IMREAD_COLOR)
+        if frame is None:
+            logging.warning("cv2.imdecode returned None for an image.")
+        return frame
 
     def _remote_state_from_obs(
         self, observation: RobotObservation
@@ -212,10 +212,10 @@ class LeKiwiClient(Robot):
 
         # Decode images
         current_frames: dict[str, np.ndarray] = {}
-        for cam_name, image_b64 in observation.items():
+        for cam_name, jpeg in observation.items():
             if cam_name not in self._cameras_ft:
                 continue
-            frame = self._decode_image_from_b64(image_b64)
+            frame = self._decode_image(jpeg)
             if frame is not None:
                 current_frames[cam_name] = frame
 
@@ -230,15 +230,15 @@ class LeKiwiClient(Robot):
         If no new data arrives or decoding fails, returns the last known values.
         """
 
-        # 1. Get the latest message string from the socket
+        # 1. Get the latest message's frames from the socket
-        latest_message_str = self._poll_and_get_latest_message()
+        latest_frames = self._poll_and_get_latest_message()
 
         # 2. If no message, return cached data
-        if latest_message_str is None:
+        if latest_frames is None:
             return self.last_frames, self.last_remote_state
 
-        # 3. Parse the JSON message
+        # 3. Parse the multipart message
-        observation = self._parse_observation_json(latest_message_str)
+        observation = self._parse_observation(latest_frames)
 
         # 4. If JSON parsing failed, return cached data
         if observation is None:

src/lerobot/robots/lekiwi/lekiwi_host.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import base64
 import json
 import logging
 import time
@@ -44,7 +43,9 @@ class LeKiwiHost:
         self.zmq_cmd_socket.bind(f"tcp://*:{config.port_zmq_cmd}")
 
         self.zmq_observation_socket = self.zmq_context.socket(zmq.PUSH)
-        self.zmq_observation_socket.setsockopt(zmq.CONFLATE, 1)
+        # CONFLATE does not support multipart messages; a 2-deep send queue keeps
+        # near-latest-only semantics and sheds stale observations during stalls.
+        self.zmq_observation_socket.setsockopt(zmq.SNDHWM, 2)
         self.zmq_observation_socket.bind(f"tcp://*:{config.port_zmq_observations}")
 
         self.connection_time_s = config.connection_time_s
@@ -99,19 +100,23 @@ def main(cfg: LeKiwiServerConfig):
 
             last_observation = robot.get_observation()
 
-            # Encode ndarrays to base64 strings
+            # Send one multipart message: a JSON header frame (state + camera
-            for cam_key, _ in robot.cameras.items():
+            # order) followed by one raw JPEG frame per camera. Raw JPEG avoids
-                ret, buffer = cv2.imencode(
+            # the 33% base64 inflation of embedding binary data in JSON.
-                    ".jpg", last_observation[cam_key], [int(cv2.IMWRITE_JPEG_QUALITY), 90]
+            cam_keys = list(robot.cameras.keys())
+            jpeg_frames = []
+            for cam_key in cam_keys:
+                ret, jpeg = cv2.imencode(
+                    ".jpg", last_observation.pop(cam_key), [int(cv2.IMWRITE_JPEG_QUALITY), 90]
                 )
-                if ret:
+                jpeg_frames.append(jpeg if ret else b"")
-                    last_observation[cam_key] = base64.b64encode(buffer).decode("utf-8")
+            header = {"_cams": cam_keys, **last_observation}
-                else:
-                    last_observation[cam_key] = ""
 
             # Send the observation to the remote agent
             try:
-                host.zmq_observation_socket.send_string(json.dumps(last_observation), flags=zmq.NOBLOCK)
+                host.zmq_observation_socket.send_multipart(
+                    [json.dumps(header).encode()] + jpeg_frames, flags=zmq.NOBLOCK
+                )
             except zmq.Again:
                 logging.info("Dropping observation, no client connected")
 

src/lerobot/robots/omx_follower/omx_follower.py

@@ -19,13 +19,13 @@ import time
 from functools import cached_property
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.dynamixel import (
     DriveMode,
     DynamixelMotorsBus,
     OperatingMode,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/openarm_follower/openarm_follower.py

