refactor(tests): update processor test assertions to reflect new preprocessor and postprocessor names (#1869)

- Changed assertions in multiple processor test files to verify the updated names from "robot_preprocessor" and "robot_postprocessor" to "policy_preprocessor" and "policy_postprocessor" for consistency with recent refactoring.

pyproject.toml

@@ -73,7 +73,6 @@ dependencies = [
     "pynput>=1.7.7",
     "pyserial>=3.5",
     "wandb>=0.20.0",
-    "scipy>=1.15.2",
 
     "torch>=2.2.1,<2.8.0", # TODO: Bumb dependency
     "torchcodec>=0.2.1,<0.6.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')", # TODO: Bumb dependency

src/lerobot/constants.py

@@ -45,8 +45,8 @@ OPTIMIZER_STATE = "optimizer_state.safetensors"
 OPTIMIZER_PARAM_GROUPS = "optimizer_param_groups.json"
 SCHEDULER_STATE = "scheduler_state.json"
 
-PREPROCESSOR_DEFAULT_NAME = "robot_preprocessor"
-POSTPROCESSOR_DEFAULT_NAME = "robot_postprocessor"
+POLICY_PREPROCESSOR_DEFAULT_NAME = "policy_preprocessor"
+POLICY_POSTPROCESSOR_DEFAULT_NAME = "policy_postprocessor"
 
 if "LEROBOT_HOME" in os.environ:
     raise ValueError(

src/lerobot/policies/act/processor_act.py

@@ -15,7 +15,7 @@
 # limitations under the License.
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.act.configuration_act import ACTConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -59,12 +59,12 @@ def make_act_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/diffusion/processor_diffusion.py

@@ -16,7 +16,7 @@
 # limitations under the License.
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.diffusion.configuration_diffusion import DiffusionConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -59,12 +59,12 @@ def make_diffusion_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/factory.py

@@ -24,6 +24,7 @@ from typing_extensions import Unpack
 
 from lerobot.configs.policies import PreTrainedConfig
 from lerobot.configs.types import FeatureType
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.datasets.lerobot_dataset import LeRobotDatasetMetadata
 from lerobot.datasets.utils import dataset_to_policy_features
 from lerobot.envs.configs import EnvConfig
@@ -148,14 +149,18 @@ def make_pre_post_processors(
         return (
             PolicyProcessorPipeline.from_pretrained(
                 pretrained_model_name_or_path=pretrained_path,
-                config_filename=kwargs.get("preprocessor_config_filename", "robot_preprocessor.json"),
+                config_filename=kwargs.get(
+                    "preprocessor_config_filename", f"{POLICY_PREPROCESSOR_DEFAULT_NAME}.json"
+                ),
                 overrides=kwargs.get("preprocessor_overrides", {}),
                 to_transition=preprocessor_kwargs.get("to_transition"),
                 to_output=preprocessor_kwargs.get("to_output"),
             ),
             PolicyProcessorPipeline.from_pretrained(
                 pretrained_model_name_or_path=pretrained_path,
-                config_filename=kwargs.get("postprocessor_config_filename", "robot_postprocessor.json"),
+                config_filename=kwargs.get(
+                    "postprocessor_config_filename", f"{POLICY_POSTPROCESSOR_DEFAULT_NAME}.json"
+                ),
                 overrides=kwargs.get("postprocessor_overrides", {}),
                 to_transition=postprocessor_kwargs.get("to_transition"),
                 to_output=postprocessor_kwargs.get("to_output"),

src/lerobot/policies/pi0/processor_pi0.py

@@ -18,7 +18,7 @@
 import torch
 
 from lerobot.configs.types import PolicyFeature
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.pi0.configuration_pi0 import PI0Config
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -107,12 +107,12 @@ def make_pi0_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/pi0fast/processor_pi0fast.py

@@ -16,7 +16,7 @@
 
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.pi0.configuration_pi0 import PI0Config
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -59,12 +59,12 @@ def make_pi0fast_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/sac/processor_sac.py

