code: def test_full_suite_coco_tensorflow():
      if len(tf.config.list_physical_devices("GPU")) > 0:
          with tf.device("/device:GPU:0"):
              coco_train_gpu = coco_tensorflow.load_dataset(
                  train=True, object_type="VisionData", n_samples=200
              )
              coco_test_gpu = coco_tensorflow.load_dataset(
                  train=False, object_type="VisionData", n_samples=200
              )
              suite = full_suite(
                  imaginery_kwarg="just to make sure all checks have kwargs in the init"
              )
              arguments = (
                  dict(
                      train_dataset=coco_train_gpu,
                      test_dataset=coco_test_gpu,
                  ),
              )
  
              for args in arguments:
                  result = suite.run(**args)
                  length = get_expected_results_length(suite, args)
                  validate_suite_result(result, length)
  
file_path: deepchecks/tests/vision/gpu_tests/full_suite_test.py
imports: import tensorflow
  import torch
  from deepchecks.vision.datasets.classification import mnist_tensorflow
  from deepchecks.vision.datasets.classification import mnist_torch
  from deepchecks.vision.datasets.detection import coco_tensorflow, coco_torch
  from deepchecks.vision.suites.default_suites import full_suite
  from tests.common import get_expected_results_length, validate_suite_result
label_desc: Use image node_id 4 for calling a global function with example usage: test_full_suite_coco_tensorflow() without return types