8d3f66f01a4decd1b240a8e6fa2af4abfd7d25d1,art/attacks/evasion/carlini.py,CarliniL2Method,__init__,#CarliniL2Method#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,71

Before Change

        :param batch_size: Size of the batch on which adversarial samples are generated.
        
        super(CarliniL2Method, self).__init__(classifier)
        if not isinstance(classifier, ClassifierGradients):
            raise ClassifierError(self.__class__, [ClassifierGradients], classifier)

        kwargs = {
            "confidence": confidence,
            "targeted": targeted,
            "learning_rate": learning_rate,
            "binary_search_steps": binary_search_steps,
            "max_iter": max_iter,
            "initial_const": initial_const,
            "max_halving": max_halving,
            "max_doubling": max_doubling,
            "batch_size": batch_size,
        }
        assert self.set_params(**kwargs)

        // There are internal hyperparameters:
        // Abort binary search for c if it exceeds this threshold (suggested in Carlini and Wagner (2016)):
        self._c_upper_bound = 10e10

After Change

        super(CarliniL2Method, self).__init__(classifier)

        self.confidence = confidence
        self.targeted = targeted
        self.learning_rate = learning_rate
        self.binary_search_steps = binary_search_steps
        self.max_iter = max_iter
        self.initial_const = initial_const
        self.max_halving = max_halving
        self.max_doubling = max_doubling
        self.batch_size = batch_size
        self._check_params()

        // There are internal hyperparameters:
        // Abort binary search for c if it exceeds this threshold (suggested in Carlini and Wagner (2016)):
        self._c_upper_bound = 10e10

Instances