refactor(camera): apply feedback

Address PR #3220 review:
- Wrap set_option calls; re-raise ValueError with option name, value,
  and sensor.get_option_range() diagnostics on out-of-range values.
- Add unit tests for _get_color_sensor (RGB Camera, D405 Stereo Module
  fallback, diagnostic error) and _configure_sensor_options (no-op,
  all values, unsupported warns, partial config, out-of-range raise).

docs/source/cameras.mdx

@@ -136,6 +136,10 @@ config = RealSenseCameraConfig(
     height=480,
     color_mode=ColorMode.RGB,
     use_depth=True,
+    # Optional fixed color controls. Omit them to leave the current sensor settings unchanged.
+    exposure=120,
+    gain=64,
+    white_balance=4600,
     rotation=Cv2Rotation.NO_ROTATION
 )
 
@@ -154,6 +158,15 @@ finally:
 ```
 <!-- prettier-ignore-end -->
 
+Manual color controls disable the corresponding automatic exposure or white-balance mode. Their
+supported ranges vary by camera model; an invalid value raises an error at connection time that
+includes the range reported by the sensor. Requesting an unsupported control also raises an error.
+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
+exposure or gain also affects the depth stream.
+
 </hfoption>
 </hfoptions>
 

src/lerobot/cameras/realsense/camera_realsense.py

@@ -121,6 +121,9 @@ class RealSenseCamera(Camera):
 
         self.config = config
 
+        self.width: int | None = config.width
+        self.height: int | None = config.height
+
         if config.serial_number_or_name.isdigit():
             self.serial_number = config.serial_number_or_name
         else:
@@ -131,6 +134,9 @@ class RealSenseCamera(Camera):
         self.use_rgb = config.use_rgb
         self.use_depth = config.use_depth
         self.warmup_s = config.warmup_s
+        self.exposure: int | None = config.exposure
+        self.gain: int | None = config.gain
+        self.white_balance: int | None = config.white_balance
 
         self.rs_pipeline: rs.pipeline | None = None
         self.rs_profile: rs.pipeline_profile | None = None
@@ -172,7 +178,8 @@ class RealSenseCamera(Camera):
 
         Raises:
             DeviceAlreadyConnectedError: If the camera is already connected.
-            ValueError: If the configuration is invalid (e.g., missing serial/name, name not unique).
+            ValueError: If the configuration is invalid, a requested sensor option is unsupported,
+                or a requested sensor value is invalid.
             ConnectionError: If the camera is found but fails to start the pipeline or no RealSense devices are detected at all.
             RuntimeError: If the pipeline starts but fails to apply requested settings.
         """
@@ -190,22 +197,30 @@ class RealSenseCamera(Camera):
                 f"Failed to open {self}.Run `lerobot-find-cameras realsense` to find available cameras."
             ) from e
 
-        self._configure_capture_settings()
-        self._start_read_thread()
+        try:
+            self._configure_capture_settings()
+            self._configure_sensor_options()
+            self._start_read_thread()
 
-        # NOTE(Steven/Caroline): Enforcing at least one second of warmup as RS cameras need a bit of time before the first read. If we don't wait, the first read from the warmup will raise.
-        self.warmup_s = max(self.warmup_s, 1)
+            # NOTE(Steven/Caroline): Enforcing at least one second of warmup as RS cameras need a bit of time before the first read. If we don't wait, the first read from the warmup will raise.
+            self.warmup_s = max(self.warmup_s, 1)
 
-        warmup_read = self.async_read if self.use_rgb else self.async_read_depth
-        start_time = time.time()
-        while time.time() - start_time < self.warmup_s:
-            warmup_read(timeout_ms=self.warmup_s * 1000)
-            time.sleep(0.1)
-        with self.frame_lock:
-            if (self.use_rgb and self.latest_color_frame is None) or (
-                self.use_depth and self.latest_depth_frame is None
-            ):
-                raise ConnectionError(f"{self} failed to capture frames during warmup.")
+            warmup_read = self.async_read if self.use_rgb else self.async_read_depth
+            start_time = time.time()
+            while time.time() - start_time < self.warmup_s:
+                warmup_read(timeout_ms=self.warmup_s * 1000)
+                time.sleep(0.1)
+            with self.frame_lock:
+                if (self.use_rgb and self.latest_color_frame is None) or (
+                    self.use_depth and self.latest_depth_frame is None
+                ):
+                    raise ConnectionError(f"{self} failed to capture frames during warmup.")
+        except Exception:
+            try:
+                self._cleanup_connection()
+            except Exception:
+                logger.exception(f"Failed to clean up {self} after a connection error.")
+            raise
 
         logger.info(f"{self} connected.")
 
@@ -339,6 +354,111 @@ class RealSenseCamera(Camera):
         self.new_frame_event.clear()
         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.
+
+        Most RealSense cameras expose "RGB Camera" for color. The D405 has no
+        separate RGB module — its color stream comes from "Stereo Module".
+        We try RGB Camera first, then fall back to Stereo Module.
+        """
+        if self.rs_profile is None:
+            raise RuntimeError(f"{self}: rs_profile must be initialized before use.")
+
+        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 name in sensors:
+                return sensors[name]
+
+        available = list(sensors.keys())
+        raise RuntimeError(f"{self}: no color sensor found. 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."""
+        try:
+            sensor.set_option(option, value)
+        except Exception as e:
+            range_info = ""
+            try:
+                option_range = sensor.get_option_range(option)
+                range_info = (
+                    f" (supported range: min={option_range.min}, max={option_range.max}, "
+                    f"step={option_range.step}, default={option_range.default})"
+                )
+            except Exception:
+                range_info = " (option range unavailable)"
+            raise ValueError(
+                f"{self}: failed to set {label} to {value}{range_info}. Original error: {e}"
+            ) from e
+
+    def _configure_sensor_options(self) -> None:
+        """Applies manual sensor options (exposure, gain, white balance) to the color sensor.
