class_docstr: This class implements a Classifier extension that wraps a classifier and a detector.
  More details in https://arxiv.org/abs/1705.07263
class_docstr_tok: ["This","class","implements","a","Classifier","extension","that","wraps","a","classifier","and","a","detector",".","More","details","in","https",":","\/\/arxiv.org\/abs\/1705.07263"]
docstr: Fit the classifier on the training set `(x, y)`.
  
  :param x: Training data.
  :param y: Target values (class labels) one-hot-encoded of shape (nb_samples, nb_classes).
  :param batch_size: Size of batches.
  :param nb_epochs: Number of epochs to use for training.
  :param kwargs: Dictionary of framework-specific arguments. This parameter is not currently supported for PyTorch
         and providing it takes no effect.
  :raises `NotImplementedException`: This method is not supported for detector-classifiers.
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code: def fit(
      self,
      x: np.ndarray,
      y: np.ndarray,
      batch_size: int = 128,
      nb_epochs: int = 10,
      **kwargs,
  ) -> None:
      """
      Fit the classifier on the training set `(x, y)`.
  
      :param x: Training data.
      :param y: Target values (class labels) one-hot-encoded of shape (nb_samples, nb_classes).
      :param batch_size: Size of batches.
      :param nb_epochs: Number of epochs to use for training.
      :param kwargs: Dictionary of framework-specific arguments. This parameter is not currently supported for PyTorch
             and providing it takes no effect.
      :raises `NotImplementedException`: This method is not supported for detector-classifiers.
      """
      raise NotImplementedError
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import List, Optional, Union, Tuple, TYPE_CHECKING
  import numpy
  from art.estimators.classification.classifier import ClassifierNeuralNetwork
label_desc: Use image node_id 4 for calling the DetectorClassifier obj's underlying member method code with example usage: obj.fit(x, y, batch_size, nb_epochs) without return types