class_docstr: A unittest class for testing the Simple Black-box Adversarial Attacks (SimBA).
  
  This module tests SimBA.
  
  | Paper link: https://arxiv.org/abs/1905.07121
code: def test_check_params(self):
      ptc = get_image_classifier_pt(from_logits=True)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, max_iter=1.0)
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, max_iter=-1)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, epsilon=-1)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, batch_size=2)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, stride=1.0)
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, stride=-1)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, freq_dim=1.0)
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, freq_dim=-1)
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, order="test")
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, attack="test")
  
      with self.assertRaises(ValueError):
          _ = SimBA(ptc, targeted="test")
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  from art.attacks.evasion.simba import SimBA
  from art.estimators.estimator import BaseEstimator, NeuralNetworkMixin
  from art.estimators.classification.classifier import ClassifierMixin
  from art.utils import get_labels_np_array
  from tests.utils import TestBase
  from tests.utils import get_image_classifier_tf, get_image_classifier_kr, get_image_classifier_pt
  from tests.attacks.utils import backend_test_classifier_type_check_fail
label_desc: Use image node_id 9 for calling the TestSimBA obj's underlying member method code with example usage: obj.test_check_params() without return types