code: def fix_get_mnist_data():
      """
      Get the first 100 samples of the mnist test set with channels first format
      :return: First 100 sample/label pairs of the MNIST test dataset.
      """
      nb_test = 100
  
      (_, _), (x_test, y_test), _, _ = load_dataset("mnist")
      x_test = np.squeeze(x_test)
      x_test = np.expand_dims(x_test, axis=1)
      y_test = np.argmax(y_test, axis=1)
  
      x_test, y_test = x_test[:nb_test], y_test[:nb_test]
  
      return x_test, y_test
  
file_path: adversarial-robustness-toolbox/tests/estimators/certification/test_deepz.py
imports: import json
  import os
  import pytest
  import numpy
  import torch
  from art.utils import load_dataset
  from art.estimators.certification.deep_z import PytorchDeepZ
  from tests.utils import ARTTestException
  from tests.utils import get_image_classifier_pt, get_cifar10_image_classifier_pt
label_desc: Use image node_id 1 for calling a global function with example usage: fix_get_mnist_data() and returns: x_test,  y_test