def __init__(
        self,
        nb_samples: int,
        clip_values: tuple[float, float],
        angles: float | tuple[float, float] = 45.0,
        label_type: str = "classification",
        apply_fit: bool = False,
        apply_predict: bool = True,
    ) -> None:
        """
        Create an instance of EoTImageRotationTensorFlow.

        :param nb_samples: Number of random samples per input sample.
        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
                            for features.
        :param angles: A positive scalar angle in degrees defining the uniform sampling range from negative to
                       positive angles_range.
        :param label_type: String defining the type of labels. Currently supported: `classification`
        :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.angles = angles
        self.angles_range = (-angles, angles) if isinstance(angles, (int, float)) else angles
        self.label_type = label_type
        self._check_params()

        Create an instance of EoTImageRotationTensorFlow.

        :param nb_samples: Number of random samples per input sample.
        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
                            for features.
        :param angles: A positive scalar angle in degrees defining the uniform sampling range from negative to
                       positive angles_range.
        :param label_type: String defining the type of labels. Currently supported: `classification`
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        
art/preprocessing/expectation_over_transformation/image_rotation/tensorflow.py