def __init__(
        self,
        clip_values: CLIP_VALUES_TYPE,
        bit_depth: int = 8,
        apply_fit: bool = False,
        apply_predict: bool = True,
    ) -> None:
        """
        Create an instance of feature squeezing.

        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
               for features.
        :param bit_depth: The number of bits per channel for encoding the data.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        """
        super().__init__(is_fitted=True, apply_fit=apply_fit, apply_predict=apply_predict)
        self.clip_values = clip_values
        self.bit_depth = bit_depth
        self._check_params()

        Create an instance of feature squeezing.

        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
               for features.
        :param bit_depth: The number of bits per channel for encoding the data.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        
art/defences/preprocessor/feature_squeezing.py