code: def test_hypergraph_conv_with_more_nodes_than_edges():
      in_channels, out_channels = (16, 32)
      hyperedge_index = torch.tensor(
          [[0, 0, 1, 1, 2, 3], [0, 1, 0, 1, 0, 1]]
      )
      num_nodes = hyperedge_index[0].max().item() + 1
      num_edges = hyperedge_index[1].max().item() + 1
      x = torch.randn((num_nodes, in_channels))
      hyperedge_weight = torch.tensor([1.0, 0.5])
      hyperedge_attr = torch.randn((num_edges, 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)
  
      conv = HypergraphConv(
          in_channels, out_channels, use_attention=True, heads=2
      )
      out = conv(x, hyperedge_index, hyperedge_attr=hyperedge_attr)
      assert out.size() == (num_nodes, 2 * out_channels)
      out = conv(x, hyperedge_index, hyperedge_weight, hyperedge_attr)
      assert out.size() == (num_nodes, 2 * out_channels)
  
      conv = HypergraphConv(
          in_channels,
          out_channels,
          use_attention=True,
          heads=2,
          concat=False,
          dropout=0.5,
      )
      out = conv(x, hyperedge_index, hyperedge_weight, hyperedge_attr)
      assert out.size() == (num_nodes, out_channels)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_hypergraph_conv_with_more_nodes_than_edges() without return types