code: def test_graph_unet():
      model = GraphUNet(16, 32, 8, depth=3)
      out = "GraphUNet(16, 32, 8, depth=3, pool_ratios=[0.5, 0.5, 0.5])"
      assert str(model) == out
  
      x = torch.randn(3, 16)
      edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
  
      out = model(x, edge_index)
      assert out.size() == (3, 8)
  
      if is_full_test():
          jit = torch.jit.export(model)
          out = jit(x, edge_index)
          assert out.size() == (3, 8)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_graph_unet() without return types