src/transformers/models/mctct/feature_extraction_mctct.py/MCTCTFeatureExtractor/normalize
class MCTCTFeatureExtractor:    def normalize(
        self, input_features: List[np.ndarray], attention_mask: Optional[np.ndarray] = None
    ) -> List[np.ndarray]:
        lengths = attention_mask.sum(-1) if attention_mask is not None else [x.shape[0] for x in input_features]
        return [self._normalize_one(x, n, self.padding_value) for x, n in zip(input_features, lengths)]