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: Perform prediction of the given classifier for a batch of inputs, potentially filtering suspicious input
  
  :param x: Input data to predict.
  :param batch_size: Batch size.
  :param training_mode: `True` for model set to training mode and `'False` for model set to evaluation mode.
  :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
docstr_tok: ["Perform","prediction","of","the","given","classifier","for","a","batch","of","inputs",",","potentially","filtering","suspicious","input",":","param","x",":","Input","data","to","predict",".",":","param","batch_size",":","Batch","size",".",":","param","training_mode",":","`","True","`","for","model","set","to","training","mode","and","`","'False","`","for","model","set","to","evaluation","mode",".",":","return",":","Array","of","predictions","of","shape","`","(","nb_inputs",",","nb_classes",")","`","."]
code: def predict(
      self,
      x: np.ndarray,
      batch_size: int = 128,
      training_mode: bool = False,
      **kwargs,
  ) -> np.ndarray:
      """
      Perform prediction of the given classifier for a batch of inputs, potentially filtering suspicious input
  
      :param x: Input data to predict.
      :param batch_size: Batch size.
      :param training_mode: `True` for model set to training mode and `'False` for model set to evaluation mode.
      :return: Array of predictions of shape `(nb_inputs, nb_classes)`.
      """
      return NeuralCleanseMixin.predict(
          self,
          x,
          batch_size=batch_size,
          training_mode=training_mode,
          **kwargs,
      )
  
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 9 for calling the KerasNeuralCleanse obj's underlying member method code with example usage: obj.predict(x, batch_size, training_mode) and returns: NeuralCleanseMixin