code: def test_check_params(art_warning, image_dl_estimator_for_attack):
      try:
          from art.attacks.evasion import FastGradientMethod
  
          classifier = image_dl_estimator_for_attack(
              FrameSaliencyAttack, from_logits=True
          )
  
          attacker = FastGradientMethod(estimator=classifier)
  
          with pytest.raises(ValueError):
              _ = FrameSaliencyAttack(classifier, attacker="attack")
  
          with pytest.raises(ValueError):
              _ = FrameSaliencyAttack(
                  classifier, attacker=attacker, method="test"
              )
  
          with pytest.raises(ValueError):
              _ = FrameSaliencyAttack(
                  classifier, attacker=attacker, frame_index=0
              )
  
          with pytest.raises(ValueError):
              _ = FrameSaliencyAttack(
                  classifier, attacker=attacker, batch_size=-1
              )
  
          with pytest.raises(ValueError):
              _ = FrameSaliencyAttack(
                  classifier, attacker=attacker, verbose="true"
              )
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/attacks/evasion/test_frame_saliency.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.attacks.evasion import FastGradientMethod, FrameSaliencyAttack
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from tests.utils import ExpectedValue
  from tests.attacks.utils import backend_check_adverse_values, backend_check_adverse_frames
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import ARTTestException
label_desc: Use image node_id 5 for calling a global function with example usage: test_check_params(art_warning, image_dl_estimator_for_attack) without return types