code: def test_shadow_model_bb_attack_rf(art_warning):
      try:
          (
              (x_target, y_target),
              (x_shadow, y_shadow),
              _,
              _,
          ) = load_nursery(test_set=0.5)
  
          target_train_size = len(x_target) // 2
          x_target_train = x_target[:target_train_size]
          y_target_train = y_target[:target_train_size]
          x_target_test = x_target[target_train_size:]
          y_target_test = y_target[target_train_size:]
  
          model = RandomForestClassifier(random_state=7)
          model.fit(x_target_train, y_target_train)
          art_classifier = ScikitlearnRandomForestClassifier(model)
  
          shadow_models = ShadowModels(
              art_classifier, num_shadow_models=1, random_state=7
          )
          shadow_dataset = shadow_models.generate_shadow_dataset(
              x_shadow, to_categorical(y_shadow, 4)
          )
          (mem_x, mem_y, mem_pred), (
              nonmem_x,
              nonmem_y,
              nonmem_pred,
          ) = shadow_dataset
  
          attack = MembershipInferenceBlackBox(
              art_classifier, attack_model_type="rf"
          )
          attack.fit(
              mem_x, mem_y, nonmem_x, nonmem_y, mem_pred, nonmem_pred
          )
  
          mem_infer = attack.infer(x_target_train, y_target_train)
          nonmem_infer = attack.infer(x_target_test, y_target_test)
          mem_acc = np.sum(mem_infer) / len(mem_infer)
          nonmem_acc = 1 - (np.sum(nonmem_infer) / len(nonmem_infer))
          accuracy = (
              mem_acc * len(mem_infer) + nonmem_acc * len(nonmem_infer)
          ) / (len(mem_infer) + len(nonmem_infer))
  
          assert accuracy == pytest.approx(0.7, abs=0.2)
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/attacks/inference/membership_inference/test_shadow_models.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from sklearn.ensemble import RandomForestClassifier
  from art.attacks.inference.membership_inference.black_box import MembershipInferenceBlackBox
  from art.attacks.inference.membership_inference.shadow_models import ShadowModels
  from art.estimators.classification.scikitlearn import ScikitlearnRandomForestClassifier, ScikitlearnClassifier
  from art.utils import load_nursery, to_categorical
  from tests.utils import ARTTestException
label_desc: Use image node_id 3 for calling a global function with example usage: test_shadow_model_bb_attack_rf(art_warning) without return types