+
+        When exposure or gain is set, auto-exposure is disabled first. When white_balance
+        is set, auto white balance is disabled first. An omitted option is left unchanged,
+        and configuration is skipped entirely if all options are omitted.
+
+        Raises:
+            ValueError: If the sensor does not support a requested option or a requested
+                value is invalid. Invalid-value errors include the option name, requested
+                value, and supported range when available.
+        """
+        if self.exposure is None and self.gain is None and self.white_balance is None:
+            return
+
+        color_sensor = self._get_color_sensor()
+
+        requested_options = (
+            (rs.option.exposure, self.exposure, "exposure"),
+            (rs.option.gain, self.gain, "gain"),
+            (rs.option.white_balance, self.white_balance, "white balance"),
+        )
+        unsupported_options = [
+            label
+            for option, value, label in requested_options
+            if value is not None and not color_sensor.supports(option)
+        ]
+        if unsupported_options:
+            raise ValueError(
+                f"{self}: color sensor does not support requested manual options: {unsupported_options}."
+            )
+
+        manual_exposure_requested = self.exposure is not None or self.gain is not None
+        if manual_exposure_requested:
+            if color_sensor.supports(rs.option.enable_auto_exposure):
+                self._set_sensor_option(color_sensor, rs.option.enable_auto_exposure, 0, "auto-exposure")
+                logger.info(f"{self} auto-exposure disabled.")
+            else:
+                logger.warning(
+                    f"{self} sensor does not support disabling auto-exposure; "
+                    "applying manual exposure/gain directly."
+                )
+
+        if self.exposure is not None:
+            self._set_sensor_option(color_sensor, rs.option.exposure, self.exposure, "exposure")
+            logger.info(f"{self} exposure set to {self.exposure}.")
+
+        if self.gain is not None:
+            self._set_sensor_option(color_sensor, rs.option.gain, self.gain, "gain")
+            logger.info(f"{self} gain set to {self.gain}.")
+
+        if self.white_balance is not None:
+            if color_sensor.supports(rs.option.enable_auto_white_balance):
+                self._set_sensor_option(
+                    color_sensor, rs.option.enable_auto_white_balance, 0, "auto white balance"
+                )
+                logger.info(f"{self} auto white balance disabled.")
+            else:
+                logger.warning(
+                    f"{self} sensor does not support disabling auto white balance; "
+                    "applying manual white balance directly."
+                )
+            self._set_sensor_option(
+                color_sensor, rs.option.white_balance, self.white_balance, "white balance"
+            )
+            logger.info(f"{self} white balance set to {self.white_balance}.")
+
     @check_if_not_connected
     def read_depth(self, timeout_ms: int = 200) -> NDArray[Any]:
         """
@@ -684,13 +804,17 @@ class RealSenseCamera(Camera):
                 f"Attempted to disconnect {self}, but it appears already disconnected."
             )
 
+        self._cleanup_connection()
+        logger.info(f"{self} disconnected.")
+
+    def _cleanup_connection(self) -> None:
+        """Release connection resources and reset state after disconnect or failed connect."""
         if self.thread is not None:
             self._stop_read_thread()
 
-        if self.rs_pipeline is not None:
-            self.rs_pipeline.stop()
-            self.rs_pipeline = None
-            self.rs_profile = None
+        pipeline = self.rs_pipeline
+        self.rs_pipeline = None
+        self.rs_profile = None
 
         with self.frame_lock:
             self.latest_color_frame = None
@@ -698,4 +822,5 @@ class RealSenseCamera(Camera):
             self.latest_timestamp = None
             self.new_frame_event.clear()
 
-        logger.info(f"{self} disconnected.")
+        if pipeline is not None:
+            pipeline.stop()

src/lerobot/cameras/realsense/configuration_realsense.py

@@ -46,6 +46,17 @@ class RealSenseCameraConfig(CameraConfig):
         use_depth: Whether to enable depth stream. Defaults to False.
         rotation: Image rotation setting (0°, 90°, 180°, or 270°). Defaults to no rotation.
         warmup_s: Time reading frames before returning from connect (in seconds)
+        exposure: Manual exposure value for the color sensor. When set, auto-exposure is
+            disabled and this fixed value is used. Valid ranges are camera-model specific
+            and reported if the value is rejected. Defaults to None (leave unchanged).
+        gain: Manual gain value for the color sensor. When set, auto-exposure is disabled
+            and this fixed gain is used, which also freezes exposure at its current value
+            when no exposure is configured. Valid ranges are camera-model specific and
+            reported if the value is rejected. Defaults to None (leave unchanged).
+        white_balance: Manual white balance value for the color sensor. When set, auto
+            white balance is disabled and this fixed value is used. Valid ranges are
+            camera-model specific and reported if the value is rejected. Defaults to None
+            (leave unchanged).
 
     Note:
         - Either name or serial_number must be specified.
@@ -61,6 +72,9 @@ class RealSenseCameraConfig(CameraConfig):
     use_depth: bool = False
     rotation: Cv2Rotation = Cv2Rotation.NO_ROTATION
     warmup_s: int = 1
+    exposure: int | None = None
+    gain: int | None = None
+    white_balance: int | None = None
 
     def __post_init__(self) -> None:
         self.color_mode = ColorMode(self.color_mode)
@@ -69,6 +83,18 @@ class RealSenseCameraConfig(CameraConfig):
         if not self.use_rgb and not self.use_depth:
             raise ValueError("At least one of `use_rgb` or `use_depth` must be enabled.")
 
+        manual_color_options = {
+            "exposure": self.exposure,
+            "gain": self.gain,
+            "white_balance": self.white_balance,
+        }
+        configured_color_options = [name for name, value in manual_color_options.items() if value is not None]
+        if configured_color_options and not self.use_rgb:
+            raise ValueError(
+                "Manual color sensor options require `use_rgb=True`. "
+                f"Configured options: {configured_color_options}."
