code: def test_line_graph():
      transform = LineGraph()
      assert str(transform) == "LineGraph()"
  
      # Directed.
      edge_index = torch.tensor(
          [
              [0, 1, 2, 2, 3],
              [1, 2, 0, 3, 0],
          ]
      )
      data = Data(edge_index=edge_index, num_nodes=4)
      data = transform(data)
      assert data.edge_index.tolist() == [
          [0, 1, 1, 2, 3, 4],
          [1, 2, 3, 0, 4, 0],
      ]
      assert data.num_nodes == data.edge_index.max().item() + 1
  
      # Undirected.
      edge_index = torch.tensor(
          [
              [0, 0, 0, 1, 1, 2, 2, 3, 3, 3, 4, 4],
              [1, 2, 3, 0, 4, 0, 3, 0, 2, 4, 1, 3],
          ]
      )
      edge_attr = torch.ones(edge_index.size(1))
      data = Data(
          edge_index=edge_index, edge_attr=edge_attr, num_nodes=5
      )
      data = transform(data)
      assert data.edge_index.max().item() + 1 == data.x.size(0)
      assert data.edge_index.tolist() == [
          [0, 0, 0, 1, 1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 4, 5, 5, 5],
          [1, 2, 3, 0, 2, 4, 0, 1, 4, 5, 0, 5, 1, 2, 5, 2, 3, 4],
      ]
      assert data.x.tolist() == [2, 2, 2, 2, 2, 2]
      assert data.num_nodes == data.edge_index.max().item() + 1
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_line_graph() without return types