@@ -17,7 +17,7 @@
 
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.sac.configuration_sac import SACConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -60,12 +60,12 @@ def make_sac_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/smolvla/processor_smolvla.py

@@ -17,7 +17,7 @@
 import torch
 
 from lerobot.configs.types import PolicyFeature
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.smolvla.configuration_smolvla import SmolVLAConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -70,12 +70,12 @@ def make_smolvla_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/tdmpc/processor_tdmpc.py

@@ -16,7 +16,7 @@
 # limitations under the License.
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.tdmpc.configuration_tdmpc import TDMPCConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -59,12 +59,12 @@ def make_tdmpc_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/policies/vqbet/processor_vqbet.py

@@ -17,7 +17,7 @@
 # limitations under the License.
 import torch
 
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.vqbet.configuration_vqbet import VQBeTConfig
 from lerobot.processor import (
     AddBatchDimensionProcessorStep,
@@ -60,12 +60,12 @@ def make_vqbet_pre_post_processors(
     return (
         PolicyProcessorPipeline(
             steps=input_steps,
-            name=PREPROCESSOR_DEFAULT_NAME,
+            name=POLICY_PREPROCESSOR_DEFAULT_NAME,
             **preprocessor_kwargs,
         ),
         PolicyProcessorPipeline(
             steps=output_steps,
-            name=POSTPROCESSOR_DEFAULT_NAME,
+            name=POLICY_POSTPROCESSOR_DEFAULT_NAME,
             **postprocessor_kwargs,
         ),
     )

src/lerobot/processor/converters.py

@@ -23,9 +23,9 @@ from typing import Any
 
 import numpy as np
 import torch
-from scipy.spatial.transform import Rotation
 
 from lerobot.constants import ACTION, DONE, OBS_IMAGES, OBS_STATE, REWARD, TRUNCATED
+from lerobot.utils.rotation import Rotation
 
 from .core import EnvTransition, TransitionKey
 

src/lerobot/processor/hil_processor.py

@@ -1,7 +1,7 @@
 import math
 import time
 from dataclasses import dataclass
-from typing import Any
+from typing import Any, Protocol, TypeVar, runtime_checkable
 
 import numpy as np
 import torch
@@ -27,6 +27,40 @@ DISCRETE_PENALTY_KEY = "discrete_penalty"
 TELEOP_ACTION_KEY = "teleop_action"
 
 
+@runtime_checkable
+class HasTeleopEvents(Protocol):
+    """Minimal protocol for objects that provide teleoperation events.
+
+    This protocol only defines the additional get_teleop_events() method,
+    avoiding duplication of the entire Teleoperator interface.
+    """
+
+    def get_teleop_events(self) -> dict[str, Any]:
+        """Get extra control events from the teleoperator.
+
+        Returns:
+            Dictionary containing control events such as:
+                - is_intervention: bool - Whether human is currently intervening
+                - terminate_episode: bool - Whether to terminate the current episode
+                - success: bool - Whether the episode was successful
+                - rerecord_episode: bool - Whether to rerecord the episode
+        """
+        ...
+
+
+# Type variable constrained to Teleoperator subclasses that also implement events
+TeleopWithEvents = TypeVar("TeleopWithEvents", bound=Teleoperator)
+
+
+def _check_teleop_with_events(teleop: Teleoperator) -> None:
+    """Runtime check that a teleoperator implements get_teleop_events."""
+    if not isinstance(teleop, HasTeleopEvents):
+        raise TypeError(
+            f"Teleoperator {type(teleop).__name__} must implement get_teleop_events() method. "
+            f"Compatible teleoperators: GamepadTeleop, KeyboardEndEffectorTeleop"
+        )
+
+
 @ProcessorStepRegistry.register("add_teleop_action_as_complementary_data")
 @dataclass
 class AddTeleopActionAsComplimentaryDataStep(ComplementaryDataProcessorStep):
@@ -46,13 +80,29 @@ class AddTeleopActionAsComplimentaryDataStep(ComplementaryDataProcessorStep):
 @ProcessorStepRegistry.register("add_teleop_action_as_info")
 @dataclass
 class AddTeleopEventsAsInfoStep(InfoProcessorStep):
-    """Add teleoperator control events to transition info."""
+    """Add teleoperator control events to transition info.
 