+            )
+
         values = (self.fps, self.width, self.height)
         if any(v is not None for v in values) and any(v is None for v in values):
             raise ValueError(

src/lerobot/configs/train.py

@@ -14,7 +14,6 @@
 import builtins
 import datetime as dt
 import json
-import multiprocessing
 import os
 import tempfile
 from dataclasses import dataclass, field
@@ -102,12 +101,6 @@ class TrainPipelineConfig(HubMixin):
     batch_size: int = 8
     prefetch_factor: int = 4
     persistent_workers: bool = True
-    # DataLoader worker start method. "spawn" is safer than "fork" with
-    # non-fork-safe libs (PyAV / torchcodec / ffmpeg), but adds some
-    # worker-startup time per run since workers re-import modules instead
-    # of inheriting parent state. Override with `--dataloader_multiprocessing_context=fork`
-    # when appropriate, or set it to `null` to use Python's platform default.
-    dataloader_multiprocessing_context: str | None = "spawn"
     steps: int = 100_000
     # Run policy in the simulation environment every N steps to measure reward/success (0 = disabled).
     env_eval_freq: int = 20_000
@@ -219,17 +212,6 @@ class TrainPipelineConfig(HubMixin):
             self.reward_model.pretrained_path = str(policy_dir)
 
     def validate(self) -> None:
-        available_contexts = multiprocessing.get_all_start_methods()
-        if (
-            self.dataloader_multiprocessing_context is not None
-            and self.dataloader_multiprocessing_context not in available_contexts
-        ):
-            raise ValueError(
-                "`dataloader_multiprocessing_context` must be None or one of "
-                f"{available_contexts} on this platform, got "
-                f"{self.dataloader_multiprocessing_context!r}."
-            )
-
         self._resolve_pretrained_from_cli()
 
         if self.policy is None and self.reward_model is None:

src/lerobot/datasets/lerobot_dataset.py

@@ -478,19 +478,18 @@ class LeRobotDataset(torch.utils.data.Dataset):
         """Return the number of frames in the selected episodes."""
         return self.num_frames
 
-    def __getitem__(self, idx: int | slice) -> dict | list[dict]:
-        """Return one frame or a slice of frames, with all transforms applied.
+    def __getitem__(self, idx) -> dict:
+        """Return a single frame by index, with all transforms applied.
 
         Loads the frame from the underlying HF dataset, expands delta-timestamp
         windows, decodes video frames, and applies image transforms. Delegates
-        the core logic to :class:`DatasetReader`.
+        the core logic to :meth:`DatasetReader.get_item`.
 
         Args:
-            idx: Integer index or slice into the possibly episode-filtered dataset.
+            idx: Index into the (possibly episode-filtered) dataset.
 
         Returns:
-            A frame dictionary for an integer index, or a list of frame
-            dictionaries for a slice.
+            Dict mapping feature names to their tensor values for this frame.
 
         Raises:
             RuntimeError: If the dataset is currently being recorded and
@@ -500,9 +499,6 @@ class LeRobotDataset(torch.utils.data.Dataset):
             raise RuntimeError(
                 "Cannot read from a dataset that is being recorded. Call finalize() first, then access items."
             )
-        if isinstance(idx, slice):
-            return [self[item_idx] for item_idx in range(*idx.indices(len(self)))]
-
         reader = self._ensure_reader()
         if reader.hf_dataset is None:
             # One-shot load after finalize()

src/lerobot/envs/configs.py

@@ -322,7 +322,7 @@ class HILSerlRobotEnvConfig(EnvConfig):
 class LiberoEnv(EnvConfig):
     task: str = "libero_10"  # can also choose libero_spatial, libero_object, etc.
     task_ids: list[int] | None = None
-    fps: int = 20  # Must match robosuite's default control_freq (20 Hz)
+    fps: int = 30
     episode_length: int | None = None
     obs_type: str = "pixels_agent_pos"
     render_mode: str = "rgb_array"
@@ -354,9 +354,6 @@ class LiberoEnv(EnvConfig):
     control_mode: str = "relative"  # or "absolute"
 
     def __post_init__(self):
-        if self.fps <= 0:
-            raise ValueError(f"fps must be positive, got {self.fps}")
-
         if self.obs_type == "pixels":
             self.features[LIBERO_KEY_PIXELS_AGENTVIEW] = PolicyFeature(
                 type=FeatureType.VISUAL, shape=(self.observation_height, self.observation_width, 3)
@@ -415,7 +412,6 @@ class LiberoEnv(EnvConfig):
             "render_mode": self.render_mode,
             "observation_height": self.observation_height,
             "observation_width": self.observation_width,
-            "control_freq": self.fps,
         }
         if self.task_ids is not None:
             kwargs["task_ids"] = self.task_ids

src/lerobot/envs/libero.py

@@ -125,13 +125,10 @@ class LiberoEnv(gym.Env):
         n_envs: int = 1,
         camera_name_mapping: dict[str, str] | None = None,
         num_steps_wait: int = 10,
-        control_freq: int = 20,
         control_mode: str = "relative",
         is_libero_plus: bool = False,
     ):
         super().__init__()
-        if control_freq <= 0:
-            raise ValueError(f"control_freq must be positive, got {control_freq}")
         self.task_id = task_id
         self.is_libero_plus = is_libero_plus
         self.obs_type = obs_type
@@ -157,7 +154,6 @@ class LiberoEnv(gym.Env):
             }
         self.camera_name_mapping = camera_name_mapping
         self.num_steps_wait = num_steps_wait
-        self.control_freq = control_freq
         self.episode_index = episode_index
         self.episode_length = episode_length
         # Load once and keep
@@ -264,7 +260,6 @@ class LiberoEnv(gym.Env):
             bddl_file_name=self._task_bddl_file,
             camera_heights=self.observation_height,
             camera_widths=self.observation_width,
-            control_freq=self.control_freq,
         )
         env.reset()
         self._env = env

src/lerobot/motors/damiao/damiao.py

@@ -20,6 +20,7 @@ import logging
 import time
 from contextlib import contextmanager
 from copy import deepcopy
+from functools import cached_property
 from typing import TYPE_CHECKING, Any, TypedDict
 
 from lerobot.utils.decorators import check_if_already_connected, check_if_not_connected
@@ -853,7 +854,7 @@ class DamiaoMotorsBus(MotorsBusBase):
         else:
             raise ValueError(f"Motor {motor_obj} doesn't have a valid recv_id (None).")
