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chore(processor): add Step suffix to all processors (#1854)

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* refactor(processor): rename MapDeltaActionToRobotAction and MapTensorToDeltaActionDict for consistency

* refactor(processor): rename DeviceProcessor to DeviceProcessorStep for consistency across modules

* refactor(processor): rename Torch2NumpyActionProcessor to Torch2NumpyActionProcessorStep for consistency

* refactor(processor): rename Numpy2TorchActionProcessor to Numpy2TorchActionProcessorStep for consistency

* refactor(processor): rename AddTeleopActionAsComplimentaryData to AddTeleopActionAsComplimentaryDataStep for consistency

* refactor(processor): rename ImageCropResizeProcessor and AddTeleopEventsAsInfo for consistency

* refactor(processor): rename TimeLimitProcessor to TimeLimitProcessorStep for consistency

* refactor(processor): rename GripperPenaltyProcessor to GripperPenaltyProcessorStep for consistency

* refactor(processor): rename InterventionActionProcessor to InterventionActionProcessorStep for consistency

* refactor(processor): rename RewardClassifierProcessor to RewardClassifierProcessorStep for consistency

* refactor(processor): rename JointVelocityProcessor to JointVelocityProcessorStep for consistency

* refactor(processor): rename MotorCurrentProcessor to MotorCurrentProcessorStep for consistency

* refactor(processor): rename NormalizerProcessor and UnnormalizerProcessor to NormalizerProcessorStep and UnnormalizerProcessorStep for consistency

* refactor(processor): rename VanillaObservationProcessor to VanillaObservationProcessorStep for consistency

* refactor(processor): rename RenameProcessor to RenameProcessorStep for consistency

* refactor(processor): rename TokenizerProcessor to TokenizerProcessorStep for consistency

* refactor(processor): rename ToBatchProcessor to AddBatchDimensionProcessorStep for consistency

