code: def make_mock_output(mocker, model, top_class):
      num_classes = 10
  
      mock_tensor = torch.zeros((1, num_classes))
      mock_tensor[0][top_class] = 1
      mock_output = mocker.Mock(
          spec=mock_tensor, shape=(1, num_classes)
      )
  
      mocker.patch.object(model, "forward", return_value=mock_output)
  
      # Mock the return value of output.topk()
  
      mock_topk = (None, top_class)
      mocker.patch.object(mock_output, "topk", return_value=mock_topk)
  
      return mock_output
  
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 3 for calling a global function with example usage: make_mock_output(mocker, model, top_class) and returns: mock_output