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fix: remove leftover normalization calls from reward classifier predict_reward
Fixes #2355
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@@ -268,10 +268,6 @@ class Classifier(PreTrainedPolicy):
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def predict_reward(self, batch, threshold=0.5):
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def predict_reward(self, batch, threshold=0.5):
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"""Eval method. Returns predicted reward with the decision threshold as argument."""
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"""Eval method. Returns predicted reward with the decision threshold as argument."""
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# Check for both OBS_IMAGE and OBS_IMAGES prefixes
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batch = self.normalize_inputs(batch)
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batch = self.normalize_targets(batch)
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# Extract images from batch dict
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# Extract images from batch dict
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images = [batch[key] for key in self.config.input_features if key.startswith(OBS_IMAGE)]
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images = [batch[key] for key in self.config.input_features if key.startswith(OBS_IMAGE)]
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