def predict(  # type: ignore
        self, x: np.ndarray, batch_size: int = 128, verbose: bool = False, **kwargs
    ) -> np.ndarray:
        """
        Perform prediction of the given classifier for a batch of inputs, taking an expectation over transformations.

        :param x: Input samples.
        :param batch_size: Batch size.
        :param verbose: Display training progress bar.
        :param is_abstain: True if function will abstain from prediction and return 0s. Default: True
        :type is_abstain: `boolean`
        :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
        """
        return RandomizedSmoothingMixin.predict(
            self, x, batch_size=batch_size, verbose=verbose, training_mode=False, **kwargs
        )

        Perform prediction of the given classifier for a batch of inputs, taking an expectation over transformations.

        :param x: Input samples.
        :param batch_size: Batch size.
        :param verbose: Display training progress bar.
        :param is_abstain: True if function will abstain from prediction and return 0s. Default: True
        :type is_abstain: `boolean`
        :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
        
art/estimators/certification/randomized_smoothing/pytorch.py