@@ -20,9 +20,9 @@ from functools import cached_property
 from typing import Any
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.damiao import DamiaoMotorsBus
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/reachy2/robot_reachy2.py

@@ -19,7 +19,7 @@ import time
 from typing import TYPE_CHECKING, Any
 
 from lerobot.cameras import make_cameras_from_configs
-from lerobot.types import RobotAction, RobotObservation
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.utils.import_utils import _reachy2_sdk_available, require_package
 
 from ..robot import Robot

src/lerobot/robots/rebot_b601_follower/rebot_b601_follower.py

@@ -21,8 +21,8 @@ from functools import cached_property
 from typing import TYPE_CHECKING
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import MotorCalibration
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 from lerobot.utils.import_utils import _motorbridge_available, require_package
 

src/lerobot/robots/robot.py

@@ -18,8 +18,8 @@ from pathlib import Path
 
 import draccus
 
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import MotorCalibration
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.constants import HF_LEROBOT_CALIBRATION, ROBOTS
 
 from .config import RobotConfig

src/lerobot/robots/so_follower/so_follower.py

@@ -19,12 +19,12 @@ import time
 from functools import cached_property
 
 from lerobot.cameras import make_cameras_from_configs
+from lerobot.lerobot_types import RobotAction, RobotObservation
 from lerobot.motors import Motor, MotorCalibration, MotorNormMode
 from lerobot.motors.feetech import (
     FeetechMotorsBus,
     OperatingMode,
 )
-from lerobot.types import RobotAction, RobotObservation
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
 
 from ..robot import Robot

src/lerobot/robots/unitree_g1/config_unitree_g1.py

@@ -68,10 +68,6 @@ class UnitreeG1Config(RobotConfig):
     # Compensates for gravity on the unitree's arms using the arm ik solver
     gravity_compensation: bool = False
 
-    # Locomotion controller class name, e.g. "GrootLocomotionController",
+    # Lower-body controller class name, e.g. "GrootLocomotionController" or
-    # "HolosomaLocomotionController", or "SonicWholeBodyController". None disables it.
+    # "HolosomaLocomotionController". None disables it.
-    # Selecting "SonicWholeBodyController" implicitly switches the robot to the 64-D
-    # latent-token action/observation interface (``motion_token.{i}.pos`` action and a
-    # ``motion_token_state.{i}.pos`` state echo) so ``lerobot-rollout`` can drive a
-    # policy trained on SONIC motion tokens (e.g. nepyope/sonic_walk).
     controller: str | None = None

src/lerobot/robots/unitree_g1/controllers/__init__.py

@@ -1,27 +0,0 @@
-#!/usr/bin/env python
-
-# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Unitree G1 locomotion controllers (Groot, Holosoma, SONIC)."""
-
-from .gr00t_locomotion import GrootLocomotionController
-from .holosoma_locomotion import HolosomaLocomotionController
-from .sonic_whole_body import SonicWholeBodyController
-
-__all__ = [
-    "GrootLocomotionController",
-    "HolosomaLocomotionController",
-    "SonicWholeBodyController",
-]