 
-    @property
+    @cached_property
     def is_calibrated(self) -> bool:
         """Check if motors are calibrated."""
         return bool(self.calibration)

src/lerobot/motors/motors_bus.py

@@ -23,7 +23,6 @@ from __future__ import annotations
 
 import abc
 import logging
-import time
 from collections.abc import Sequence
 from contextlib import contextmanager
 from dataclasses import dataclass
@@ -819,13 +818,13 @@ class SerialMotorsBus(MotorsBusBase):
         """
         motor_names = self._get_motors_list(motors)
 
-        start_positions = self.sync_read("Present_Position", motor_names, normalize=False, num_retry=5)
+        start_positions = self.sync_read("Present_Position", motor_names, normalize=False)
         mins = start_positions.copy()
         maxes = start_positions.copy()
 
         user_pressed_enter = False
         while not user_pressed_enter:
-            positions = self.sync_read("Present_Position", motor_names, normalize=False, num_retry=5)
+            positions = self.sync_read("Present_Position", motor_names, normalize=False)
             mins = {motor: min(positions[motor], min_) for motor, min_ in mins.items()}
             maxes = {motor: max(positions[motor], max_) for motor, max_ in maxes.items()}
 
@@ -838,12 +837,9 @@ class SerialMotorsBus(MotorsBusBase):
             if enter_pressed():
                 user_pressed_enter = True
 
-            if not user_pressed_enter:
-                if display_values:
-                    # Move cursor up to overwrite the previous output
-                    move_cursor_up(len(motor_names) + 3)
-                # Throttle reads even when the live table is disabled.
-                time.sleep(0.02)
+            if display_values and not user_pressed_enter:
+                # Move cursor up to overwrite the previous output
+                move_cursor_up(len(motor_names) + 3)
 
         same_min_max = [motor for motor in motor_names if mins[motor] == maxes[motor]]
         if same_min_max:

src/lerobot/policies/diffusion/configuration_diffusion.py

@@ -79,8 +79,6 @@ class DiffusionConfig(PreTrainedConfig):
         use_film_scale_modulation: FiLM (https://huggingface.co/papers/1709.07871) is used for the Unet conditioning.
             Bias modulation is used be default, while this parameter indicates whether to also use scale
             modulation.
-        gradient_checkpointing: Whether to checkpoint the Unet residual blocks during training. This reduces
-            activation memory at the cost of recomputing those blocks during the backward pass.
         noise_scheduler_type: Name of the noise scheduler to use. Supported options: ["DDPM", "DDIM"].
         num_train_timesteps: Number of diffusion steps for the forward diffusion schedule.
         beta_schedule: Name of the diffusion beta schedule as per DDPMScheduler from Hugging Face diffusers.
@@ -134,7 +132,6 @@ class DiffusionConfig(PreTrainedConfig):
     n_groups: int = 8
     diffusion_step_embed_dim: int = 128
     use_film_scale_modulation: bool = True
-    gradient_checkpointing: bool = False
     # Noise scheduler.
     noise_scheduler_type: str = "DDPM"
     num_train_timesteps: int = 100

src/lerobot/policies/diffusion/modeling_diffusion.py

@@ -31,7 +31,6 @@ import torch
 import torch.nn.functional as F  # noqa: N812
 import torchvision
 from torch import Tensor, nn
-from torch.utils.checkpoint import checkpoint
 
 from lerobot.utils.constants import ACTION, OBS_ENV_STATE, OBS_IMAGES, OBS_STATE
 from lerobot.utils.import_utils import _diffusers_available, require_package
@@ -728,35 +727,22 @@ class DiffusionConditionalUnet1d(nn.Module):
         else:
             global_feature = timesteps_embed
 
-        use_gc = self.config.gradient_checkpointing and self.training
-
         # Run encoder, keeping track of skip features to pass to the decoder.
         encoder_skip_features: list[Tensor] = []
         for resnet, resnet2, downsample in self.down_modules:
-            if use_gc:
-                x = checkpoint(resnet, x, global_feature, use_reentrant=False)
-                x = checkpoint(resnet2, x, global_feature, use_reentrant=False)
-            else:
-                x = resnet(x, global_feature)
-                x = resnet2(x, global_feature)
+            x = resnet(x, global_feature)
+            x = resnet2(x, global_feature)
             encoder_skip_features.append(x)
             x = downsample(x)
 
         for mid_module in self.mid_modules:
-            if use_gc:
-                x = checkpoint(mid_module, x, global_feature, use_reentrant=False)
-            else:
-                x = mid_module(x, global_feature)
+            x = mid_module(x, global_feature)
 
         # Run decoder, using the skip features from the encoder.
         for resnet, resnet2, upsample in self.up_modules:
             x = torch.cat((x, encoder_skip_features.pop()), dim=1)
-            if use_gc:
-                x = checkpoint(resnet, x, global_feature, use_reentrant=False)
-                x = checkpoint(resnet2, x, global_feature, use_reentrant=False)
-            else:
-                x = resnet(x, global_feature)
-                x = resnet2(x, global_feature)
+            x = resnet(x, global_feature)
+            x = resnet2(x, global_feature)
             x = upsample(x)
 
         x = self.final_conv(x)

src/lerobot/robots/openarm_follower/openarm_follower.py

@@ -150,6 +150,9 @@ class OpenArmFollower(Robot):
 
         self.configure()
 
+        if self.is_calibrated:
+            self.bus.set_zero_position()
+
         self.bus.enable_torque()
 
         logger.info(f"{self} connected.")

