code: def test_loading_model(request: Any, url: str) -> None:
      backend = request.config.option.backend
      if backend != "tensorflow":
          pytest.skip()
  
      # download model
      try:
          fmodel = fbn.zoo.get_model(
              url, name="MobileNetV2", overwrite=True
          )
      except fbn.zoo.GitCloneError:
          pytest.skip()
  
      # download again (test overwriting)
      try:
          fmodel = fbn.zoo.get_model(
              url, name="MobileNetV2", overwrite=True
          )
      except fbn.zoo.GitCloneError:
          pytest.skip()
  
      # create a dummy image
      # x = np.zeros(dim, dtype=np.float32)
      # x[:] = np.random.randn(*x.shape)
      x, y = fbn.samples(fmodel, dataset="imagenet", batchsize=16)
  
      # run the model
      # logits = model(x)
      # probabilities = ep.softmax(logits)
      # predicted_class = np.argmax(logits)
      assert fbn.accuracy(fmodel, x, y) > 0.9
  
file_path: foolbox/tests/test_zoo.py
imports: from typing import Any
  import sys
  import pytest
  import foolbox
  from foolbox.zoo.model_loader import ModelLoader
label_desc: Use image node_id 2 for calling a global function with example usage: test_loading_model(request, url) without return types