code: def test_torch_save(model_name, pretrained, tmp_path):
      print('test_torch_save("{}")'.format(model_name))
      net = pm.__dict__[model_name](
          num_classes=1000, pretrained=pretrained
      )
  
      tmp_file = tmp_path / "{}.pkl".format(model_name)
      torch.save(net, tmp_file.open("wb"))
      tmp_file.unlink()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_torch_save(model_name, pretrained, tmp_path) without return types