class_docstr: A unittest class for testing Randomized Smoothing as a post-processing step for classifiers.
code: def setUpClass(cls):
      # Get MNIST
      (x_train, y_train), (x_test, y_test), _, _ = load_dataset("mnist")
      x_train, y_train = x_train[:NB_TRAIN], y_train[:NB_TRAIN]
      x_test, y_test = x_test[:NB_TEST], y_test[:NB_TEST]
      cls.mnist = (x_train, y_train), (x_test, y_test)
  
file_path: adversarial-robustness-toolbox/tests/attacks/test_adversarial_embedding.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import os
  import unittest
  import numpy
  from art.attacks.poisoning.backdoor_attack import PoisoningAttackBackdoor
  from art.attacks.poisoning.adversarial_embedding_attack import PoisoningAttackAdversarialEmbedding
  from art.attacks.poisoning.perturbations import add_pattern_bd
  from art.utils import load_dataset
  from tests.utils import master_seed, get_image_classifier_kr_tf
label_desc: Use image node_id 1 for calling the TestAdversarialEmbedding obj's underlying member method code with example usage: obj.setUpClass(cls) without return types