code: def test_deep_sets_aggregation():
      x = torch.randn(6, 16)
      index = torch.tensor([0, 0, 1, 1, 1, 2])
  
      aggr = DeepSetsAggregation(
          local_nn=Linear(16, 32),
          global_nn=Linear(32, 64),
      )
      aggr.reset_parameters()
      assert str(aggr) == (
          "DeepSetsAggregation("
          "local_nn=Linear(16, 32, bias=True), "
          "global_nn=Linear(32, 64, bias=True))"
      )
  
      out = aggr(x, index)
      assert out.size() == (3, 64)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_deep_sets_aggregation() without return types