code: def test_6_keras_iris_clipped(self):
      classifier = get_tabular_classifier_kr()
  
      # Test untargeted attack
      attack = VirtualAdversarialMethod(
          classifier, eps=0.1, verbose=False
      )
      x_test_iris_adv = attack.generate(self.x_test_iris)
      self.assertFalse((self.x_test_iris == x_test_iris_adv).all())
      self.assertTrue((x_test_iris_adv <= 1).all())
      self.assertTrue((x_test_iris_adv >= 0).all())
  
      preds_adv = np.argmax(classifier.predict(x_test_iris_adv), axis=1)
      self.assertFalse(
          (np.argmax(self.y_test_iris, axis=1) == preds_adv).all()
      )
      acc = (
          np.sum(preds_adv == np.argmax(self.y_test_iris, axis=1))
          / self.y_test_iris.shape[0]
      )
      logger.info(
          "Accuracy on Iris with VAT adversarial examples: %.2f%%",
          (acc * 100),
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from art.attacks.evasion.virtual_adversarial import VirtualAdversarialMethod
  from art.estimators.classification.keras import KerasClassifier
  from art.estimators.estimator import BaseEstimator
  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.utils import get_tabular_classifier_tf, get_tabular_classifier_kr, get_tabular_classifier_pt
  from tests.attacks.utils import backend_test_classifier_type_check_fail
label_desc: Use image node_id 6 for calling the TestVirtualAdversarial obj's underlying member method code with example usage: obj.test_6_keras_iris_clipped() without return types