class_docstr: A unittest class for testing the Threshold Attack.
  
  This module tests the Threshold Attack.
  
  | Paper link:
      https://arxiv.org/abs/1906.06026
class_docstr_tok: ["A","unittest","class","for","testing","the","Threshold","Attack",".","This","module","tests","the","Threshold","Attack",".","|","Paper","link",":","https",":","\/\/arxiv.org\/abs\/1906.06026"]
docstr: Test with the PyTorchClassifier. (Untargeted Attack)
  :return:
docstr_tok: ["Test","with","the","PyTorchClassifier",".","(","Untargeted","Attack",")",":","return",":"]
code: def test_4_pytorch_mnist(self):
      """
      Test with the PyTorchClassifier. (Untargeted Attack)
      :return:
      """
      x_test = np.reshape(
          self.x_test_mnist, (self.x_test_mnist.shape[0], 1, 28, 28)
      ).astype(np.float32)
      classifier = get_image_classifier_pt()
      self._test_attack(classifier, x_test, self.y_test_mnist, False)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from art.attacks.evasion.pixel_threshold import ThresholdAttack
  from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import get_labels_np_array
  from tests.utils import TestBase
  from tests.utils import get_image_classifier_tf, get_image_classifier_kr, get_image_classifier_pt
  from tests.attacks.utils import backend_test_classifier_type_check_fail
label_desc: Use image node_id 4 for calling the TestThresholdAttack obj's underlying member method code with example usage: obj.test_4_pytorch_mnist() without return types