def __init__(
        self,
        classifier: ClassifierNeuralNetwork,
        detector: ClassifierNeuralNetwork,
        preprocessing_defences: "Preprocessor" | list["Preprocessor"] | None = None,
        postprocessing_defences: "Postprocessor" | list["Postprocessor"] | None = None,
        preprocessing: "PREPROCESSING_TYPE" = (0.0, 1.0),
    ) -> None:
        """
        Initialization for the DetectorClassifier.

        :param classifier: A trained classifier.
        :param detector: A trained detector applied for the binary classification.
        :param preprocessing_defences: Preprocessing defence(s) to be applied by the classifier. Not applicable
               in this classifier.
        :param postprocessing_defences: Postprocessing defence(s) to be applied by the classifier.
        :param preprocessing: Tuple of the form `(subtrahend, divisor)` of floats or `np.ndarray` of values to be
               used for data preprocessing. The first value will be subtracted from the input. The input will then
               be divided by the second one. Not applicable in this classifier.
        """
        if preprocessing_defences is not None:
            raise NotImplementedError("Preprocessing is not applicable in this classifier.")

        super().__init__(
            model=None,
            clip_values=classifier.clip_values,
            preprocessing=preprocessing,
            channels_first=classifier.channels_first,
            preprocessing_defences=preprocessing_defences,
            postprocessing_defences=postprocessing_defences,
        )

        self.classifier = classifier
        self.detector = detector
        self.nb_classes = classifier.nb_classes + 1
        self._input_shape = classifier.input_shape

        Initialization for the DetectorClassifier.

        :param classifier: A trained classifier.
        :param detector: A trained detector applied for the binary classification.
        :param preprocessing_defences: Preprocessing defence(s) to be applied by the classifier. Not applicable
               in this classifier.
        :param postprocessing_defences: Postprocessing defence(s) to be applied by the classifier.
        :param preprocessing: Tuple of the form `(subtrahend, divisor)` of floats or `np.ndarray` of values to be
               used for data preprocessing. The first value will be subtracted from the input. The input will then
               be divided by the second one. Not applicable in this classifier.
        
art/estimators/classification/detector_classifier.py