code: def test_apply_patch_patch_points(art_warning, fix_get_goturn):
      try:
          goturn = fix_get_goturn
          attack = AdversarialTexturePyTorch(
              goturn,
              patch_height=4,
              patch_width=4,
              x_min=2,
              y_min=2,
              step_size=1.0 / 255.0,
              max_iter=500,
              batch_size=16,
              verbose=True,
          )
  
          patch = np.ones(shape=(4, 4, 3))
          foreground = np.ones(shape=(1, 15, 10, 10, 3))
          foreground[:, :, 5, 5, :] = 0
          x = np.zeros(shape=(1, 15, 10, 10, 3))
  
          patched_images = attack.apply_patch(
              x=x, patch_external=patch, foreground=foreground
          )
  
          patch_sum_expected = 15 * 3 * (4 * 4 - 1)
          complement_sum_expected = 0.0
  
          patch_sum = np.sum(patched_images[0, :, 2:6, 2:6, :])
          complement_sum = np.sum(patched_images[0]) - patch_sum
  
          assert patch_sum == patch_sum_expected
          assert complement_sum == complement_sum_expected
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/attacks/evasion/test_adversarial_texture_pytorch.py
imports: import os
  import logging
  import numpy
  import pytest
  from art.attacks.evasion import AdversarialTexturePyTorch
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from art.estimators.object_tracking.object_tracker import ObjectTrackerMixin
  from art.estimators.object_tracking import PyTorchGoturn
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import ARTTestException
label_desc: Use image node_id 5 for calling a global function with example usage: test_apply_patch_patch_points(art_warning, fix_get_goturn) without return types