def __init__(
        self,
        classifier: "CLASSIFIER_NEURALNETWORK_TYPE",
        th: int | None = None,
        es: int = 1,
        max_iter: int = 100,
        targeted: bool = False,
        verbose: bool = False,
    ) -> None:
        """
        Create a :class:`.PixelAttack` instance.

        :param classifier: A trained classifier.
        :param th: threshold value of the Pixel/ Threshold attack. th=None indicates finding a minimum threshold.
        :param es: Indicates whether the attack uses CMAES (0) or DE (1) as Evolutionary Strategy.
        :param max_iter: Sets the Maximum iterations to run the Evolutionary Strategies for optimisation.
        :param targeted: Indicates whether the attack is targeted (True) or untargeted (False).
        :param verbose: Indicates whether to print verbose messages of ES used.
        """
        super().__init__(classifier, th, es, max_iter, targeted, verbose)
        self.type_attack = 0

        Create a :class:`.PixelAttack` instance.

        :param classifier: A trained classifier.
        :param th: threshold value of the Pixel/ Threshold attack. th=None indicates finding a minimum threshold.
        :param es: Indicates whether the attack uses CMAES (0) or DE (1) as Evolutionary Strategy.
        :param max_iter: Sets the Maximum iterations to run the Evolutionary Strategies for optimisation.
        :param targeted: Indicates whether the attack is targeted (True) or untargeted (False).
        :param verbose: Indicates whether to print verbose messages of ES used.
        
art/attacks/evasion/pixel_threshold.py