src/lerobot/scripts/lerobot_setup_motors.py

@@ -51,7 +51,19 @@ from lerobot.teleoperators import (  # noqa: F401
     rebot_102_leader,
     so_leader,
 )
-from lerobot.utils.import_utils import register_third_party_plugins
+
+COMPATIBLE_DEVICES = [
+    "koch_follower",
+    "koch_leader",
+    "omx_follower",
+    "omx_leader",
+    "openarm_mini",
+    "so100_follower",
+    "so100_leader",
+    "so101_follower",
+    "so101_leader",
+    "lekiwi",
+]
 
 
 @dataclass
@@ -68,19 +80,18 @@ class SetupConfig:
 
 @draccus.wrap()
 def setup_motors(cfg: SetupConfig):
+    if cfg.device.type not in COMPATIBLE_DEVICES:
+        raise NotImplementedError
+
     if isinstance(cfg.device, RobotConfig):
         device = make_robot_from_config(cfg.device)
     else:
         device = make_teleoperator_from_config(cfg.device)
 
-    setup = getattr(device, "setup_motors", None)
-    if not callable(setup):
-        raise NotImplementedError(f"Device type '{cfg.device.type}' does not support motor setup.")
-    setup()
+    device.setup_motors()
 
 
 def main():
-    register_third_party_plugins()
     setup_motors()
 
 

src/lerobot/scripts/lerobot_train.py

@@ -71,16 +71,6 @@ from lerobot.utils.utils import (
 from .lerobot_eval import eval_policy_all
 
 
-def _dataloader_worker_kwargs(cfg: TrainPipelineConfig) -> dict[str, Any]:
-    """Return worker-only DataLoader options, disabling them for single-process loading."""
-    workers_enabled = cfg.num_workers > 0
-    return {
-        "prefetch_factor": cfg.prefetch_factor if workers_enabled else None,
-        "persistent_workers": cfg.persistent_workers and workers_enabled,
-        "multiprocessing_context": cfg.dataloader_multiprocessing_context if workers_enabled else None,
-    }
-
-
 def update_policy(
     train_metrics: MetricsTracker,
     policy: PreTrainedPolicy,
@@ -483,7 +473,8 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
         pin_memory=device.type == "cuda",
         drop_last=False,
         collate_fn=collate_fn,
-        **_dataloader_worker_kwargs(cfg),
+        prefetch_factor=cfg.prefetch_factor if cfg.num_workers > 0 else None,
+        persistent_workers=cfg.persistent_workers and cfg.num_workers > 0,
     )
 
     # Build eval dataloader if a held-out split exists
@@ -509,7 +500,8 @@ def train(cfg: TrainPipelineConfig, accelerator: "Accelerator | None" = None):
             pin_memory=device.type == "cuda",
             drop_last=False,
             collate_fn=eval_collate_fn,
-            **_dataloader_worker_kwargs(cfg),
+            prefetch_factor=cfg.prefetch_factor if cfg.num_workers > 0 else None,
+            persistent_workers=cfg.persistent_workers and cfg.num_workers > 0,
         )
 
     # Prepare everything with accelerator

src/lerobot/teleoperators/gamepad/configuration_gamepad.py

@@ -23,5 +23,3 @@ from ..config import TeleoperatorConfig
 @dataclass
 class GamepadTeleopConfig(TeleoperatorConfig):
     use_gripper: bool = True
-    # Use hidapi instead of pygame for controllers that pygame cannot detect reliably.
-    hidapi_fallback: bool = False

src/lerobot/teleoperators/gamepad/teleop_gamepad.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
 import sys
 from enum import IntEnum
 from typing import Any
@@ -28,8 +27,6 @@ from ..teleoperator import Teleoperator
 from ..utils import TeleopEvents
 from .configuration_gamepad import GamepadTeleopConfig
 
-logger = logging.getLogger(__name__)
-
 
 class GripperAction(IntEnum):
     CLOSE = 0
@@ -59,13 +56,6 @@ class GamepadTeleop(Teleoperator):
 
         self.gamepad = None
 
-        self.hidapi_fallback = config.hidapi_fallback
-        if sys.platform == "darwin" and not self.hidapi_fallback:
-            logger.warning(
-                "On macOS, pygame may not reliably detect input from some controllers. "
-                "If you experience issues, set `hidapi_fallback=true`."
