chore(processor): rename specialized processor -> XYZProcessorStep (#1852)

src/lerobot/policies/pi0/processor_pi0.py

@@ -21,7 +21,7 @@ from lerobot.configs.types import PolicyFeature
 from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.pi0.configuration_pi0 import PI0Config
 from lerobot.processor import (
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
     DataProcessorPipeline,
     DeviceProcessor,
     NormalizerProcessor,
@@ -36,7 +36,7 @@ from lerobot.processor import (
 
 
 @ProcessorStepRegistry.register(name="pi0_new_line_processor")
-class Pi0NewLineProcessor(ComplementaryDataProcessor):
+class Pi0NewLineProcessor(ComplementaryDataProcessorStep):
     """Add a new line to the end of the task if it doesn't have one.
     This is required for the PaliGemma tokenizer.
     """

src/lerobot/policies/sac/reward_model/processor_classifier.py

@@ -19,7 +19,7 @@ from lerobot.policies.sac.reward_model.configuration_classifier import RewardCla
 from lerobot.processor import (
     DataProcessorPipeline,
     DeviceProcessor,
-    IdentityProcessor,
+    IdentityProcessorStep,
     NormalizerProcessor,
     ProcessorKwargs,
 )
@@ -45,7 +45,7 @@ def make_classifier_processor(
         ),
         DeviceProcessor(device=config.device),
     ]
-    output_steps = [DeviceProcessor(device="cpu"), IdentityProcessor()]
+    output_steps = [DeviceProcessor(device="cpu"), IdentityProcessorStep()]
 
     return (
         DataProcessorPipeline(

src/lerobot/policies/smolvla/processor_smolvla.py

@@ -20,7 +20,7 @@ from lerobot.configs.types import PolicyFeature
 from lerobot.constants import POSTPROCESSOR_DEFAULT_NAME, PREPROCESSOR_DEFAULT_NAME
 from lerobot.policies.smolvla.configuration_smolvla import SmolVLAConfig
 from lerobot.processor import (
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
     DataProcessorPipeline,
     DeviceProcessor,
     NormalizerProcessor,
@@ -82,7 +82,7 @@ def make_smolvla_pre_post_processors(
 
 
 @ProcessorStepRegistry.register(name="smolvla_new_line_processor")
-class SmolVLANewLineProcessor(ComplementaryDataProcessor):
+class SmolVLANewLineProcessor(ComplementaryDataProcessorStep):
     """Add a new line to the end of the task if it doesn't have one."""
 
     def complementary_data(self, complementary_data):

src/lerobot/processor/__init__.py

@@ -39,37 +39,37 @@ from .joint_observations_processor import JointVelocityProcessor, MotorCurrentPr
 from .normalize_processor import NormalizerProcessor, UnnormalizerProcessor, hotswap_stats
 from .observation_processor import VanillaObservationProcessor
 from .pipeline import (
-    ActionProcessor,
+    ActionProcessorStep,
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
     DataProcessorPipeline,
-    DoneProcessor,
+    DoneProcessorStep,
-    IdentityProcessor,
+    IdentityProcessorStep,
-    InfoProcessor,
+    InfoProcessorStep,
-    ObservationProcessor,
+    ObservationProcessorStep,
     ProcessorKwargs,
     ProcessorStep,
     ProcessorStepRegistry,
-    RewardProcessor,
+    RewardProcessorStep,
-    TruncatedProcessor,
+    TruncatedProcessorStep,
 )
 from .rename_processor import RenameProcessor
 from .tokenizer_processor import TokenizerProcessor
 
 __all__ = [
-    "ActionProcessor",
+    "ActionProcessorStep",
     "AddTeleopActionAsComplimentaryData",
     "AddTeleopEventsAsInfo",
-    "ComplementaryDataProcessor",
+    "ComplementaryDataProcessorStep",
     "batch_to_transition",
     "create_transition",
     "DeviceProcessor",
-    "DoneProcessor",
+    "DoneProcessorStep",
     "EnvTransition",
     "GripperPenaltyProcessor",
     "hotswap_stats",
-    "IdentityProcessor",
+    "IdentityProcessorStep",
     "ImageCropResizeProcessor",
-    "InfoProcessor",
+    "InfoProcessorStep",
     "InterventionActionProcessor",
     "JointVelocityProcessor",
     "MapDeltaActionToRobotAction",
@@ -78,13 +78,13 @@ __all__ = [
     "MotorCurrentProcessor",
     "NormalizerProcessor",
     "Numpy2TorchActionProcessor",
-    "ObservationProcessor",
+    "ObservationProcessorStep",
     "ProcessorKwargs",
     "ProcessorStep",
     "ProcessorStepRegistry",
     "RenameProcessor",
     "RewardClassifierProcessor",
-    "RewardProcessor",
+    "RewardProcessorStep",
     "DataProcessorPipeline",
     "TimeLimitProcessor",
     "ToBatchProcessor",
@@ -93,7 +93,7 @@ __all__ = [
     "transition_to_batch",
     "transition_to_dataset_frame",
     "TransitionKey",
-    "TruncatedProcessor",
+    "TruncatedProcessorStep",
     "UnnormalizerProcessor",
     "VanillaObservationProcessor",
 ]