src/lerobot/robots/unitree_g1/controllers/sonic_whole_body.py

@@ -1,378 +0,0 @@
-#!/usr/bin/env python
-
-# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""SONIC decoder whole-body controller for the Unitree G1 (token-only).
-
-Pure-Python/ONNX re-implementation of the *decode* half of NVIDIA's SONIC deploy stack.
-The encoder is intentionally absent: a token-output VLA (e.g. ``nepyope/sonic_walk``)
-supplies the 64-D latent ``motion_token`` directly each tick, and the SONIC **decoder**
-maps ``token + recent proprioception history`` to a residual action that is scaled and
-added onto the standing pose (``default_angles``) to produce 50 Hz joint-position targets
-for the robot's PD controller.
-
-Index spaces: joints exist in two orderings — **IsaacLab** (policy/training order) and
-**MuJoCo** (deploy order). ``ISAACLAB_TO_MUJOCO`` / ``MUJOCO_TO_ISAACLAB`` (in g1_utils)
-convert between them. Quaternions are scalar-first ``(w, x, y, z)``.
-"""
-
-from __future__ import annotations
-
-import json
-import logging
-
-import numpy as np
-import onnx
-import onnxruntime as ort
-from huggingface_hub import hf_hub_download
-
-from ..g1_utils import (
-    ISAACLAB_TO_MUJOCO,
-    MUJOCO_TO_ISAACLAB,
-    G1_29_JointIndex,
-    get_gravity_orientation,
-)
-from ..unitree_g1 import lowstate_to_obs
-
-logger = logging.getLogger(__name__)
-
-# ── Constants (hardware-validated; see the NVIDIA SONIC deploy reference) ──────
-CONTROL_DT = 0.02  # 50 Hz control period (s)
-TOKEN_DIM = 64  # decoder latent size
-
-# SONIC decoder checkpoint: NVIDIA's decoder ONNX re-packaged with its deploy constants
-# (kp/kd PD gains, the standing pose default_angles, and the residual action_scale) embedded
-# in the ONNX metadata; see upload_sonic_decoder.py for provisioning. The runtime loads the
-# model *and* all of these straight from the checkpoint (the Holosoma convention), so no
-# motor-physics math happens at deploy time.
-DEFAULT_SONIC_REPO_ID = "lerobot/sonic_decoder"
-DECODER_FILENAME = "model_decoder.onnx"
-DECODER_INPUT_DIM = 994  # token(64) + 10-frame proprio history + gravity
-
-
-def load_sonic_decoder(repo_id: str = DEFAULT_SONIC_REPO_ID):
-    """Load the SONIC decoder ONNX and its baked-in deploy constants from the checkpoint.
-
-    Returns ``(decoder_session, kp, kd, default_angles, action_scale, neutral_token)``. The
-    gains/pose/scale are (29,) float32 in IsaacLab joint order and ``neutral_token`` is the
-    (64,) float32 idle latent -- all read from the ONNX ``metadata_props`` rather than
-    recomputed/hardcoded at deploy time (mirrors ``holosoma_locomotion.load_policy``).
-    """
-    decoder_path = hf_hub_download(repo_id=repo_id, filename=DECODER_FILENAME)
-    so = ort.SessionOptions()
-    so.log_severity_level = 3  # quiet ORT logs
-    session = ort.InferenceSession(decoder_path, sess_options=so)
-    dec_dim = int(session.get_inputs()[0].shape[1])
-    if dec_dim != DECODER_INPUT_DIM:
-        raise RuntimeError(f"Unexpected decoder input dim {dec_dim} (expected {DECODER_INPUT_DIM})")
-
-    meta = {p.key: p.value for p in onnx.load(decoder_path, load_external_data=False).metadata_props}
-    required = ("kp", "kd", "default_angles", "action_scale", "neutral_token")
-    missing = [k for k in required if k not in meta]
-    if missing:
-        raise ValueError(
-            f"SONIC decoder ONNX at {repo_id} is missing metadata {missing}; "
-            "re-run upload_sonic_decoder.py to (re)provision the checkpoint."
-        )
-    arr = {k: np.array(json.loads(meta[k]), dtype=np.float32) for k in required}
-    logger.info("Loaded SONIC deploy constants from %s (%d joints)", repo_id, len(arr["kp"]))
-    return session, arr["kp"], arr["kd"], arr["default_angles"], arr["action_scale"], arr["neutral_token"]
-
-
-def _to_mujoco(a):
-    """Apply the ``MUJOCO_TO_ISAACLAB`` gather to a 29-vector (deploy-order reorder).
-
-    NOTE: this returns ``a[MUJOCO_TO_ISAACLAB]``. The ``_mj`` suffixes and the exact
-    permutation direction are a fixed convention validated against the deployed SONIC ONNX
-    policy (the decoder consumes vectors in this order). Do not "correct" the table or