-    teleop_device: Teleoperator
+    This processor step extracts control events from teleoperators that support
+    event-based interaction (intervention detection, episode termination, etc.).
+
+    Works with any teleoperator that inherits from Teleoperator and implements the
+    get_teleop_events() method, including custom user-defined teleoperators.
+
+    Built-in compatible teleoperators:
+        - GamepadTeleop: Uses gamepad buttons for control events
+        - KeyboardEndEffectorTeleop: Uses keyboard keys for control events
+    """
+
+    teleop_device: TeleopWithEvents
+
+    def __post_init__(self):
+        """Validate that the teleoperator supports events."""
+        _check_teleop_with_events(self.teleop_device)
 
     def info(self, info: dict) -> dict:
         new_info = dict(info)
-        teleop_events = getattr(self.teleop_device, "get_teleop_events", lambda: {})()
+
+        teleop_events = self.teleop_device.get_teleop_events()
         new_info.update(teleop_events)
         return new_info
 

src/lerobot/robots/so100_follower/robot_kinematic_processor.py

@@ -17,7 +17,6 @@
 from dataclasses import dataclass, field
 
 import numpy as np
-from scipy.spatial.transform import Rotation
 
 from lerobot.configs.types import FeatureType, PolicyFeature
 from lerobot.constants import ACTION, OBS_STATE
@@ -32,6 +31,7 @@ from lerobot.processor import (
     TransitionKey,
 )
 from lerobot.robots.robot import Robot
+from lerobot.utils.rotation import Rotation
 
 
 @ProcessorStepRegistry.register("ee_reference_and_delta")

src/lerobot/scripts/train.py

@@ -26,7 +26,7 @@ from torch.optim import Optimizer
 
 from lerobot.configs import parser
 from lerobot.configs.train import TrainPipelineConfig
-from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
+from lerobot.constants import POLICY_POSTPROCESSOR_DEFAULT_NAME, POLICY_PREPROCESSOR_DEFAULT_NAME
 from lerobot.datasets.factory import make_dataset
 from lerobot.datasets.sampler import EpisodeAwareSampler
 from lerobot.datasets.utils import cycle
@@ -153,9 +153,11 @@ def train(cfg: TrainPipelineConfig):
 
     if cfg.resume:
         step, optimizer, lr_scheduler = load_training_state(cfg.checkpoint_path, optimizer, lr_scheduler)
-        preprocessor.from_pretrained(cfg.checkpoint_path, config_filename=f"{PREPROCESSOR_DEFAULT_NAME}.json")
+        preprocessor.from_pretrained(
+            cfg.policy.pretrained_path, config_filename=f"{POLICY_PREPROCESSOR_DEFAULT_NAME}.json"
+        )
         postprocessor.from_pretrained(
-            cfg.checkpoint_path, config_filename=f"{POSTPROCESSOR_DEFAULT_NAME}.json"
+            cfg.policy.pretrained_path, config_filename=f"{POLICY_POSTPROCESSOR_DEFAULT_NAME}.json"
         )
 
     num_learnable_params = sum(p.numel() for p in policy.parameters() if p.requires_grad)

src/lerobot/teleoperators/phone/teleop_phone.py

@@ -24,12 +24,12 @@ import time
 
 import hebi
 import numpy as np
-from scipy.spatial.transform import Rotation
 from teleop import Teleop
 
 from lerobot.errors import DeviceAlreadyConnectedError, DeviceNotConnectedError
 from lerobot.teleoperators.phone.config_phone import PhoneConfig, PhoneOS
 from lerobot.teleoperators.teleoperator import Teleoperator
+from lerobot.utils.rotation import Rotation
 