src/lerobot/processor/batch_processor.py

@@ -20,9 +20,9 @@ from lerobot.constants import OBS_ENV_STATE, OBS_IMAGE, OBS_IMAGES, OBS_STATE
 
 from .core import EnvTransition
 from .pipeline import (
-    ActionProcessor,
+    ActionProcessorStep,
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
-    ObservationProcessor,
+    ObservationProcessorStep,
     ProcessorStep,
     ProcessorStepRegistry,
 )
@@ -30,7 +30,7 @@ from .pipeline import (
 
 @dataclass
 @ProcessorStepRegistry.register(name="to_batch_processor_action")
-class ToBatchProcessorAction(ActionProcessor):
+class ToBatchProcessorAction(ActionProcessorStep):
     """Process action component in-place, adding batch dimension if needed."""
 
     def action(self, action):
@@ -45,7 +45,7 @@ class ToBatchProcessorAction(ActionProcessor):
 
 @dataclass
 @ProcessorStepRegistry.register(name="to_batch_processor_observation")
-class ToBatchProcessorObservation(ObservationProcessor):
+class ToBatchProcessorObservation(ObservationProcessorStep):
     """Process observation component in-place, adding batch dimensions where needed."""
 
     def observation(self, observation):
@@ -74,7 +74,7 @@ class ToBatchProcessorObservation(ObservationProcessor):
 
 @dataclass
 @ProcessorStepRegistry.register(name="to_batch_processor_complementary_data")
-class ToBatchProcessorComplementaryData(ComplementaryDataProcessor):
+class ToBatchProcessorComplementaryData(ComplementaryDataProcessorStep):
     """Process complementary data in-place, handling task field batching."""
 
     def complementary_data(self, complementary_data):

src/lerobot/processor/delta_action_processor.py

@@ -21,12 +21,12 @@ from torch import Tensor
 from lerobot.configs.types import FeatureType, PolicyFeature
 from lerobot.constants import ACTION
 
-from .pipeline import ActionProcessor, ProcessorStepRegistry
+from .pipeline import ActionProcessorStep, ProcessorStepRegistry
 
 
 @ProcessorStepRegistry.register("map_tensor_to_delta_action_dict")
 @dataclass
-class MapTensorToDeltaActionDict(ActionProcessor):
+class MapTensorToDeltaActionDict(ActionProcessorStep):
     """
     Map a tensor to a delta action dictionary.
     """
@@ -58,7 +58,7 @@ class MapTensorToDeltaActionDict(ActionProcessor):
 
 @ProcessorStepRegistry.register("map_delta_action_to_robot_action")
 @dataclass
-class MapDeltaActionToRobotAction(ActionProcessor):
+class MapDeltaActionToRobotAction(ActionProcessorStep):
     """
     Map delta actions from teleoperators (gamepad, keyboard) to robot target actions
     for use with inverse kinematics processors.

src/lerobot/processor/gym_action_processor.py

@@ -19,12 +19,12 @@ import torch
 from lerobot.configs.types import PolicyFeature
 
 from .converters import to_tensor
-from .pipeline import ActionProcessor, ProcessorStepRegistry
+from .pipeline import ActionProcessorStep, ProcessorStepRegistry
 
 
 @ProcessorStepRegistry.register("torch2numpy_action_processor")
 @dataclass
-class Torch2NumpyActionProcessor(ActionProcessor):
+class Torch2NumpyActionProcessor(ActionProcessorStep):
     """Convert PyTorch tensor actions to NumPy arrays."""
 
     squeeze_batch_dim: bool = True
@@ -56,7 +56,7 @@ class Torch2NumpyActionProcessor(ActionProcessor):
 
