code: def test_delaunay():
      assert str(Delaunay()) == "Delaunay()"
  
      pos = torch.tensor(
          [[-1, -1], [-1, 1], [1, 1], [1, -1]], dtype=torch.float
      )
      data = Data(pos=pos)
      data = Delaunay()(data)
      assert len(data) == 2
      assert data.face.tolist() == [[3, 1], [1, 3], [0, 2]]
  
      pos = torch.tensor([[-1, -1], [-1, 1], [1, 1]], dtype=torch.float)
      data = Data(pos=pos)
      data = Delaunay()(data)
      assert len(data) == 2
      assert data.face.tolist() == [[0], [1], [2]]
  
      pos = torch.tensor([[-1, -1], [1, 1]], dtype=torch.float)
      data = Data(pos=pos)
      data = Delaunay()(data)
      assert len(data) == 2
      assert data.edge_index.tolist() == [[0, 1], [1, 0]]
  
      pos = torch.tensor([[-1, -1]], dtype=torch.float)
      data = Data(pos=pos)
      data = Delaunay()(data)
      assert len(data) == 2
      assert data.edge_index.tolist() == [[], []]
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_delaunay() without return types