class_docstr: This class implements a classifier with the PyTorch framework.
class_docstr_tok: ["This","class","implements","a","classifier","with","the","PyTorch","framework","."]
code: def __repr__(self):
      repr_ = (
          f"{self.__module__ + '.' + self.__class__.__name__}(model={self._model}, loss={self._loss}, "
          f"optimizer={self._optimizer}, input_shape={self._input_shape}, nb_classes={self.nb_classes}, "
          f"channels_first={self.channels_first}, clip_values={self.clip_values!r}, "
          f"preprocessing_defences={self.preprocessing_defences}, "
          f"postprocessing_defences={self.postprocessing_defences}, preprocessing={self.preprocessing})"
      )
  
      return repr_
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import copy
  import logging
  import os
  import time
  from typing import Any, Dict, List, Optional, Tuple, Union, TYPE_CHECKING
  from tqdm.auto import tqdm
  import numpy
  import six
  from art import config
  from art.estimators.classification.classifier import ClassGradientsMixin, ClassifierMixin
  from art.estimators.pytorch import PyTorchEstimator
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 26 for calling the PyTorchClassifier obj's underlying member method code with example usage: obj.__repr__() and returns: repr_