code: def test_attack_generate(
      attack, random_image, accurate_class, not_close, art_warning
  ):
      """
      Test attacking neural network and generating adversarial images.
      """
      try:
          adv_image = attack.generate(
              np.expand_dims(random_image, 0),
              np.array([accurate_class]),
          )[0]
  
          assert (
              adv_image.shape == random_image.shape
          ), "Image shapes are not the same"
          np.testing.assert_array_compare(
              not_close, random_image, adv_image
          )
      except ARTTestException as _e:
          art_warning(_e)
  
imports: from typing import Callable, Tuple, Any
  import numpy
  import pytest
  from art.attacks.evasion.laser_attack.laser_attack import LaserBeam, LaserBeamGenerator, LaserBeamAttack
  from art.attacks.evasion.laser_attack.utils import ImageGenerator
  from tests.utils import ARTTestException
label_desc: Use image node_id 17 for calling a global function with example usage: test_attack_generate(attack, random_image, accurate_class, not_close, art_warning) without return types