code: def test_pretrained_model_load():
      if MODEL_PATH.exists():
          model = load_model().real_model
          assert_that(model.training is False)
          assert_that(model, instance_of(MnistModel))
      else:
          model = load_model().real_model
          assert_that(model.training is False)
          assert_that(model, instance_of(MnistModel))
          assert_that(MODEL_PATH.exists() and MODEL_PATH.is_file())
          # to verify loading from the file
          test_pretrained_model_load()
  
file_path: deepchecks/tests/vision/datasets/test_mnist_torch.py
imports: import time
  from hamcrest import assert_that, calling, equal_to, instance_of, is_not, raises
  from torch.utils.data import DataLoader
  from deepchecks.vision import VisionData
  from deepchecks.vision.datasets.classification.mnist_torch import MNIST_DIR, MODEL_PATH, MnistModel, load_dataset, load_model
label_desc: Use image node_id 4 for calling a global function with example usage: test_pretrained_model_load() without return types