def __init__(
        self,
        nb_samples: int,
        clip_values: tuple[float, float],
        contrast_factor: float | tuple[float, float],
        apply_fit: bool = False,
        apply_predict: bool = True,
    ) -> None:
        """
        Create an instance of EoTContrastTensorFlow.

        :param nb_samples: Number of random samples per input sample.
        :param clip_values: Tuple of float representing minimum and maximum values of input `(min, max)`.
        :param contrast_factor: Range to sample the contrast factor adjust the contrast. A single float is translated to
               range [-delta, delta] or a tuple of floats is used to create sampling range [delta[0], delta[1]]. The
               applied delta is sampled uniformly from this range for each image.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        """
        super().__init__(
            apply_fit=apply_fit, apply_predict=apply_predict, nb_samples=nb_samples, clip_values=clip_values
        )

        self.contrast_factor = contrast_factor
        self.contrast_factor_range = (
            (0, contrast_factor) if isinstance(contrast_factor, (int, float)) else contrast_factor
        )
        self._check_params()

        Create an instance of EoTContrastTensorFlow.

        :param nb_samples: Number of random samples per input sample.
        :param clip_values: Tuple of float representing minimum and maximum values of input `(min, max)`.
        :param contrast_factor: Range to sample the contrast factor adjust the contrast. A single float is translated to
               range [-delta, delta] or a tuple of floats is used to create sampling range [delta[0], delta[1]]. The
               applied delta is sampled uniformly from this range for each image.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        
art/preprocessing/expectation_over_transformation/natural_corruptions/contrast/tensorflow.py