 @ProcessorStepRegistry.register("numpy2torch_action_processor")
 @dataclass
-class Numpy2TorchActionProcessor(ActionProcessor):
+class Numpy2TorchActionProcessor(ActionProcessorStep):
     """Convert NumPy array action to PyTorch tensor."""
 
     def action(self, action: np.ndarray) -> torch.Tensor:

src/lerobot/processor/hil_processor.py

@@ -14,12 +14,12 @@ from lerobot.teleoperators.utils import TeleopEvents
 
 from .core import EnvTransition, TransitionKey
 from .pipeline import (
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
-    InfoProcessor,
+    InfoProcessorStep,
-    ObservationProcessor,
+    ObservationProcessorStep,
     ProcessorStep,
     ProcessorStepRegistry,
-    TruncatedProcessor,
+    TruncatedProcessorStep,
 )
 
 GRIPPER_KEY = "gripper"
@@ -29,7 +29,7 @@ TELEOP_ACTION_KEY = "teleop_action"
 
 @ProcessorStepRegistry.register("add_teleop_action_as_complementary_data")
 @dataclass
-class AddTeleopActionAsComplimentaryData(ComplementaryDataProcessor):
+class AddTeleopActionAsComplimentaryData(ComplementaryDataProcessorStep):
     """Add teleoperator action to transition complementary data."""
 
     teleop_device: Teleoperator
@@ -45,7 +45,7 @@ class AddTeleopActionAsComplimentaryData(ComplementaryDataProcessor):
 
 @ProcessorStepRegistry.register("add_teleop_action_as_info")
 @dataclass
-class AddTeleopEventsAsInfo(InfoProcessor):
+class AddTeleopEventsAsInfo(InfoProcessorStep):
     """Add teleoperator control events to transition info."""
 
     teleop_device: Teleoperator
@@ -62,7 +62,7 @@ class AddTeleopEventsAsInfo(InfoProcessor):
 
 @ProcessorStepRegistry.register("image_crop_resize_processor")
 @dataclass
-class ImageCropResizeProcessor(ObservationProcessor):
+class ImageCropResizeProcessor(ObservationProcessorStep):
     """Crop and resize image observations."""
 
     crop_params_dict: dict[str, tuple[int, int, int, int]] | None = None
@@ -112,7 +112,7 @@ class ImageCropResizeProcessor(ObservationProcessor):
 
 @dataclass
 @ProcessorStepRegistry.register("time_limit_processor")
-class TimeLimitProcessor(TruncatedProcessor):
+class TimeLimitProcessor(TruncatedProcessorStep):
     """Track episode steps and enforce time limits."""
 
     max_episode_steps: int
@@ -139,7 +139,7 @@ class TimeLimitProcessor(TruncatedProcessor):
 
 @dataclass
 @ProcessorStepRegistry.register("gripper_penalty_processor")
-class GripperPenaltyProcessor(ComplementaryDataProcessor):
+class GripperPenaltyProcessor(ComplementaryDataProcessorStep):
     """Apply penalty for inappropriate gripper usage."""
 
     penalty: float = -0.01

src/lerobot/processor/joint_observations_processor.py

@@ -6,7 +6,7 @@ import torch
 from lerobot.configs.types import PolicyFeature
 from lerobot.constants import OBS_STATE
 from lerobot.processor.pipeline import (
-    ObservationProcessor,
+    ObservationProcessorStep,
     ProcessorStepRegistry,
 )
 from lerobot.robots import Robot
@@ -14,7 +14,7 @@ from lerobot.robots import Robot
 
 @dataclass
 @ProcessorStepRegistry.register("joint_velocity_processor")
-class JointVelocityProcessor(ObservationProcessor):
+class JointVelocityProcessor(ObservationProcessorStep):
     """Add joint velocity information to observations."""
 
     dt: float = 0.1
@@ -67,7 +67,7 @@ class JointVelocityProcessor(ObservationProcessor):
 
 @dataclass
 @ProcessorStepRegistry.register("current_processor")
-class MotorCurrentProcessor(ObservationProcessor):
+class MotorCurrentProcessor(ObservationProcessorStep):
     """Add motor current information to observations."""
 
     robot: Robot | None = None

src/lerobot/processor/observation_processor.py

@@ -23,12 +23,12 @@ from torch import Tensor
 from lerobot.configs.types import PolicyFeature
 from lerobot.constants import OBS_ENV_STATE, OBS_IMAGE, OBS_IMAGES, OBS_STATE
 
-from .pipeline import ObservationProcessor, ProcessorStepRegistry
+from .pipeline import ObservationProcessorStep, ProcessorStepRegistry
 
 
 @dataclass
 @ProcessorStepRegistry.register(name="observation_processor")
-class VanillaObservationProcessor(ObservationProcessor):
+class VanillaObservationProcessor(ObservationProcessorStep):
     """
     Processes environment observations into the LeRobot format by handling both images and states.
 

src/lerobot/processor/pipeline.py

@@ -805,7 +805,7 @@ class DataProcessorPipeline(ModelHubMixin, Generic[TOutput]):
         return transformed_transition[TransitionKey.COMPLEMENTARY_DATA]
 
 
-class ObservationProcessor(ProcessorStep, ABC):
+class ObservationProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the observation component of a transition.
 
