code: def test_normalize_scale():
      transform = NormalizeFeatures()
      assert str(transform) == "NormalizeFeatures()"
  
      x = torch.tensor(
          [[1, 0, 1], [0, 1, 0], [0, 0, 0]], dtype=torch.float
      )
      data = Data(x=x)
  
      data = transform(data)
      assert len(data) == 1
      assert data.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 1 for calling a global function with example usage: test_normalize_scale() without return types