-    rename toward the opposite direction without re-validating on hardware.
-    """
-    return a[MUJOCO_TO_ISAACLAB]
-
-
-# Action-feature prefix for the latent-token interface (see _extract_token_from_action).
-TOKEN_ACTION_PREFIX = "motion_token"  # nosec B105 - feature-key prefix, not a secret
-# Proprio-state prefix for the token interface: the robot echoes the last commanded token
-# here so ``lerobot-rollout`` aggregates it into a 64-D ``observation.state``.
-TOKEN_STATE_PREFIX = "motion_token_state"  # nosec B105 - feature-key prefix, not a secret
-
-
-def token_action_key(i: int) -> str:
-    """Action-dict key for the i-th component of the 64-D SONIC latent token.
-
-    The ``.pos`` suffix is required so the value flows through ``lerobot-rollout``, which
-    only routes ``.pos`` scalar features onto the policy action vector.
-    """
-    return f"{TOKEN_ACTION_PREFIX}.{i}.pos"
-
-
-def token_state_key(i: int) -> str:
-    """Observation key for the i-th component of the 64-D SONIC latent token state."""
-    return f"{TOKEN_STATE_PREFIX}.{i}.pos"
-
-
-# Startup blend duration: over the first control ticks, linearly interpolate every joint
-# from the robot's initial measured pose into the policy's commanded target, so control
-# eases in without a snap on the first command.
-INIT_RAMP_S = 3.0
-
-
-def _extract_token_from_action(action: dict | None) -> np.ndarray | None:
-    """Reassemble a dense (64,) latent token from ``motion_token.{i}`` keys, or None.
-
-    The token-only interface: the caller supplies the 64-D encoder latent directly (e.g. a
-    token-output VLA's action), which the decoder consumes with the encoder bypassed.
-    Requires the full dense token; a partial one is ignored (returns None).
-    """
-    if not action:
-        return None
-    keys = [token_action_key(i) for i in range(TOKEN_DIM)]
-    if any(key not in action for key in keys):
-        return None
-    return np.fromiter((float(action[key]) for key in keys), dtype=np.float32, count=TOKEN_DIM)
-
-
-class SonicDecoder:
-    """Runs the SONIC decoder ONNX model and owns the proprioception history.
-
-    Each tick it appends the latest robot state to 10-frame history buffers, then maps the
-    supplied 64-D ``token`` + that history to a residual action added onto ``default_angles``.
-    The encoder is bypassed entirely (token supplied by the policy). ``default_angles`` and
-    ``action_scale`` are (29,) float32 in IsaacLab order, loaded from the checkpoint.
-    """
-
-    def __init__(self, decoder, default_angles, action_scale):
-        self.decoder = decoder
-        self.decoder_input = decoder.get_inputs()[0].name
-        self.default_angles = np.asarray(default_angles, np.float32)
-        self.action_scale = np.asarray(action_scale, np.float32)
-        self.default_angles_mj = _to_mujoco(self.default_angles)
-        self.token = np.zeros(TOKEN_DIM, np.float32)
-        self.last_action_mj = np.zeros(29, np.float32)
-        self.h_q_mj = [np.zeros(29, np.float32)] * 10
-        self.h_dq_mj = [np.zeros(29, np.float32)] * 10
-        self.h_ang = [np.zeros(3, np.float32)] * 10
-        self.h_act_mj = [np.zeros(29, np.float32)] * 10
-        self.h_quat = [np.array([1, 0, 0, 0], np.float32)] * 10
-
-    def reset(self):
-        """Clear the token and 10-frame proprioception history.
-
-        ``UnitreeG1.reset()`` relies on this so the first decoder outputs of a new episode
-        are not contaminated by the previous episode's state.
-        """
-        self.token = np.zeros(TOKEN_DIM, np.float32)
-        self.last_action_mj = np.zeros(29, np.float32)
-        self.h_q_mj = [np.zeros(29, np.float32)] * 10
-        self.h_dq_mj = [np.zeros(29, np.float32)] * 10
-        self.h_ang = [np.zeros(3, np.float32)] * 10
-        self.h_act_mj = [np.zeros(29, np.float32)] * 10
-        self.h_quat = [np.array([1, 0, 0, 0], np.float32)] * 10
-
-    def update_history(self, q, dq, ang, quat):
-        """Push the latest proprioception (pos/vel/gyro/orientation) into the 10-frame buffers."""
-        quat = quat / (np.linalg.norm(quat) + 1e-8)