 logger = logging.getLogger(__name__)
 

src/lerobot/utils/rotation.py

@@ -0,0 +1,174 @@
+#!/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.
+
+"""Custom rotation utilities to replace scipy.spatial.transform.Rotation."""
+
+import numpy as np
+
+
+class Rotation:
+    """
+    Custom rotation class that provides a subset of scipy.spatial.transform.Rotation functionality.
+
+    Supports conversions between rotation vectors, rotation matrices, and quaternions.
+    """
+
+    def __init__(self, quat: np.ndarray) -> None:
+        """Initialize rotation from quaternion [x, y, z, w]."""
+        self._quat = np.asarray(quat, dtype=float)
+        # Normalize quaternion
+        norm = np.linalg.norm(self._quat)
+        if norm > 0:
+            self._quat = self._quat / norm
+
+    @classmethod
+    def from_rotvec(cls, rotvec: np.ndarray) -> "Rotation":
+        """
+        Create rotation from rotation vector using Rodrigues' formula.
+
+        Args:
+            rotvec: Rotation vector [x, y, z] where magnitude is angle in radians
+
+        Returns:
+            Rotation instance
+        """
+        rotvec = np.asarray(rotvec, dtype=float)
+        angle = np.linalg.norm(rotvec)
+
+        if angle < 1e-8:
+            # For very small angles, use identity quaternion
+            quat = np.array([0.0, 0.0, 0.0, 1.0])
+        else:
+            axis = rotvec / angle
+            half_angle = angle / 2.0
+            sin_half = np.sin(half_angle)
+            cos_half = np.cos(half_angle)
+
+            # Quaternion [x, y, z, w]
+            quat = np.array([axis[0] * sin_half, axis[1] * sin_half, axis[2] * sin_half, cos_half])
+
+        return cls(quat)
+
+    @classmethod
+    def from_matrix(cls, matrix: np.ndarray) -> "Rotation":
+        """
+        Create rotation from 3x3 rotation matrix.
+
+        Args:
+            matrix: 3x3 rotation matrix
+
+        Returns:
+            Rotation instance
+        """
+        matrix = np.asarray(matrix, dtype=float)
+
+        # Shepherd's method for converting rotation matrix to quaternion
+        trace = np.trace(matrix)
+
+        if trace > 0:
+            s = np.sqrt(trace + 1.0) * 2  # s = 4 * qw
+            qw = 0.25 * s
+            qx = (matrix[2, 1] - matrix[1, 2]) / s
+            qy = (matrix[0, 2] - matrix[2, 0]) / s
+            qz = (matrix[1, 0] - matrix[0, 1]) / s
+        elif matrix[0, 0] > matrix[1, 1] and matrix[0, 0] > matrix[2, 2]:
+            s = np.sqrt(1.0 + matrix[0, 0] - matrix[1, 1] - matrix[2, 2]) * 2  # s = 4 * qx
+            qw = (matrix[2, 1] - matrix[1, 2]) / s
+            qx = 0.25 * s
+            qy = (matrix[0, 1] + matrix[1, 0]) / s
+            qz = (matrix[0, 2] + matrix[2, 0]) / s
+        elif matrix[1, 1] > matrix[2, 2]:
+            s = np.sqrt(1.0 + matrix[1, 1] - matrix[0, 0] - matrix[2, 2]) * 2  # s = 4 * qy
+            qw = (matrix[0, 2] - matrix[2, 0]) / s
+            qx = (matrix[0, 1] + matrix[1, 0]) / s
+            qy = 0.25 * s
+            qz = (matrix[1, 2] + matrix[2, 1]) / s
+        else:
+            s = np.sqrt(1.0 + matrix[2, 2] - matrix[0, 0] - matrix[1, 1]) * 2  # s = 4 * qz
+            qw = (matrix[1, 0] - matrix[0, 1]) / s
+            qx = (matrix[0, 2] + matrix[2, 0]) / s
+            qy = (matrix[1, 2] + matrix[2, 1]) / s
+            qz = 0.25 * s
+
+        quat = np.array([qx, qy, qz, qw])
+        return cls(quat)
+
+    @classmethod
+    def from_quat(cls, quat: np.ndarray) -> "Rotation":
+        """
+        Create rotation from quaternion.
+
+        Args:
+            quat: Quaternion [x, y, z, w] or [w, x, y, z] (specify convention in docstring)
+                  This implementation expects [x, y, z, w] format
+
+        Returns:
+            Rotation instance
+        """
+        return cls(quat)
+
+    def as_matrix(self) -> np.ndarray:
+        """
+        Convert rotation to 3x3 rotation matrix.
+
+        Returns:
+            3x3 rotation matrix
+        """
+        qx, qy, qz, qw = self._quat
+
+        # Compute rotation matrix from quaternion
+        return np.array(
+            [
+                [1 - 2 * (qy * qy + qz * qz), 2 * (qx * qy - qz * qw), 2 * (qx * qz + qy * qw)],
+                [2 * (qx * qy + qz * qw), 1 - 2 * (qx * qx + qz * qz), 2 * (qy * qz - qx * qw)],
+                [2 * (qx * qz - qy * qw), 2 * (qy * qz + qx * qw), 1 - 2 * (qx * qx + qy * qy)],
+            ],
+            dtype=float,
+        )
+
+    def as_rotvec(self) -> np.ndarray:
+        """
+        Convert rotation to rotation vector.
+
+        Returns:
+            Rotation vector [x, y, z] where magnitude is angle in radians
+        """
+        qx, qy, qz, qw = self._quat
+
+        # Ensure qw is positive for unique representation
+        if qw < 0:
+            qx, qy, qz, qw = -qx, -qy, -qz, -qw
+
+        # Compute angle and axis
+        angle = 2.0 * np.arccos(np.clip(abs(qw), 0.0, 1.0))
+        sin_half_angle = np.sqrt(1.0 - qw * qw)
+
+        if sin_half_angle < 1e-8:
+            # For very small angles, use linearization: rotvec ≈ 2 * [qx, qy, qz]
+            return 2.0 * np.array([qx, qy, qz])
+
+        # Extract axis and scale by angle
+        axis = np.array([qx, qy, qz]) / sin_half_angle
+        return angle * axis
+
+    def as_quat(self) -> np.ndarray:
+        """
+        Get quaternion representation.
+
+        Returns:
+            Quaternion [x, y, z, w]
+        """
+        return self._quat.copy()

