code: def test_local_cartesian():
      transform = LocalCartesian()
      assert str(transform) == "LocalCartesian()"
  
      pos = torch.tensor([[-1.0, 0.0], [0.0, 0.0], [2.0, 0.0]])
      edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
      edge_attr = torch.tensor([1.0, 2.0, 3.0, 4.0])
      data = Data(edge_index=edge_index, pos=pos)
  
      data = transform(data)
      assert len(data) == 3
      assert data.pos.tolist() == pos.tolist()
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.edge_attr.tolist() == [
          [0.25, 0.5],
          [1.0, 0.5],
          [0.0, 0.5],
          [1.0, 0.5],
      ]
  
      data = Data(edge_index=edge_index, pos=pos, edge_attr=edge_attr)
      data = transform(data)
      assert len(data) == 3
      assert data.pos.tolist() == pos.tolist()
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.edge_attr.tolist() == [
          [1, 0.25, 0.5],
          [2, 1.0, 0.5],
          [3, 0.0, 0.5],
          [4, 1.0, 0.5],
      ]
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_local_cartesian() without return types