-        q_mj = _to_mujoco(q)
-        dq_mj = _to_mujoco(dq)
-        self.h_q_mj = [q_mj - self.default_angles_mj] + self.h_q_mj[:-1]
-        self.h_dq_mj = [dq_mj] + self.h_dq_mj[:-1]
-        self.h_ang = [ang.copy()] + self.h_ang[:-1]
-        self.h_act_mj = [self.last_action_mj.copy()] + self.h_act_mj[:-1]
-        self.h_quat = [quat.copy()] + self.h_quat[:-1]
-
-    def build_decoder_obs(self):
-        """Assemble the 994-D decoder input: token + 10-frame proprioception history + gravity."""
-        obs = np.zeros(994, np.float32)
-        off = 0
-        obs[off : off + 64] = self.token
-        off += 64
-        for h, sz in [
-            (list(reversed(self.h_ang)), 3),
-            (list(reversed(self.h_q_mj)), 29),
-            (list(reversed(self.h_dq_mj)), 29),
-            (list(reversed(self.h_act_mj)), 29),
-        ]:
-            for f in range(10):
-                obs[off : off + sz] = h[f]
-                off += sz
-        for q in reversed(self.h_quat):
-            obs[off : off + 3] = get_gravity_orientation(q)
-            off += 3
-        assert off == 994, f"Decoder obs mismatch: {off}"
-        return obs
-
-    def step(self, robot_obs, token, debug=False):
-        """One control tick: read robot obs, decode the supplied token -> joint targets.
-
-        Args:
-            robot_obs: dict with ``<joint>.q``/``.dq`` and ``imu.*`` fields.
-            token: 64-D latent supplied by the policy (encoder bypassed).
-            debug: log action/delta norms.
-
-        Returns:
-            dict of ``<joint>.q`` target positions (rad) in IsaacLab joint order.
-        """
-        self.token = np.asarray(token, np.float32)
-        jnames = [m.name for m in G1_29_JointIndex]
-        q = np.array(
-            [
-                robot_obs.get(f"{n}.q", self.default_angles[m.value])
-                for m, n in zip(G1_29_JointIndex, jnames, strict=False)
-            ],
-            np.float32,
-        )
-        dq = np.array([robot_obs.get(f"{n}.dq", 0.0) for n in jnames], np.float32)
-        quat = np.array(
-            [
-                robot_obs.get("imu.quat.w", 1),
-                robot_obs.get("imu.quat.x", 0),
-                robot_obs.get("imu.quat.y", 0),
-                robot_obs.get("imu.quat.z", 0),
-            ],
-            np.float32,
-        )
-        ang = np.array([robot_obs.get(f"imu.gyro.{a}", 0) for a in "xyz"], np.float32)
-        self.update_history(q, dq, ang, quat)
-        action_mj = (
-            self.decoder.run(None, {self.decoder_input: self.build_decoder_obs().reshape(1, -1)})[0]
-            .squeeze()
-            .astype(np.float32)
-        )
-        self.last_action_mj = action_mj.copy()
-        target = self.default_angles + action_mj[ISAACLAB_TO_MUJOCO] * self.action_scale
-        if debug:
-            delta = target - q
-            logger.debug(
-                "token_norm=%.4f action_norm=%.4f delta_max=%.4f delta_rms=%.4f",
-                np.linalg.norm(self.token),
-                np.linalg.norm(action_mj),
-                np.max(np.abs(delta)),
-                np.sqrt(np.mean(delta**2)),
-            )
-        return {f"{m.name}.q": float(target[m.value]) for m in G1_29_JointIndex}
-
-
-class SonicRuntime:
-    """Loads the SONIC decoder ONNX model and owns the decode controller.
-
-    Token-only deploy: the encoder is bypassed; each tick the decoder consumes a 64-D
-    latent token supplied directly by the policy.
-    """
-
-    def __init__(self):
-        decoder_sess, self.kp, self.kd, default_angles, action_scale, neutral_token = load_sonic_decoder()
-        self.default_angles = default_angles
-        self.neutral_token = neutral_token
-        self.controller = SonicDecoder(decoder_sess, default_angles, action_scale)
-
-    @property
-    def pipeline(self):
-        return self.controller
-
-    def reset(self):
-        self.controller.reset()
-
-    def shutdown(self):
-        pass
-
-
-class SonicWholeBodyController:
-    """Full-body SONIC controller for UnitreeG1's background controller thread."""
-
-    control_dt = CONTROL_DT
