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: Set the weights (and biases) of a neuron at index in the penultimate layer of the neural network to zero
  
  :param index: An index of the penultimate layer
docstr_tok: ["Set","the","weights","(","and","biases",")","of","a","neuron","at","index","in","the","penultimate","layer","of","the","neural","network","to","zero",":","param","index",":","An","index","of","the","penultimate","layer"]
code: def _prune_neuron_at_index(self, index: int) -> None:
      """
      Set the weights (and biases) of a neuron at index in the penultimate layer of the neural network to zero
  
      :param index: An index of the penultimate layer
      """
      if self.layer_names is not None:
          layer = self._model.layers[len(self.layer_names) - 2]
      else:  # pragma: no cover
          raise ValueError("No layer names found.")
      weights, biases = layer.get_weights()
      weights[:, index] = np.zeros_like(weights[:, index])
      biases[index] = 0
      layer.set_weights([weights, biases])
  
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 8 for calling the KerasNeuralCleanse obj's underlying member method code with example usage: obj._prune_neuron_at_index(index) without return types