tests/processor/test_act_processor.py

@@ -81,8 +81,8 @@ def test_make_act_processor_basic():
     preprocessor, postprocessor = make_act_pre_post_processors(config, stats)
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 4

tests/processor/test_diffusion_processor.py

@@ -84,8 +84,8 @@ def test_make_diffusion_processor_basic():
     preprocessor, postprocessor = make_diffusion_pre_post_processors(config, stats)
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 4

tests/processor/test_pi0_processor.py

@@ -110,8 +110,8 @@ def test_make_pi0_processor_basic():
         )
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 6

tests/processor/test_sac_processor.py

@@ -86,8 +86,8 @@ def test_make_sac_processor_basic():
     )
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 4

tests/processor/test_smolvla_processor.py

@@ -117,8 +117,8 @@ def test_make_smolvla_processor_basic():
         )
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 6

tests/processor/test_tdmpc_processor.py

@@ -89,8 +89,8 @@ def test_make_tdmpc_processor_basic():
     )
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 4

tests/processor/test_vqbet_processor.py

@@ -89,8 +89,8 @@ def test_make_vqbet_processor_basic():
     )
 
     # Check processor names
-    assert preprocessor.name == "robot_preprocessor"
-    assert postprocessor.name == "robot_postprocessor"
+    assert preprocessor.name == "policy_preprocessor"
+    assert postprocessor.name == "policy_postprocessor"
 
     # Check steps in preprocessor
     assert len(preprocessor.steps) == 4