code: def test_hetero_normalize_scale():
      x = torch.tensor(
          [[1, 0, 1], [0, 1, 0], [0, 0, 0]], dtype=torch.float
      )
  
      data = HeteroData()
      data["v"].x = x
      data["w"].x = x
      data = NormalizeFeatures()(data)
      assert data["v"].x.tolist() == [
          [0.5, 0, 0.5],
          [0, 1, 0],
          [0, 0, 0],
      ]
      assert data["w"].x.tolist() == [
          [0.5, 0, 0.5],
          [0, 1, 0],
          [0, 0, 0],
      ]
  
imports: import torch
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.transforms import NormalizeFeatures
label_desc: Use image node_id 2 for calling a global function with example usage: test_hetero_normalize_scale() without return types