-    full_body = True
-
-    def __init__(self):
-        logger.info("Loading SONIC whole-body controller...")
-        self._runtime = SonicRuntime()
-        self.kp = self._runtime.kp
-        self.kd = self._runtime.kd
-        self.controller = self._runtime.controller
-        self._default_angles = self._runtime.default_angles
-        self._neutral_token = self._runtime.neutral_token
-
-        # Startup blend: ease from the robot's initial pose into the first commanded policy
-        # targets over INIT_RAMP_S (captured on the first control tick).
-        self._init_ramp_steps = max(1, round(INIT_RAMP_S / CONTROL_DT))
-        self._init_step = 0
-        self._start_pose: dict[str, float] = {}
-
-        # Token-interface state. ``token_mode`` is set True by the robot whenever a SONIC
-        # whole-body controller is selected (token-driven deploy): the controller then holds a
-        # stable *neutral* token until the first real token arrives, and afterwards holds the
-        # *last* token received between ticks (the async controller runs ~50 Hz while a token
-        # VLA streams ~30 Hz). This lives here (not in the entry-point script) so it applies
-        # uniformly to run_g1_server, lerobot-rollout and the sim replays.
-        self.token_mode = False
-        self._last_token: np.ndarray | None = None
-
-        logger.info("SONIC ready (decoder, 64-D token command path)")
-
-    def _startup_blend(self, obs: dict, out: dict) -> dict:
-        """Ease into policy control at startup: for the first ``INIT_RAMP_S`` seconds,
-        interpolate between the robot's pose captured on the first tick and the policy's
-        live commanded target, so the handoff has no snap.
-
-        ``out`` is the policy's ``<joint>.q`` target dict for this tick; the blend ratio
-        climbs 0->1 over the ramp, after which the raw policy target passes through.
-        """
-        if self._init_step >= self._init_ramp_steps or not out:
-            return out
-        if self._init_step == 0:
-            # Capture the robot's actual pose as the interpolation start point.
-            self._start_pose = {
-                f"{m.name}.q": float(obs.get(f"{m.name}.q", self._default_angles[m.value]))
-                for m in G1_29_JointIndex
-            }
-        self._init_step += 1
-        ratio = min(1.0, self._init_step / self._init_ramp_steps)
-        blended = {
-            k: self._start_pose.get(k, float(tgt)) * (1.0 - ratio) + float(tgt) * ratio
-            for k, tgt in out.items()
-        }
-        if self._init_step >= self._init_ramp_steps:
-            logger.info("SONIC startup blend complete -> full policy control")
-        return blended
-
-    def run_step(self, action: dict, lowstate) -> dict:
-        if lowstate is None:
-            return {}
-        obs = lowstate_to_obs(lowstate)
-
-        # Token-only interface (token-output VLA): a dense 64-D ``motion_token.{i}`` command
-        # is decoded directly, encoder bypassed.
-        token = _extract_token_from_action(action)
-        if token is not None:
-            self._last_token = token
-        elif self._last_token is None and self.token_mode:
-            # Token-driven deploy, but no token has arrived yet: hold the checkpoint's neutral
-            # token, which the decoder maps to a stable, natural standing pose.
-            self._last_token = self._neutral_token.copy()
-        if self._last_token is None:
-            # No token yet and not in token_mode: hold (keep last target).
-            return {}
-        # Either a fresh token this tick or the last one received (held between the ~30 Hz
-        # token stream and the ~50 Hz control loop).
-        return self._startup_blend(obs, self.controller.step(obs, self._last_token))
-
-    def reset(self):
-        self._runtime.reset()
-        self._init_step = 0  # re-run the startup blend after a reset
-        self._start_pose = {}
-        # Drop the held token so token_mode re-seeds the neutral token after a reset.
-        self._last_token = None
-
-    def shutdown(self):
-        self._runtime.shutdown()