     Subclasses should override the `observation` method to implement custom observation processing.
@@ -851,7 +851,7 @@ class ObservationProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class ActionProcessor(ProcessorStep, ABC):
+class ActionProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the action component of a transition.
 
     Subclasses should override the `action` method to implement custom action processing.
@@ -898,7 +898,7 @@ class ActionProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class RewardProcessor(ProcessorStep, ABC):
+class RewardProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the reward component of a transition.
 
     Subclasses should override the `reward` method to implement custom reward processing.
@@ -944,7 +944,7 @@ class RewardProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class DoneProcessor(ProcessorStep, ABC):
+class DoneProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the done flag of a transition.
 
     Subclasses should override the `done` method to implement custom done flag processing.
@@ -995,7 +995,7 @@ class DoneProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class TruncatedProcessor(ProcessorStep, ABC):
+class TruncatedProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the truncated flag of a transition.
 
     Subclasses should override the `truncated` method to implement custom truncated flag processing.
@@ -1042,7 +1042,7 @@ class TruncatedProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class InfoProcessor(ProcessorStep, ABC):
+class InfoProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the info dictionary of a transition.
 
     Subclasses should override the `info` method to implement custom info processing.
@@ -1094,7 +1094,7 @@ class InfoProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class ComplementaryDataProcessor(ProcessorStep, ABC):
+class ComplementaryDataProcessorStep(ProcessorStep, ABC):
     """Base class for processors that modify only the complementary data of a transition.
 
     Subclasses should override the `complementary_data` method to implement custom complementary data processing.
@@ -1127,7 +1127,7 @@ class ComplementaryDataProcessor(ProcessorStep, ABC):
         return new_transition
 
 
-class IdentityProcessor(ProcessorStep):
+class IdentityProcessorStep(ProcessorStep):
     """Identity processor that does nothing."""
 
     def __call__(self, transition: EnvTransition) -> EnvTransition:

src/lerobot/processor/rename_processor.py

@@ -19,12 +19,12 @@ from typing import Any
 
 from lerobot.configs.types import PolicyFeature
 
-from .pipeline import ObservationProcessor, ProcessorStepRegistry
+from .pipeline import ObservationProcessorStep, ProcessorStepRegistry
 
 
 @dataclass
 @ProcessorStepRegistry.register(name="rename_processor")
-class RenameProcessor(ObservationProcessor):
+class RenameProcessor(ObservationProcessorStep):
     """Rename processor that renames keys in the observation."""
 
     rename_map: dict[str, str] = field(default_factory=dict)

src/lerobot/processor/tokenizer_processor.py

@@ -14,7 +14,7 @@ from lerobot.constants import OBS_LANGUAGE_ATTENTION_MASK, OBS_LANGUAGE_TOKENS
 from lerobot.utils.import_utils import _transformers_available
 
 from .core import EnvTransition, TransitionKey
-from .pipeline import ObservationProcessor, ProcessorStepRegistry
+from .pipeline import ObservationProcessorStep, ProcessorStepRegistry
 
 if TYPE_CHECKING or _transformers_available:
     from transformers import AutoTokenizer
@@ -24,7 +24,7 @@ else:
 
 @dataclass
 @ProcessorStepRegistry.register(name="tokenizer_processor")
-class TokenizerProcessor(ObservationProcessor):
+class TokenizerProcessor(ObservationProcessorStep):
     """Tokenizes text tasks in complementary data using a huggingface tokenizer.
 
