code: def test_target_indegree():
      assert (
          str(TargetIndegree())
          == "TargetIndegree(norm=True, max_value=None)"
      )
  
      edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
      edge_attr = torch.tensor([1.0, 1.0, 1.0, 1.0])
  
      data = Data(edge_index=edge_index, num_nodes=3)
      data = TargetIndegree(norm=False)(data)
      assert len(data) == 3
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.edge_attr.tolist() == [[2], [1], [1], [2]]
      assert data.num_nodes == 3
  
      data = Data(
          edge_index=edge_index, edge_attr=edge_attr, num_nodes=3
      )
      data = TargetIndegree(norm=True)(data)
      assert len(data) == 3
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.edge_attr.tolist() == [
          [1, 1],
          [1, 0.5],
          [1, 0.5],
          [1, 1],
      ]
      assert data.num_nodes == 3
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_target_indegree() without return types