code: def fix_get_mnist_subset(get_mnist_dataset):
      (x_train_mnist, y_train_mnist), (
          x_test_mnist,
          y_test_mnist,
      ) = get_mnist_dataset
      n_train = 100
      n_test = 11
      yield x_train_mnist[:n_train], y_train_mnist[
          :n_train
      ], x_test_mnist[:n_test], y_test_mnist[:n_test]
  
imports: import numpy
  import pytest
  import torch
  import torch.nn.functional
  import torch.nn
  import torch.optim
  import sklearn.datasets
  from art.estimators.classification.pytorch import PyTorchClassifier
  from art.defences.preprocessor.spatial_smoothing import SpatialSmoothing
  from art.defences.preprocessor.spatial_smoothing_pytorch import SpatialSmoothingPyTorch
  from art.attacks.evasion.fast_gradient import FastGradientMethod
  from art.attacks.evasion.projected_gradient_descent.projected_gradient_descent import ProjectedGradientDescent
  from tests.attacks.utils import backend_test_defended_images
  from tests.utils import ARTTestException
label_desc: Use image node_id 1 for calling a global function with example usage: fix_get_mnist_subset(get_mnist_dataset) without return types