def __init__(
        self,
        classifier: "CLASSIFIER_CLASS_LOSS_GRADIENTS_TYPE",
        num_basis: int,
        sigma: float,
        round_samples: float = 0.0,
    ) -> None:
        """
        :param classifier: An instance of a classification estimator whose loss_gradient is being approximated.
        :param num_basis:  The number of samples to draw to approximate the gradient.
        :param sigma: Scaling on the Gaussian noise N(0,1).
        :param round_samples: The resolution of the input domain to round the data to, e.g., 1.0, or 1/255. Set to 0 to
                              disable.
        """
        super().__init__(model=classifier.model, clip_values=classifier.clip_values)
        self._classifier = classifier
        self.num_basis = num_basis
        self.sigma = sigma
        self.round_samples = round_samples
        self._nb_classes = self._classifier.nb_classes

        :param classifier: An instance of a classification estimator whose loss_gradient is being approximated.
        :param num_basis:  The number of samples to draw to approximate the gradient.
        :param sigma: Scaling on the Gaussian noise N(0,1).
        :param round_samples: The resolution of the input domain to round the data to, e.g., 1.0, or 1/255. Set to 0 to
                              disable.
        
art/estimators/classification/query_efficient_bb.py