code: def test_randomized_smoothing_iris_predict(
      art_warning, get_iris_classifier
  ):
      (_, _), (x_test, y_test), _, _ = load_dataset("iris")
  
      try:
          _, rs = get_iris_classifier()
          y_test_smooth = rs.predict(x=x_test)
  
          np.testing.assert_array_equal(
              y_test_smooth.shape, y_test.shape
          )
          assert np.all(np.sum(y_test_smooth, axis=1) <= 1)
  
      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 8 for calling a global function with example usage: test_randomized_smoothing_iris_predict(art_warning, get_iris_classifier) without return types