class_docstr: A unittest class for testing Adversarial Patch attack.
class_docstr_tok: ["A","unittest","class","for","testing","Adversarial","Patch","attack","."]
code: def test_5_failure_feature_vectors(self):
      classifier = get_tabular_classifier_kr()
      classifier._clip_values = (0, 1)
  
      # Assert that value error is raised for feature vectors
      with self.assertRaises(ValueError) as context:
          _ = AdversarialPatch(classifier=classifier)
  
      self.assertIn(
          "Unexpected input_shape in estimator detected. AdversarialPatch is expecting images or videos as input.",
          str(context.exception),
      )
  
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 7 for calling the TestAdversarialPatch obj's underlying member method code with example usage: obj.test_5_failure_feature_vectors() without return types