code: def load_mnist_dataset():
      logging.info("Loading mnist")
      (
          (x_train_mnist, y_train_mnist),
          (x_test_mnist, y_test_mnist),
          _,
          _,
      ) = load_dataset("mnist")
      yield (x_train_mnist, y_train_mnist), (x_test_mnist, y_test_mnist)
  
imports: import importlib
  import json
  import logging
  import os
  import shutil
  import tempfile
  from typing import Dict, List, TYPE_CHECKING, Union
  import warnings
  import numpy
  import pytest
  import requests
  from art.data_generators import KerasDataGenerator, MXDataGenerator, PyTorchDataGenerator, TensorFlowDataGenerator, TensorFlowV2DataGenerator
  from art.defences.preprocessor import FeatureSqueezing, JpegCompression, SpatialSmoothing
  from art.estimators.classification import KerasClassifier
  from tests.utils import ARTTestFixtureNotImplemented, get_attack_classifier_pt, get_image_classifier_kr, get_image_classifier_kr_functional, get_image_classifier_kr_tf, get_image_classifier_kr_tf_functional, get_image_classifier_kr_tf_with_wildcard, get_image_classifier_mxnet_custom_ini, get_image_classifier_pt, get_image_classifier_pt_functional, get_image_classifier_tf, get_image_classifier_hf, get_image_gan_tf_v2, get_image_generator_tf_v2, get_tabular_classifier_kr, get_tabular_classifier_pt, get_tabular_classifier_scikit_list, get_tabular_classifier_tf, load_dataset, master_seed
label_desc: Use image node_id 34 for calling a global function with example usage: load_mnist_dataset() without return types