class_docstr: A unittest class for testing Backdoor Poisoning attack.
docstr: Test the backdoor attack with a pixel-based perturbation can be trained on classifier
docstr_tok: ["Test","the","backdoor","attack","with","a","pixel-based","perturbation","can","be","trained","on","classifier"]
code: def test_backdoor_pixel(self):
      """
      Test the backdoor attack with a pixel-based perturbation can be trained on classifier
      """
  
      krc = get_image_classifier_kr()
      (
          is_poison_train,
          x_poisoned_raw,
          y_poisoned_raw,
      ) = self.poison_dataset(
          self.x_train_mnist, self.y_train_mnist, self.poison_func_2
      )
  
      # Shuffle training data
      n_train = np.shape(y_poisoned_raw)[0]
      shuffled_indices = np.arange(n_train)
      np.random.shuffle(shuffled_indices)
      x_train = x_poisoned_raw[shuffled_indices]
      y_train = y_poisoned_raw[shuffled_indices]
  
      krc.fit(x_train, y_train, nb_epochs=NB_EPOCHS, batch_size=32)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import os
  import logging
  import unittest
  import numpy
  from art.attacks.poisoning.backdoor_attack import PoisoningAttackBackdoor
  from art.attacks.poisoning.perturbations import add_pattern_bd, add_single_bd, insert_image
  from art.utils import to_categorical
  from tests.utils import TestBase, master_seed, get_image_classifier_kr
label_desc: Use image node_id 10 for calling the TestBackdoorAttack obj's underlying member method code with example usage: obj.test_backdoor_pixel() without return types