code: def test_visualize_calls_calculate_gradients_twice(mocker, model):
      backprop = Backprop(model)
      mocker.spy(backprop, "calculate_gradients")
  
      top_class = 5
      target_class = 5
      input_ = torch.zeros([1, 3, 224, 224])
  
      make_expected_gradient_target(top_class)
      make_mock_output(mocker, model, target_class)
  
      backprop.visualize(input_, target_class, use_gpu=True)
  
      assert backprop.calculate_gradients.call_count == 2
  
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 17 for calling a global function with example usage: test_visualize_calls_calculate_gradients_twice(mocker, model) without return types