refactor(classifier): remove redundant input normalization in predict_reward method

src/lerobot/rewards/classifier/modeling_classifier.py

@@ -276,10 +276,6 @@ class Classifier(PreTrainedRewardModel):
 
     def predict_reward(self, batch, threshold=0.5):
         """Eval method. Returns predicted reward with the decision threshold as argument."""
-        # Check for both OBS_IMAGE and OBS_IMAGES prefixes
-        batch = self.normalize_inputs(batch)
-        batch = self.normalize_targets(batch)
-
         # Extract images from batch dict
         images = [batch[key] for key in self.config.input_features if key.startswith(OBS_IMAGE)]