-            )
-
     @property
     def action_features(self) -> dict:
         if self.config.use_gripper:
@@ -86,7 +76,9 @@ class GamepadTeleop(Teleoperator):
         return {}
 
     def connect(self) -> None:
-        if self.hidapi_fallback:
+        # use HidApi for macos
+        if sys.platform == "darwin":
+            # NOTE: On macOS, pygame doesn’t reliably detect input from some controllers so we fall back to hidapi
             from .gamepad_utils import GamepadControllerHID as Gamepad
         else:
             from .gamepad_utils import GamepadController as Gamepad

tests/cameras/test_realsense.py

@@ -20,7 +20,7 @@
 # ```
 
 from pathlib import Path
-from unittest.mock import patch
+from unittest.mock import MagicMock, patch
 
 import numpy as np
 import pytest
@@ -30,6 +30,8 @@ from lerobot.utils.errors import DeviceAlreadyConnectedError, DeviceNotConnected
 
 pytest.importorskip("pyrealsense2")
 
+import pyrealsense2 as rs
+
 from lerobot.cameras.realsense import RealSenseCamera, RealSenseCameraConfig
 
 TEST_ARTIFACTS_DIR = Path(__file__).parent.parent / "artifacts" / "cameras"
@@ -61,6 +63,17 @@ def test_abc_implementation():
     _ = RealSenseCamera(config)
 
 
+@pytest.mark.parametrize("option", ["exposure", "gain", "white_balance"])
+def test_manual_color_option_requires_rgb(option):
+    with pytest.raises(ValueError, match="use_rgb=True"):
+        RealSenseCameraConfig(
+            serial_number_or_name="042",
+            use_rgb=False,
+            use_depth=True,
+            **{option: 100},
+        )
+
+
 def test_connect():
     config = RealSenseCameraConfig(serial_number_or_name="042", warmup_s=0)
 
@@ -83,6 +96,27 @@ def test_connect_invalid_camera_path(patch_realsense):
         camera.connect(warmup=False)
 
 
+def test_connect_cleans_up_when_sensor_configuration_fails():
+    config = RealSenseCameraConfig(serial_number_or_name="042", exposure=120)
+    camera = RealSenseCamera(config)
+    pipeline = MagicMock()
+    pipeline.start.return_value = MagicMock()
+
+    with (
+        patch("lerobot.cameras.realsense.camera_realsense.rs.pipeline", return_value=pipeline),
+        patch.object(camera, "_configure_rs_pipeline_config"),
+        patch.object(camera, "_configure_capture_settings"),
+        patch.object(camera, "_configure_sensor_options", side_effect=ValueError("invalid exposure")),
+        pytest.raises(ValueError, match="invalid exposure"),
+    ):
+        camera.connect(warmup=False)
+
+    pipeline.stop.assert_called_once_with()
+    assert camera.rs_pipeline is None
+    assert camera.rs_profile is None
+    assert not camera.is_connected
+
+
 def test_invalid_width_connect():
     config = RealSenseCameraConfig(serial_number_or_name="042", width=99999, height=480, fps=30)
     camera = RealSenseCamera(config)
@@ -202,6 +236,203 @@ def test_read_latest_too_old():
             _ = camera.read_latest(max_age_ms=0)  # immediately too old
 
 
+def _make_mock_sensor(name: str, supported_options: set | None = None) -> MagicMock:
+    """Build a fake rs.sensor that reports a name and a configurable supported-options set."""
+    supported = supported_options if supported_options is not None else set()
+    sensor = MagicMock()
+    sensor.get_info.return_value = name
+    sensor.supports.side_effect = lambda opt: opt in supported
+    return sensor
+
+
+def _attach_mock_color_sensor(camera: RealSenseCamera, sensor: MagicMock) -> None:
+    """Wire camera.rs_profile so _get_color_sensor finds the given sensor."""
+    profile = MagicMock()
+    device = MagicMock()
+    device.query_sensors.return_value = [sensor]
+    profile.get_device.return_value = device
+    camera.rs_profile = profile
+
+
+def test_get_color_sensor_prefers_rgb_camera():
+    config = RealSenseCameraConfig(serial_number_or_name="042")
+    camera = RealSenseCamera(config)
+
+    rgb = _make_mock_sensor("RGB Camera")
+    stereo = _make_mock_sensor("Stereo Module")
+    profile = MagicMock()
+    device = MagicMock()
+    device.query_sensors.return_value = [stereo, rgb]
+    profile.get_device.return_value = device
+    camera.rs_profile = profile
+
+    assert camera._get_color_sensor() is rgb
+
+
+def test_get_color_sensor_falls_back_to_stereo_module():
+    """D405 has no separate RGB module; color comes from Stereo Module."""
+    config = RealSenseCameraConfig(serial_number_or_name="042")
+    camera = RealSenseCamera(config)
+
+    stereo = _make_mock_sensor("Stereo Module")
+    _attach_mock_color_sensor(camera, stereo)
+
+    assert camera._get_color_sensor() is stereo
+
+
+def test_get_color_sensor_raises_with_available_sensors():
+    config = RealSenseCameraConfig(serial_number_or_name="042")
+    camera = RealSenseCamera(config)
+
+    other = _make_mock_sensor("Motion Module")
+    _attach_mock_color_sensor(camera, other)
+
+    with pytest.raises(RuntimeError, match="Motion Module"):
+        camera._get_color_sensor()
+
+
+def test_configure_sensor_options_skipped_when_none():
+    config = RealSenseCameraConfig(serial_number_or_name="042")
+    camera = RealSenseCamera(config)
+
+    with patch.object(RealSenseCamera, "_get_color_sensor") as mock_get:
+        camera._configure_sensor_options()
+        mock_get.assert_not_called()
+
+
+def test_configure_sensor_options_applies_all_values():
+    config = RealSenseCameraConfig(serial_number_or_name="042", exposure=120, gain=64, white_balance=4600)
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor(
+        "RGB Camera",
+        supported_options={
+            rs.option.enable_auto_exposure,
+            rs.option.exposure,
+            rs.option.gain,
+            rs.option.enable_auto_white_balance,
+            rs.option.white_balance,
+        },
+    )
+    _attach_mock_color_sensor(camera, sensor)
+
+    camera._configure_sensor_options()
+
+    sensor.set_option.assert_any_call(rs.option.enable_auto_exposure, 0)
+    sensor.set_option.assert_any_call(rs.option.exposure, 120)
+    sensor.set_option.assert_any_call(rs.option.gain, 64)
+    sensor.set_option.assert_any_call(rs.option.enable_auto_white_balance, 0)
+    sensor.set_option.assert_any_call(rs.option.white_balance, 4600)
+
+
+@pytest.mark.parametrize(
+    ("config_field", "option", "label"),
+    [
+        ("exposure", rs.option.exposure, "exposure"),
+        ("gain", rs.option.gain, "gain"),
+        ("white_balance", rs.option.white_balance, "white balance"),
+    ],
+)
+def test_configure_sensor_options_raises_when_requested_option_is_unsupported(config_field, option, label):
+    config = RealSenseCameraConfig(serial_number_or_name="042", **{config_field: 100})
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor("RGB Camera", supported_options=set())
+    _attach_mock_color_sensor(camera, sensor)
+
+    with pytest.raises(ValueError, match=label):
+        camera._configure_sensor_options()
+
+    sensor.supports.assert_any_call(option)
+    sensor.set_option.assert_not_called()
+
+
+@pytest.mark.parametrize(
+    ("config_field", "option", "value"),
+    [
+        ("exposure", rs.option.exposure, 120),
+        ("gain", rs.option.gain, 64),
+    ],
+)
+def test_configure_sensor_options_exposure_or_gain_disables_auto_exposure(config_field, option, value):
+    """white_balance=None should not touch auto white balance."""
