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: Reset the state of the defense
  :return:
docstr_tok: ["Reset","the","state","of","the","defense",":","return",":"]
code: def reset(self):
      """
      Reset the state of the defense
      :return:
      """
      import keras.backend as K
  
      self.cost = self.init_cost
      K.set_value(self.cost_tensor, self.init_cost)
      K.set_value(self.opt.iterations, 0)
      for weight in self.opt.weights:
          K.set_value(weight, np.zeros(K.int_shape(weight)))
  
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 3 for calling the KerasNeuralCleanse obj's underlying member method code with example usage: obj.reset() without return types