     This processor handles tokenization of task strings found in the complementary_data

src/lerobot/record.py

@@ -76,7 +76,7 @@ from lerobot.datasets.utils import hw_to_dataset_features
 from lerobot.datasets.video_utils import VideoEncodingManager
 from lerobot.policies.factory import make_policy, make_pre_post_processors
 from lerobot.policies.pretrained import PreTrainedPolicy
-from lerobot.processor import DataProcessorPipeline, IdentityProcessor, TransitionKey
+from lerobot.processor import DataProcessorPipeline, IdentityProcessorStep, TransitionKey
 from lerobot.processor.converters import (
     to_output_robot_action,
     to_transition_robot_observation,
@@ -245,13 +245,15 @@ def record_loop(
     display_data: bool = False,
 ):
     teleop_action_processor = teleop_action_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()], to_transition=to_transition_teleop_action, to_output=lambda tr: tr
+        steps=[IdentityProcessorStep()], to_transition=to_transition_teleop_action, to_output=lambda tr: tr
     )
     robot_action_processor = robot_action_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()], to_transition=lambda tr: tr, to_output=to_output_robot_action
+        steps=[IdentityProcessorStep()], to_transition=lambda tr: tr, to_output=to_output_robot_action
     )
     robot_observation_processor = robot_observation_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()], to_transition=to_transition_robot_observation, to_output=lambda tr: tr
+        steps=[IdentityProcessorStep()],
+        to_transition=to_transition_robot_observation,
+        to_output=lambda tr: tr,
     )
 
     if dataset is not None and dataset.fps != fps:

src/lerobot/replay.py

@@ -47,7 +47,7 @@ from pprint import pformat
 
 from lerobot.configs import parser
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
-from lerobot.processor import DataProcessorPipeline, IdentityProcessor
+from lerobot.processor import DataProcessorPipeline, IdentityProcessorStep
 from lerobot.processor.converters import to_output_robot_action, to_transition_teleop_action
 from lerobot.robots import (  # noqa: F401
     Robot,
@@ -95,7 +95,7 @@ def replay(cfg: ReplayConfig):
 
     # Initialize robot action processor with default if not provided
     robot_action_processor = cfg.robot_action_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()],
+        steps=[IdentityProcessorStep()],
         to_transition=to_transition_teleop_action,
         to_output=to_output_robot_action,  # type: ignore[arg-type]
     )

src/lerobot/robots/so100_follower/robot_kinematic_processor.py

@@ -23,10 +23,10 @@ from lerobot.configs.types import FeatureType, PolicyFeature
 from lerobot.constants import ACTION, OBS_STATE
 from lerobot.model.kinematics import RobotKinematics
 from lerobot.processor import (
-    ActionProcessor,
+    ActionProcessorStep,
-    ComplementaryDataProcessor,
+    ComplementaryDataProcessorStep,
     EnvTransition,
-    ObservationProcessor,
+    ObservationProcessorStep,
     ProcessorStep,
     ProcessorStepRegistry,
     TransitionKey,
@@ -36,7 +36,7 @@ from lerobot.robots.robot import Robot
 
 @ProcessorStepRegistry.register("ee_reference_and_delta")
 @dataclass
-class EEReferenceAndDelta(ActionProcessor):
+class EEReferenceAndDelta(ActionProcessorStep):
     """
     Compute the desired end-effector pose from the target pose and the current pose.
 
@@ -159,7 +159,7 @@ class EEReferenceAndDelta(ActionProcessor):
 
 @ProcessorStepRegistry.register("ee_bounds_and_safety")
 @dataclass
-class EEBoundsAndSafety(ActionProcessor):
+class EEBoundsAndSafety(ActionProcessorStep):
     """
     Clip the end-effector pose to the bounds and check for jumps.
 
@@ -389,7 +389,7 @@ class GripperVelocityToJoint(ProcessorStep):
 
 @ProcessorStepRegistry.register("forward_kinematics_joints_to_ee")
 @dataclass
-class ForwardKinematicsJointsToEE(ObservationProcessor):
+class ForwardKinematicsJointsToEE(ObservationProcessorStep):
     """
     Compute the end-effector pose from the joint positions.
 
@@ -433,7 +433,7 @@ class ForwardKinematicsJointsToEE(ObservationProcessor):
 
 @ProcessorStepRegistry.register("add_robot_observation")
 @dataclass
-class AddRobotObservationAsComplimentaryData(ComplementaryDataProcessor):
+class AddRobotObservationAsComplimentaryData(ComplementaryDataProcessorStep):
     """
     Read the robot's current observation and insert it into the transition as complementary data.
 

