code: def test_pytorch_certify(art_warning, get_pytorch_yolo):
      object_detector, x_test, _ = get_pytorch_yolo
      object_seeker = PyTorchObjectSeeker(
          model=object_detector.model,
          input_shape=object_detector.input_shape,
          channels_first=object_detector.channels_first,
          optimizer=object_detector.optimizer,
          clip_values=object_detector.clip_values,
          attack_losses=object_detector.attack_losses,
          detector_type="YOLO",
          num_lines=3,
          confidence_threshold=0.3,
          iou_threshold=0.4,
          prune_threshold=0.5,
          device_type="cpu",
      )
  
      try:
          result = object_seeker.certify(
              x=x_test, patch_size=0.01, offset=0.1
          )
  
          assert len(result) == len(x_test)
          assert np.any(result[0])
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/estimators/object_detection/test_object_seeker_yolo.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.estimators.certification.object_seeker import PyTorchObjectSeeker
  from tests.utils import ARTTestException
label_desc: Use image node_id 3 for calling a global function with example usage: test_pytorch_certify(art_warning, get_pytorch_yolo) without return types