def __init__(self, scale: float = 0.2, apply_fit: bool = False, apply_predict: bool = True) -> None:
        """
        Create a GaussianNoise postprocessor.

        :param scale: Standard deviation of the distribution.
        :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.scale = scale
        self._check_params()

        Create a GaussianNoise postprocessor.

        :param scale: Standard deviation of the distribution.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        
art/defences/postprocessor/gaussian_noise.py