class_docstr: Test cases for the AdversarialTrainer class.
class_docstr_tok: ["Test","cases","for","the","AdversarialTrainer","class","."]
docstr: Test the adversarial trainer using a targeted attack, which will currently result in a NotImplementError.
  
  :return: None
docstr_tok: ["Test","the","adversarial","trainer","using","a","targeted","attack",",","which","will","currently","result","in","a","NotImplementError",".",":","return",":","None"]
code: def test_targeted_attack_error(self):
      """
      Test the adversarial trainer using a targeted attack, which will currently result in a NotImplementError.
  
      :return: None
      """
      (x_train, y_train), (_, _) = self.mnist
      params = {"nb_epochs": 2, "batch_size": BATCH_SIZE}
  
      adv = FastGradientMethod(self.classifier, targeted=True)
      adv_trainer = AdversarialTrainer(self.classifier, attacks=adv)
      self.assertRaises(
          NotImplementedError,
          adv_trainer.fit,
          x_train,
          y_train,
          **params,
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from art.attacks.evasion.fast_gradient import FastGradientMethod
  from art.attacks.evasion.deepfool import DeepFool
  from art.data_generators import DataGenerator
  from art.defences.trainer.adversarial_trainer import AdversarialTrainer
  from art.utils import load_mnist
  from tests.utils import master_seed, get_image_classifier_tf
label_desc: Use image node_id 9 for calling the TestAdversarialTrainer obj's underlying member method code with example usage: obj.test_targeted_attack_error() without return types