code: def test_graphnet_for_graphs_in_batch():
      # Testing with a batch of Graphs
      try:
          from torch_geometric.data import Batch
      except ModuleNotFoundError:
          raise ImportError(
              "Tests require pytorch geometric to be installed"
          )
  
      n_node_features, n_edge_features, n_global_features = 3, 4, 5
      fgg = FakeGraphGenerator(
          min_nodes=8,
          max_nodes=12,
          n_node_features=n_node_features,
          avg_degree=10,
          n_edge_features=n_edge_features,
          n_classes=2,
          task="graph",
          z=n_global_features,
      )
      graphs = fgg.sample(n_graphs=10)
  
      graphnet = GraphNetwork(
          n_node_features, n_edge_features, n_global_features
      )
  
      graph_batch = Batch()
      graph_batch = graph_batch.from_data_list(
          [graph.to_pyg_graph() for graph in graphs.X]
      )
  
      (
          new_node_features,
          new_edge_features,
          new_global_features,
      ) = graphnet(
          graph_batch.x,
          graph_batch.edge_index,
          graph_batch.edge_attr,
          graph_batch.z,
          graph_batch.batch,
      )
      assert graph_batch.x.size() == new_node_features.size()
      assert graph_batch.edge_attr.size() == new_edge_features.size()
      assert graph_batch.z.size() == new_global_features.size()
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_graphnet_for_graphs_in_batch() without return types