+    config = RealSenseCameraConfig(serial_number_or_name="042", **{config_field: value})
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor(
+        "RGB Camera",
+        supported_options={rs.option.enable_auto_exposure, option},
+    )
+    _attach_mock_color_sensor(camera, sensor)
+
+    camera._configure_sensor_options()
+
+    calls = [call.args for call in sensor.set_option.call_args_list]
+    assert (rs.option.enable_auto_exposure, 0) in calls
+    assert (option, value) in calls
+    for opt, _ in calls:
+        assert opt != rs.option.enable_auto_white_balance
+        assert opt != rs.option.white_balance
+
+
+def test_configure_sensor_options_warns_when_auto_exposure_control_is_unsupported(caplog):
+    config = RealSenseCameraConfig(serial_number_or_name="042", exposure=120)
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor("RGB Camera", supported_options={rs.option.exposure})
+    _attach_mock_color_sensor(camera, sensor)
+
+    with caplog.at_level("WARNING"):
+        camera._configure_sensor_options()
+
+    sensor.set_option.assert_called_once_with(rs.option.exposure, 120)
+    assert "does not support disabling auto-exposure" in caplog.text
+
+
+def test_configure_sensor_options_warns_when_auto_white_balance_control_is_unsupported(caplog):
+    config = RealSenseCameraConfig(serial_number_or_name="042", white_balance=4600)
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor("RGB Camera", supported_options={rs.option.white_balance})
+    _attach_mock_color_sensor(camera, sensor)
+
+    with caplog.at_level("WARNING"):
+        camera._configure_sensor_options()
+
+    sensor.set_option.assert_called_once_with(rs.option.white_balance, 4600)
+    assert "does not support disabling auto white balance" in caplog.text
+
+
+def test_configure_sensor_options_out_of_range_raises_value_error():
+    """set_option errors should be re-raised as ValueError with range diagnostics."""
+    config = RealSenseCameraConfig(serial_number_or_name="042", exposure=999999)
+    camera = RealSenseCamera(config)
+
+    sensor = _make_mock_sensor(
+        "RGB Camera",
+        supported_options={rs.option.enable_auto_exposure, rs.option.exposure},
+    )
+
+    def fake_set_option(option, value):
+        if option == rs.option.exposure:
+            raise RuntimeError("value out of range")
+
+    sensor.set_option.side_effect = fake_set_option
+
+    option_range = MagicMock(min=1, max=10000, step=1, default=156)
+    sensor.get_option_range.return_value = option_range
+
+    _attach_mock_color_sensor(camera, sensor)
+
+    with pytest.raises(ValueError, match="exposure") as exc_info:
+        camera._configure_sensor_options()
+
+    msg = str(exc_info.value)
+    assert "999999" in msg
+    assert "min=1" in msg
+    assert "max=10000" in msg
+
+
 @pytest.mark.parametrize(
     "rotation",
     [

tests/datasets/test_datasets.py

@@ -114,20 +114,6 @@ def test_dataset_initialization(tmp_path, lerobot_dataset_factory):
     assert dataset.num_frames == len(dataset)
 
 
-def test_dataset_slice(tmp_path, lerobot_dataset_factory):
-    dataset = lerobot_dataset_factory(
-        root=tmp_path / "test", total_episodes=3, total_frames=30, use_videos=False
-    )
-
-    assert len(dataset[:5]) == 5
-    assert len(dataset[::2]) == (len(dataset) + 1) // 2
-    assert [item["index"].item() for item in dataset[4::-1]] == [4, 3, 2, 1, 0]
-    assert [item["index"].item() for item in dataset[-3:]] == list(range(len(dataset) - 3, len(dataset)))
-    assert dataset[len(dataset) :] == []
-    assert isinstance(dataset[0], dict)
-    assert dataset[:1][0].keys() == dataset[0].keys()
-
-
 # TODO(rcadene, aliberts): do not run LeRobotDataset.create, instead refactor LeRobotDatasetMetadata.create
 # and test the small resulting function that validates the features
 def test_dataset_feature_with_forward_slash_raises_error():
@@ -1755,38 +1741,6 @@ def test_delta_timestamps_query_returns_correct_values(tmp_path, empty_lerobot_d
     assert is_pad == [True, False], f"Expected [True, False], got {is_pad}"
 
 
-def test_dataset_slice_with_delta_timestamps(tmp_path, empty_lerobot_dataset_factory):
-    features = {
-        "observation.state": {"dtype": "float32", "shape": (1,), "names": ["x"]},
-    }
-    dataset = empty_lerobot_dataset_factory(
-        root=tmp_path / "test_slice_delta", features=features, use_videos=False, fps=10
-    )
-
-    for frame_idx in range(5):
-        dataset.add_frame(
-            {
-                "observation.state": torch.tensor([frame_idx], dtype=torch.float32),
-                "task": "task_0",
-            }
-        )
-    dataset.save_episode()
-    dataset.finalize()
-
-    sliced_dataset = LeRobotDataset(
-        dataset.repo_id,
-        root=dataset.root,
-        delta_timestamps={"observation.state": [-0.1, 0.0]},
-        tolerance_s=0.04,
-    )
-
-    items = sliced_dataset[:2]
-
-    assert items[0]["observation.state"].tolist() == [0.0, 0.0]
-    assert items[0]["observation.state_is_pad"].tolist() == [True, False]
-    assert items[1]["observation.state"].tolist() == [0.0, 1.0]
-
-
 def test_episode_filter_filters_dataset(tmp_path, lerobot_dataset_factory):
     """episode_filter on LeRobotDataset narrows the loaded dataset to matching episodes."""