src/lerobot/teleoperate.py

@@ -61,7 +61,7 @@ import rerun as rr
 from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig  # noqa: F401
 from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig  # noqa: F401
 from lerobot.configs import parser
-from lerobot.processor import DataProcessorPipeline, IdentityProcessor
+from lerobot.processor import DataProcessorPipeline, IdentityProcessorStep
 from lerobot.processor.converters import (
     to_output_robot_action,
     to_transition_robot_observation,
@@ -121,15 +121,17 @@ def teleop_loop(
 ):
     # Initialize processors with defaults if not provided
     teleop_action_processor = teleop_action_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()], to_transition=to_transition_teleop_action, to_output=lambda tr: tr
+        steps=[IdentityProcessorStep()], to_transition=to_transition_teleop_action, to_output=lambda tr: tr
     )
     robot_action_processor = robot_action_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()],
+        steps=[IdentityProcessorStep()],
         to_transition=lambda tr: tr,
         to_output=to_output_robot_action,  # type: ignore[arg-type]
     )
     robot_observation_processor = robot_observation_processor or DataProcessorPipeline(
-        steps=[IdentityProcessor()], to_transition=to_transition_robot_observation, to_output=lambda tr: tr
+        steps=[IdentityProcessorStep()],
+        to_transition=to_transition_robot_observation,
+        to_output=lambda tr: tr,
     )
 
     # Reset processors

src/lerobot/teleoperators/phone/phone_processor.py

@@ -18,13 +18,13 @@ from dataclasses import dataclass, field
 
 from lerobot.configs.types import FeatureType, PolicyFeature
 from lerobot.constants import ACTION
-from lerobot.processor import ActionProcessor, ProcessorStepRegistry
+from lerobot.processor import ActionProcessorStep, ProcessorStepRegistry
 from lerobot.teleoperators.phone.config_phone import PhoneOS
 
 
 @ProcessorStepRegistry.register("map_phone_action_to_robot_action")
 @dataclass
-class MapPhoneActionToRobotAction(ActionProcessor):
+class MapPhoneActionToRobotAction(ActionProcessorStep):
     """
     Map calibrated phone pose (actions) to the inputs for robot actions
 

tests/processor/test_classifier_processor.py

@@ -27,7 +27,7 @@ from lerobot.policies.sac.reward_model.processor_classifier import make_classifi
 from lerobot.processor import (
     DataProcessorPipeline,
     DeviceProcessor,
-    IdentityProcessor,
+    IdentityProcessorStep,
     NormalizerProcessor,
     TransitionKey,
 )
@@ -94,7 +94,7 @@ def test_make_classifier_processor_basic():
     # Check steps in postprocessor
     assert len(postprocessor.steps) == 2
     assert isinstance(postprocessor.steps[0], DeviceProcessor)
-    assert isinstance(postprocessor.steps[1], IdentityProcessor)
+    assert isinstance(postprocessor.steps[1], IdentityProcessorStep)
 
 
 def test_classifier_processor_normalization():

tests/processor/test_normalize_processor.py

@@ -22,7 +22,7 @@ import torch
 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
 from lerobot.processor import (
     DataProcessorPipeline,
-    IdentityProcessor,
+    IdentityProcessorStep,
     NormalizerProcessor,
     TransitionKey,
     UnnormalizerProcessor,
@@ -1008,7 +1008,7 @@ def test_hotswap_stats_basic_functionality():
     # Create processors
     normalizer = NormalizerProcessor(features=features, norm_map=norm_map, stats=initial_stats)
     unnormalizer = UnnormalizerProcessor(features=features, norm_map=norm_map, stats=initial_stats)
-    identity = IdentityProcessor()
+    identity = IdentityProcessorStep()
 
     # Create robot processor
     robot_processor = DataProcessorPipeline(steps=[normalizer, unnormalizer, identity])
@@ -1089,7 +1089,7 @@ def test_hotswap_stats_only_affects_normalizer_steps():
     # Create mixed steps
     normalizer = NormalizerProcessor(features=features, norm_map=norm_map, stats=stats)
     unnormalizer = UnnormalizerProcessor(features=features, norm_map=norm_map, stats=stats)
-    identity = IdentityProcessor()
+    identity = IdentityProcessorStep()
 
     robot_processor = DataProcessorPipeline(steps=[normalizer, identity, unnormalizer])
 
@@ -1135,7 +1135,7 @@ def test_hotswap_stats_no_normalizer_steps():
     }
 
     # Create processor with only identity steps
-    robot_processor = DataProcessorPipeline(steps=[IdentityProcessor(), IdentityProcessor()])
+    robot_processor = DataProcessorPipeline(steps=[IdentityProcessorStep(), IdentityProcessorStep()])
 
     # Hotswap stats - should work without error
     new_processor = hotswap_stats(robot_processor, stats)