code: def test_randomized_smoothing_iris_fgsm(
      art_warning, get_iris_classifier
  ):
      (_, _), (x_test, y_test), _, _ = load_dataset("iris")
  
      try:
          classifier, rs = get_iris_classifier()
          attack = FastGradientMethod(classifier, eps=0.1)
          x_test_adv = attack.generate(x_test)
          preds_smooth = np.argmax(rs.predict(x_test_adv), axis=1)
  
          assert not np.array_equal(x_test, x_test_adv)
          assert not np.array_equal(
              np.argmax(y_test, axis=1), preds_smooth
          )
          assert np.all(x_test_adv <= 1)
          assert np.all(x_test_adv >= 0)
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/estimators/certification/test_randomized_smoothing.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import pytest
  import numpy
  from art.attacks.evasion.fast_gradient import FastGradientMethod
  from art.estimators.certification.randomized_smoothing import NumpyRandomizedSmoothing, TensorFlowV2RandomizedSmoothing, PyTorchRandomizedSmoothing
  from art.utils import load_dataset, random_targets
  from tests.utils import get_image_classifier_pt, get_image_classifier_tf, get_image_classifier_kr, get_tabular_classifier_pt, ARTTestException
label_desc: Use image node_id 10 for calling a global function with example usage: test_randomized_smoothing_iris_fgsm(art_warning, get_iris_classifier) without return types