     dataset = lerobot_dataset_factory(root=tmp_path / "test", total_episodes=8, total_frames=200)

tests/envs/test_dispatch.py

@@ -35,17 +35,6 @@ def test_unknown_type():
         make_env_config("nonexistent")
 
 
-def test_libero_fps_controls_simulator_frequency():
-    cfg = LiberoEnv(fps=17)
-
-    assert cfg.gym_kwargs["control_freq"] == 17
-
-
-def test_libero_rejects_nonpositive_fps():
-    with pytest.raises(ValueError, match="fps must be positive"):
-        LiberoEnv(fps=0)
-
-
 def test_identity_processors():
     """Base class get_env_processors() returns identity pipelines."""
     cfg = make_env_config("aloha")

tests/motors/test_dynamixel.py

@@ -405,18 +405,12 @@ def test_record_ranges_of_motion(mock_motors, dummy_motors):
     read_pos_stub = mock_motors.build_sequential_sync_read_stub(
         *X_SERIES_CONTROL_TABLE["Present_Position"], positions
     )
-    bus = DynamixelMotorsBus(port=mock_motors.port, motors=dummy_motors)
-    bus.connect(handshake=False)
+    with patch("lerobot.motors.motors_bus.enter_pressed", side_effect=[False, True]):
+        bus = DynamixelMotorsBus(port=mock_motors.port, motors=dummy_motors)
+        bus.connect(handshake=False)
 
-    with (
-        patch("lerobot.motors.motors_bus.enter_pressed", side_effect=[False, True]),
-        patch("lerobot.motors.motors_bus.time.sleep") as mock_sleep,
-        patch.object(bus, "sync_read", wraps=bus.sync_read) as mock_sync_read,
-    ):
         mins, maxes = bus.record_ranges_of_motion(display_values=False)
 
     assert mock_motors.stubs[read_pos_stub].calls == 3
-    assert all(call.kwargs["num_retry"] == 5 for call in mock_sync_read.call_args_list)
-    mock_sleep.assert_called_once_with(0.02)
     assert mins == expected_mins
     assert maxes == expected_maxes

tests/motors/test_feetech.py

@@ -509,18 +509,12 @@ def test_record_ranges_of_motion(mock_motors, dummy_motors):
     stub = mock_motors.build_sequential_sync_read_stub(
         *STS_SMS_SERIES_CONTROL_TABLE["Present_Position"], positions
     )
-    bus = FeetechMotorsBus(port=mock_motors.port, motors=dummy_motors)
-    bus.connect(handshake=False)
+    with patch("lerobot.motors.motors_bus.enter_pressed", side_effect=[False, True]):
+        bus = FeetechMotorsBus(port=mock_motors.port, motors=dummy_motors)
+        bus.connect(handshake=False)
 
-    with (
-        patch("lerobot.motors.motors_bus.enter_pressed", side_effect=[False, True]),
-        patch("lerobot.motors.motors_bus.time.sleep") as mock_sleep,
-        patch.object(bus, "sync_read", wraps=bus.sync_read) as mock_sync_read,
-    ):
         mins, maxes = bus.record_ranges_of_motion(display_values=False)
 
     assert mock_motors.stubs[stub].calls == 3
-    assert all(call.kwargs["num_retry"] == 5 for call in mock_sync_read.call_args_list)
-    mock_sleep.assert_called_once_with(0.02)
     assert mins == expected_mins
     assert maxes == expected_maxes

tests/scripts/test_setup_motors.py

@@ -1,49 +0,0 @@
-# Copyright 2026 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.
-
-from types import SimpleNamespace
-from unittest.mock import MagicMock
-
-import pytest
-
-import lerobot.scripts.lerobot_setup_motors as motors_module
-
-
-def test_main_registers_plugins_before_parsing(monkeypatch):
-    calls = []
-    monkeypatch.setattr(motors_module, "register_third_party_plugins", lambda: calls.append("register"))
-    monkeypatch.setattr(motors_module, "setup_motors", lambda: calls.append("setup"))
-
-    motors_module.main()
-
-    assert calls == ["register", "setup"]
-
-
-def test_setup_motors_accepts_third_party_device(monkeypatch):
-    device = MagicMock()
-    monkeypatch.setattr(motors_module, "make_teleoperator_from_config", lambda _: device)
-    cfg = SimpleNamespace(device=SimpleNamespace(type="third_party"))
-
-    motors_module.setup_motors.__wrapped__(cfg)
-
-    device.setup_motors.assert_called_once_with()
-
-
-def test_setup_motors_reports_unsupported_device(monkeypatch):
-    device = object()
-    monkeypatch.setattr(motors_module, "make_teleoperator_from_config", lambda _: device)
-    cfg = SimpleNamespace(device=SimpleNamespace(type="third_party"))
-
-    with pytest.raises(NotImplementedError, match="third_party"):
-        motors_module.setup_motors.__wrapped__(cfg)