class_docstr: Implementation of methods in Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks.
  Wang et al. (2019).
  
  | Paper link: https://people.cs.uchicago.edu/~ravenben/publications/pdf/backdoor-sp19.pdf
docstr: Return the shape of one input sample.
  
  :return: Shape of one input sample.
docstr_tok: ["Return","the","shape","of","one","input","sample",".",":","return",":","Shape","of","one","input","sample","."]
code: def input_shape(self) -> Tuple[int, ...]:
      """
      Return the shape of one input sample.
  
      :return: Shape of one input sample.
      """
      return self._input_shape
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  from typing import List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from tqdm.auto import tqdm
  from art.config import ART_NUMPY_DTYPE
  from art.estimators.poison_mitigation.neural_cleanse.neural_cleanse import NeuralCleanseMixin
  from art.estimators.classification.keras import KerasClassifier, KERAS_MODEL_TYPE
label_desc: Use image node_id 2 for calling the KerasNeuralCleanse obj's underlying member method code with example usage: obj.input_shape() and returns: self