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 using the generator that yields batches as specified.
  
  :param generator: Batch generator providing `(x, y)` for each epoch.
  :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_generator(
      self, generator: "DataGenerator", nb_epochs: int = 20, **kwargs
  ) -> None:
      """
      Fit the classifier using the generator that yields batches as specified.
  
      :param generator: Batch generator providing `(x, y)` for each epoch.
      :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 5 for calling the DetectorClassifier obj's underlying member method code with example usage: obj.fit_generator(generator, nb_epochs) without return types