code: def test_attack_generate_params(
      attack, random_image, accurate_class, art_warning
  ):
      """
      Test attacking neural network and generating adversarial objects.
      """
      try:
          adv_laser, adv_class = attack.generate_parameters(
              np.expand_dims(random_image, 0),
              np.array([accurate_class]),
          )[0]
  
          assert adv_class != accurate_class
          assert adv_laser is not None
      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 18 for calling a global function with example usage: test_attack_generate_params(attack, random_image, accurate_class, art_warning) without return types