src/lerobot/robots/unitree_g1/g1_utils.py

@@ -23,47 +23,6 @@ import numpy as np
 
 NUM_MOTORS = 29
 
-# Joint-order permutations between the two 29-DoF layouts used across the G1 stack:
-# IsaacLab (policy/training order) and MuJoCo (deploy order). ``a[ISAACLAB_TO_MUJOCO]``
-# reorders an IsaacLab-ordered vector into MuJoCo order, and vice-versa.
-ISAACLAB_TO_MUJOCO = np.array(
-    [
-        0,
-        3,
-        6,
-        9,
-        13,
-        17,
-        1,
-        4,
-        7,
-        10,
-        14,
-        18,
-        2,
-        5,
-        8,
-        11,
-        15,
-        19,
-        21,
-        23,
-        25,
-        27,
-        12,
-        16,
-        20,
-        22,
-        24,
-        26,
-        28,
-    ],
-    dtype=np.int32,
-)
-# The two orderings are inverses of each other, so derive one from the other (argsort) to
-# guarantee they can never drift out of sync.
-MUJOCO_TO_ISAACLAB = np.argsort(ISAACLAB_TO_MUJOCO).astype(np.int32)
-
 REMOTE_AXES = ("remote.lx", "remote.ly", "remote.rx", "remote.ry")
 REMOTE_BUTTONS = tuple(f"remote.button.{i}" for i in range(16))
 REMOTE_KEYS = REMOTE_AXES + REMOTE_BUTTONS
@@ -109,9 +68,8 @@ def make_locomotion_controller(name: str | None):
     if name is None:
         return None
     controllers = {
-        "GrootLocomotionController": "lerobot.robots.unitree_g1.controllers.gr00t_locomotion",
+        "GrootLocomotionController": "lerobot.robots.unitree_g1.gr00t_locomotion",
-        "HolosomaLocomotionController": "lerobot.robots.unitree_g1.controllers.holosoma_locomotion",
+        "HolosomaLocomotionController": "lerobot.robots.unitree_g1.holosoma_locomotion",
-        "SonicWholeBodyController": "lerobot.robots.unitree_g1.controllers.sonic_whole_body",
     }
     module_path = controllers.get(name)
     if module_path is None: