refactor(tests): streamline transition creation in processor tests

- Replaced custom transition creation functions with a centralized `create_transition` function imported from converters across multiple test files.
- Updated test cases to utilize keyword arguments for better readability and maintainability, ensuring consistent transition creation throughout the test suite.

tests/processor/test_device_processor.py

@@ -20,28 +20,7 @@ import torch
 
 from lerobot.configs.types import FeatureType, PipelineFeatureType, PolicyFeature
 from lerobot.processor import DataProcessorPipeline, DeviceProcessorStep, TransitionKey
-
-
-def create_transition(
-    observation=None, action=None, reward=None, done=None, truncated=None, info=None, complementary_data=None
-):
-    """Helper function to create a transition dictionary."""
-    transition = {}
-    if observation is not None:
-        transition[TransitionKey.OBSERVATION] = observation
-    if action is not None:
-        transition[TransitionKey.ACTION] = action
-    if reward is not None:
-        transition[TransitionKey.REWARD] = reward
-    if done is not None:
-        transition[TransitionKey.DONE] = done
-    if truncated is not None:
-        transition[TransitionKey.TRUNCATED] = truncated
-    if info is not None:
-        transition[TransitionKey.INFO] = info
-    if complementary_data is not None:
-        transition[TransitionKey.COMPLEMENTARY_DATA] = complementary_data
-    return transition
+from lerobot.processor.converters import create_transition
 
 
 def test_basic_functionality():
@@ -147,14 +126,14 @@ def test_none_values():
     # Test with None observation
     transition = create_transition(observation=None, action=torch.randn(5))
     result = processor(transition)
-    assert TransitionKey.OBSERVATION not in result
+    assert result[TransitionKey.OBSERVATION] is None
     assert result[TransitionKey.ACTION].device.type == "cpu"
 
     # Test with None action
     transition = create_transition(observation={"observation.state": torch.randn(10)}, action=None)
     result = processor(transition)
     assert result[TransitionKey.OBSERVATION]["observation.state"].device.type == "cpu"
-    assert TransitionKey.ACTION not in result
+    assert result[TransitionKey.ACTION] is None
 
 
 def test_empty_observation():
@@ -822,8 +801,8 @@ def test_complementary_data_none():
 
     result = processor(transition)
 
-    # Complementary data should not be in the result (same as input)
-    assert TransitionKey.COMPLEMENTARY_DATA not in result
+    # Complementary data should be an empty dict (standardized behavior)
+    assert result[TransitionKey.COMPLEMENTARY_DATA] == {}
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")