code: def test_masked_images(
      art_warning, fix_get_mnist_subset, image_dl_estimator_for_attack
  ):
      try:
          classifier = image_dl_estimator_for_attack(FastGradientMethod)
          attack = FastGradientMethod(
              classifier, eps=1.0, num_random_init=1
          )
          backend_masked_images(attack, fix_get_mnist_subset)
      except ARTTestException as e:
          art_warning(e)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.attacks.evasion import FastGradientMethod
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from tests.attacks.utils import backend_check_adverse_values, backend_test_defended_images
  from tests.attacks.utils import backend_test_random_initialisation_images, backend_targeted_images
  from tests.attacks.utils import backend_targeted_tabular, backend_untargeted_tabular, backend_masked_images
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import ExpectedValue, ARTTestException
label_desc: Use image node_id 5 for calling a global function with example usage: test_masked_images(art_warning, fix_get_mnist_subset, image_dl_estimator_for_attack) without return types