code: def test_one_hot_degree():
      assert str(OneHotDegree(max_degree=3)) == "OneHotDegree(3)"
  
      edge_index = torch.tensor(
          [[0, 0, 0, 1, 2, 3], [1, 2, 3, 0, 0, 0]]
      )
      x = torch.tensor([1.0, 1.0, 1.0, 1.0])
  
      data = Data(edge_index=edge_index, num_nodes=4)
      data = OneHotDegree(max_degree=3)(data)
      assert len(data) == 3
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.x.tolist() == [
          [0.0, 0.0, 0.0, 1.0],
          [0.0, 1.0, 0.0, 0.0],
          [0.0, 1.0, 0.0, 0.0],
          [0.0, 1.0, 0.0, 0.0],
      ]
      assert data.num_nodes == 4
  
      data = Data(edge_index=edge_index, x=x)
      data = OneHotDegree(max_degree=3)(data)
      assert len(data) == 2
      assert data.edge_index.tolist() == edge_index.tolist()
      assert data.x.tolist() == [
          [1.0, 0.0, 0.0, 0.0, 1.0],
          [1.0, 0.0, 1.0, 0.0, 0.0],
          [1.0, 0.0, 1.0, 0.0, 0.0],
          [1.0, 0.0, 1.0, 0.0, 0.0],
      ]
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_one_hot_degree() without return types