class_docstr: A unittest class for testing Adversarial Patch attack.
class_docstr_tok: ["A","unittest","class","for","testing","Adversarial","Patch","attack","."]
docstr: Second test with the KerasClassifier.
  :return:
docstr_tok: ["Second","test","with","the","KerasClassifier",".",":","return",":"]
code: def test_6_keras(self):
      """
      Second test with the KerasClassifier.
      :return:
      """
      krc = get_image_classifier_kr(from_logits=True)
  
      attack_ap = AdversarialPatch(
          krc,
          rotation_max=0.5,
          scale_min=0.4,
          scale_max=0.41,
          learning_rate=5.0,
          batch_size=10,
          max_iter=5,
          verbose=False,
      )
  
      target = np.zeros(self.x_train_mnist.shape[0])
      patch_adv, _ = attack_ap.generate(self.x_train_mnist, target)
  
      self.assertAlmostEqual(patch_adv[8, 8, 0], 0.67151666, delta=0.05)
      self.assertAlmostEqual(
          patch_adv[14, 14, 0], 0.6292826, delta=0.05
      )
      self.assertAlmostEqual(
          float(np.sum(patch_adv)), 424.31439208984375, delta=1.0
      )
  
      # insert_transformed_patch
      x_out = attack_ap.insert_transformed_patch(
          self.x_train_mnist[0],
          np.ones((14, 14, 1)),
          np.asarray([[2, 13], [2, 18], [12, 22], [8, 13]]),
      )
      x_out_expexted = np.array(
          [
              0.0,
              0.0,
              1.0,
              1.0,
              1.0,
              1.0,
              1.0,
              1.0,
              1.0,
              0.84313726,
              0.0,
              0.0,
              0.0,
              0.0,
              0.1764706,
              0.7294118,
              0.99215686,
              0.99215686,
              0.5882353,
              0.10588235,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
          ],
          dtype=np.float32,
      )
      np.testing.assert_almost_equal(
          x_out[15, :, 0], x_out_expexted, decimal=3
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  import keras
  import tensorflow
  from art.attacks.evasion.adversarial_patch.adversarial_patch import AdversarialPatch, AdversarialPatchNumpy, AdversarialPatchPyTorch
  from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from tests.utils import TestBase, master_seed
  from tests.utils import get_image_classifier_tf, get_image_classifier_kr
  from tests.utils import get_tabular_classifier_kr, get_image_classifier_pt
  from tests.attacks.utils import backend_test_classifier_type_check_fail
label_desc: Use image node_id 5 for calling the TestAdversarialPatch obj's underlying member method code with example usage: obj.test_6_keras() without return types