chore: enable simplify in ruff lint (#2085)

src/lerobot/processor/hil_processor.py

@@ -340,7 +340,7 @@ class GripperPenaltyProcessorStep(ComplementaryDataProcessorStep):
         """
         action = self.transition.get(TransitionKey.ACTION)
 
-        raw_joint_positions = complementary_data.get("raw_joint_positions", None)
+        raw_joint_positions = complementary_data.get("raw_joint_positions")
         if raw_joint_positions is None:
             return complementary_data
 

src/lerobot/processor/normalize_processor.py

@@ -119,13 +119,12 @@ class _NormalizationMixin:
                     )
                 self.features = reconstructed
 
-        if self.norm_map:
-            # if keys are strings (JSON), rebuild enum map
-            if all(isinstance(k, str) for k in self.norm_map.keys()):
-                reconstructed = {}
-                for ft_type_str, norm_mode_str in self.norm_map.items():
-                    reconstructed[FeatureType(ft_type_str)] = NormalizationMode(norm_mode_str)
-                self.norm_map = reconstructed
+        # if keys are strings (JSON), rebuild enum map
+        if self.norm_map and all(isinstance(k, str) for k in self.norm_map):
+            reconstructed = {}
+            for ft_type_str, norm_mode_str in self.norm_map.items():
+                reconstructed[FeatureType(ft_type_str)] = NormalizationMode(norm_mode_str)
+            self.norm_map = reconstructed
 
         # Convert stats to tensors and move to the target device once during initialization.
         self.stats = self.stats or {}

src/lerobot/processor/observation_processor.py

@@ -152,7 +152,7 @@ class VanillaObservationProcessorStep(ObservationProcessorStep):
         """
         # Build a new features mapping keyed by the same FeatureType buckets
         # We assume callers already placed features in the correct FeatureType.
-        new_features: dict[PipelineFeatureType, dict[str, PolicyFeature]] = {ft: {} for ft in features.keys()}
+        new_features: dict[PipelineFeatureType, dict[str, PolicyFeature]] = {ft: {} for ft in features}
 
         exact_pairs = {
             "pixels": OBS_IMAGE,