code: def test_hypergraph_conv_with_more_edges_than_nodes():
      in_channels, out_channels = (16, 32)
      hyperedge_index = torch.tensor(
          [
              [0, 0, 1, 1, 2, 3, 3, 3, 2, 1, 2],
              [0, 1, 2, 1, 2, 1, 0, 3, 3, 4, 4],
          ]
      )
      hyperedge_weight = torch.tensor([1.0, 0.5, 0.8, 0.2, 0.7])
      num_nodes = hyperedge_index[0].max().item() + 1
      x = torch.randn((num_nodes, in_channels))
  
      conv = HypergraphConv(in_channels, out_channels)
      assert str(conv) == "HypergraphConv(16, 32)"
      out = conv(x, hyperedge_index)
      assert out.size() == (num_nodes, out_channels)
      out = conv(x, hyperedge_index, hyperedge_weight)
      assert out.size() == (num_nodes, out_channels)
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_hypergraph_conv_with_more_edges_than_nodes() without return types