class_docstr: Wrapper class for importing Keras models.
docstr: Create a copy of the classifier that can be refit from scratch. Will inherit same architecture, optimizer and
  initialization as cloned model, but without weights.
  
  :return: new classifier
docstr_tok: ["Create","a","copy","of","the","classifier","that","can","be","refit","from","scratch",".","Will","inherit","same","architecture",",","optimizer","and","initialization","as","cloned","model",",","but","without","weights",".",":","return",":","new","classifier"]
code: def clone_for_refitting(
      self,
  ) -> "KerasClassifier":
      """
      Create a copy of the classifier that can be refit from scratch. Will inherit same architecture, optimizer and
      initialization as cloned model, but without weights.
  
      :return: new classifier
      """
      cloned_classifier = super().clone_for_refitting()
      if isinstance(cloned_classifier, KerasClassifier):
          return cloned_classifier
      raise ValueError("Type of cloned classifier not expected.")
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import time
  from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  import six
  from art import config
  from art.estimators.keras import KerasEstimator
  from art.estimators.classification.classifier import ClassifierMixin, ClassGradientsMixin
  from art.utils import check_and_transform_label_format
label_desc: Use image node_id 15 for calling the KerasClassifier obj's underlying member method code with example usage: obj.clone_for_refitting() and returns: cloned_classifier