code: def test_check_params(
      art_warning, get_default_mnist_subset, image_dl_estimator
  ):
      try:
          classifier, _ = image_dl_estimator(functional=True)
  
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier,
                  percent_poison=0.01,
                  learning_rate_schedule=[0.1, 0.2, 0.3],
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(classifier, percent_poison=1.2)
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, max_epochs=0
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, max_trials=0
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, clip_values=1
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, epsilon=-1
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, batch_size=0
              )
          with pytest.raises(ValueError):
              _ = GradientMatchingAttack(
                  classifier, percent_poison=0.01, verbose=1.1
              )
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/attacks/poison/test_gradient_matching_attack.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.attacks.poisoning import GradientMatchingAttack
  from tests.utils import ARTTestException
label_desc: Use image node_id 2 for calling a global function with example usage: test_check_params(art_warning, get_default_mnist_subset, image_dl_estimator) without return types