code: def test_fvcore():
      from fvcore.nn import FlopCountAnalysis
  
      x = torch.randn(10, 16)
      edge_index = get_random_edge_index(10, 10, num_edges=100)
  
      model = GraphSAGE(16, 32, num_layers=2)
  
      flops = FlopCountAnalysis(model, (x, edge_index))
  
      # TODO (matthias) Currently, aggregations are not properly registered.
      assert flops.by_module()["convs.0"] == 2 * 10 * 16 * 32
      assert flops.by_module()["convs.1"] == 2 * 10 * 32 * 32
      assert flops.total() == (
          flops.by_module()["convs.0"] + flops.by_module()["convs.1"]
      )
      assert flops.by_operator()["linear"] == flops.total()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_fvcore() without return types