code: def test_check_params(art_warning, image_dl_estimator_for_attack):
      try:
          classifier = image_dl_estimator_for_attack(
              AutoProjectedGradientDescent, from_logits=True
          )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, norm=0)
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, eps="1")
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, eps=-1.0)
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, eps_step="1")
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, eps_step=-1.0
              )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, max_iter=1.0)
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(classifier, max_iter=-1)
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, targeted="true"
              )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, nb_random_init=1.0
              )
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, nb_random_init=-1
              )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, batch_size=1.0
              )
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, batch_size=-1
              )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, loss_type="test"
              )
  
          with pytest.raises(ValueError):
              _ = AutoProjectedGradientDescent(
                  classifier, verbose="true"
              )
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/attacks/evasion/test_auto_projected_gradient_descent.py
imports: import logging
  import pytest
  import numpy
  from art.attacks.evasion import AutoProjectedGradientDescent
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import ARTTestException
label_desc: Use image node_id 3 for calling a global function with example usage: test_check_params(art_warning, image_dl_estimator_for_attack) without return types