code: def test_calculate_gradients_for_all_models(
      mocker, name, model_module
  ):
      model = model_module()
      backprop = Backprop(model)
  
      target_class = 5
      input_ = torch.zeros([1, 3, 224, 224])
  
      if "inception" in name:
          input_ = torch.zeros([1, 3, 299, 299])
  
      make_mock_output(mocker, model, target_class)
  
      gradients = backprop.calculate_gradients(
          input_, target_class, use_gpu=True
      )
  
      assert gradients.shape == input_.size()[1:]
  
imports: import inspect
  import pytest
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision.models
  from flashtorch.saliency import Backprop
label_desc: Use image node_id 21 for calling a global function with example usage: test_calculate_gradients_for_all_models(mocker, name, model_module) without return types