* refactor(processor): update config file name in test for RenameProcessorStep consistency
This commit is contained in:
Adil Zouitine
2025-09-03 18:12:11 +02:00
committed by GitHub
parent 029c4a9a76
commit ce793cde64
37 changed files with 653 additions and 628 deletions
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tests/processor/test_observation_processor.py
+25 -25
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@@ -20,7 +20,7 @@ import torch
from lerobot.configs.types import FeatureType
from lerobot.constants import OBS_ENV_STATE, OBS_IMAGE, OBS_IMAGES, OBS_STATE
from lerobot.processor import TransitionKey, VanillaObservationProcessor
from lerobot.processor import TransitionKey, VanillaObservationProcessorStep
from tests.conftest import assert_contract_is_typed
@@ -41,7 +41,7 @@ def create_transition(
def test_process_single_image():
"""Test processing a single image."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create a mock image (H, W, C) format, uint8
image = np.random.randint(0, 256, size=(64, 64, 3), dtype=np.uint8)
@@ -67,7 +67,7 @@ def test_process_single_image():
def test_process_image_dict():
"""Test processing multiple images in a dictionary."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create mock images
image1 = np.random.randint(0, 256, size=(32, 32, 3), dtype=np.uint8)
@@ -90,7 +90,7 @@ def test_process_image_dict():
def test_process_batched_image():
"""Test processing already batched images."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create a batched image (B, H, W, C)
image = np.random.randint(0, 256, size=(2, 64, 64, 3), dtype=np.uint8)
@@ -107,7 +107,7 @@ def test_process_batched_image():
def test_invalid_image_format():
"""Test error handling for invalid image formats."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Test wrong channel order (channels first)
image = np.random.randint(0, 256, size=(3, 64, 64), dtype=np.uint8)
@@ -120,7 +120,7 @@ def test_invalid_image_format():
def test_invalid_image_dtype():
"""Test error handling for invalid image dtype."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Test wrong dtype
image = np.random.rand(64, 64, 3).astype(np.float32)
@@ -133,7 +133,7 @@ def test_invalid_image_dtype():
def test_no_pixels_in_observation():
"""Test processor when no pixels are in observation."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
observation = {"other_data": np.array([1, 2, 3])}
transition = create_transition(observation=observation)
@@ -148,7 +148,7 @@ def test_no_pixels_in_observation():
def test_none_observation():
"""Test processor with None observation."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
transition = create_transition()
result = processor(transition)
@@ -158,7 +158,7 @@ def test_none_observation():
def test_serialization_methods():
"""Test serialization methods."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Test get_config
config = processor.get_config()
@@ -177,7 +177,7 @@ def test_serialization_methods():
def test_process_environment_state():
"""Test processing environment_state."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
env_state = np.array([1.0, 2.0, 3.0], dtype=np.float32)
observation = {"environment_state": env_state}
@@ -198,7 +198,7 @@ def test_process_environment_state():
def test_process_agent_pos():
"""Test processing agent_pos."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
agent_pos = np.array([0.5, -0.5, 1.0], dtype=np.float32)
observation = {"agent_pos": agent_pos}
@@ -219,7 +219,7 @@ def test_process_agent_pos():
def test_process_batched_states():
"""Test processing already batched states."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
env_state = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
agent_pos = np.array([[0.5, -0.5], [1.0, -1.0]], dtype=np.float32)
@@ -237,7 +237,7 @@ def test_process_batched_states():
def test_process_both_states():
"""Test processing both environment_state and agent_pos."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
env_state = np.array([1.0, 2.0], dtype=np.float32)
agent_pos = np.array([0.5, -0.5], dtype=np.float32)
@@ -262,7 +262,7 @@ def test_process_both_states():
def test_no_states_in_observation():
"""Test processor when no states are in observation."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
observation = {"other_data": np.array([1, 2, 3])}
transition = create_transition(observation=observation)
@@ -276,7 +276,7 @@ def test_no_states_in_observation():
def test_complete_observation_processing():
"""Test processing a complete observation with both images and states."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create mock data
image = np.random.randint(0, 256, size=(32, 32, 3), dtype=np.uint8)
@@ -313,7 +313,7 @@ def test_complete_observation_processing():
def test_image_only_processing():
"""Test processing observation with only images."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
image = np.random.randint(0, 256, size=(64, 64, 3), dtype=np.uint8)
observation = {"pixels": image}
@@ -328,7 +328,7 @@ def test_image_only_processing():
def test_state_only_processing():
"""Test processing observation with only states."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
agent_pos = np.array([1.0, 2.0], dtype=np.float32)
observation = {"agent_pos": agent_pos}
@@ -343,7 +343,7 @@ def test_state_only_processing():
def test_empty_observation():
"""Test processing empty observation."""
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
observation = {}
transition = create_transition(observation=observation)
@@ -359,7 +359,7 @@ def test_equivalent_to_original_function():
# Import the original function for comparison
from lerobot.envs.utils import preprocess_observation
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create test data similar to what the original function expects
image = np.random.randint(0, 256, size=(64, 64, 3), dtype=np.uint8)
@@ -386,7 +386,7 @@ def test_equivalent_with_image_dict():
"""Test equivalence with dictionary of images."""
from lerobot.envs.utils import preprocess_observation
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
# Create test data with multiple cameras
image1 = np.random.randint(0, 256, size=(32, 32, 3), dtype=np.uint8)
@@ -410,7 +410,7 @@ def test_equivalent_with_image_dict():
def test_image_processor_features_pixels_to_image(policy_feature_factory):
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
features = {
"pixels": policy_feature_factory(FeatureType.VISUAL, (3, 64, 64)),
"keep": policy_feature_factory(FeatureType.ENV, (1,)),
@@ -424,7 +424,7 @@ def test_image_processor_features_pixels_to_image(policy_feature_factory):
def test_image_processor_features_observation_pixels_to_image(policy_feature_factory):
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
features = {
"observation.pixels": policy_feature_factory(FeatureType.VISUAL, (3, 64, 64)),
"keep": policy_feature_factory(FeatureType.ENV, (1,)),
@@ -438,7 +438,7 @@ def test_image_processor_features_observation_pixels_to_image(policy_feature_fac
def test_image_processor_features_multi_camera_and_prefixed(policy_feature_factory):
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
features = {
"pixels.front": policy_feature_factory(FeatureType.VISUAL, (3, 64, 64)),
"pixels.wrist": policy_feature_factory(FeatureType.VISUAL, (3, 64, 64)),
@@ -456,7 +456,7 @@ def test_image_processor_features_multi_camera_and_prefixed(policy_feature_facto
def test_state_processor_features_environment_and_agent_pos(policy_feature_factory):
processor = VanillaObservationProcessor()
processor = VanillaObservationProcessorStep()
features = {
"environment_state": policy_feature_factory(FeatureType.STATE, (3,)),
"agent_pos": policy_feature_factory(FeatureType.STATE, (7,)),
@@ -472,7 +472,7 @@ def test_state_processor_features_environment_and_agent_pos(policy_feature_facto
def test_state_processor_features_prefixed_inputs(policy_feature_factory):
proc = VanillaObservationProcessor()
proc = VanillaObservationProcessorStep()
features = {
"observation.environment_state": policy_feature_factory(FeatureType.STATE, (2,)),
"observation.agent_pos": policy_feature_factory(FeatureType.STATE, (4,)),