def METHOD_NAME(self, x: np.ndarray, batch_size: int = 128, **kwargs) -> Tuple[dict, np.ndarray]:
    """
    Perform detection of adversarial data and return prediction as tuple.
    :param x: Data sample on which to perform detection.
    :param batch_size: Size of batches.
    :return: (report, is_adversarial):
            where report is a dictionary containing the detector model output predictions;
            where is_adversarial is a boolean list of per-sample prediction whether the sample is adversarial
            or not and has the same `batch_size` (first dimension) as `x`.
    """
    x_activations: np.ndarray = self._get_activations(x, self._layer_name, batch_size)
    predictions = self.detector.predict(x_activations, batch_size=batch_size)
    is_adversarial = np.argmax(predictions, axis=1).astype(bool)
    report = {"predictions": predictions}
    return report, is_adversarial