code: def test_ogbg_gin(virtual_node):
      # Test for ogbg-mol datasets
      data_info = {"name": "ogbg-molhiv", "out_size": 1}
      model = OGBGGIN(
          data_info,
          embed_size=10,
          num_layers=2,
          virtual_node=virtual_node,
      )
      num_nodes = 5
      num_edges = 15
      g1 = dgl.rand_graph(num_nodes, num_edges)
      g2 = dgl.rand_graph(num_nodes, num_edges)
      g = dgl.batch([g1, g2])
      num_nodes = g.num_nodes()
      num_edges = g.num_edges()
      nfeat = torch.zeros(num_nodes, 9).long()
      efeat = torch.zeros(num_edges, 3).long()
      model(g, nfeat, efeat)
  
      # Test for non-ogbg-mol datasets
      data_info = {
          "name": "a_dataset",
          "out_size": 1,
          "node_feat_size": 15,
          "edge_feat_size": 5,
      }
      model = OGBGGIN(
          data_info,
          embed_size=10,
          num_layers=2,
          virtual_node=virtual_node,
      )
      nfeat = torch.randn(num_nodes, data_info["node_feat_size"])
      efeat = torch.randn(num_edges, data_info["edge_feat_size"])
      model(g, nfeat, efeat)
  
file_path: dgl/tests/go/test_model.py
imports: import dgl
  import pytest
  import torch
  from utils.graph_cases import get_cases
  from dglgo.model import *
label_desc: Use image node_id 11 for calling a global function with example usage: test_ogbg_gin(virtual_node) without return types