code: def forward(self, x1, edge_index1, batch1, x2, edge_index2, batch2):
      messages1 = self.message_aggr(x1, edge_index1)
      messages2 = self.message_aggr(x2, edge_index2)
  
      attentions1, attentions2 = self.cross_attention2(
          x1, batch1, x2, batch2
      )
  
      new_x1 = self.node_update(x1, messages1, attentions1)
      new_x2 = self.node_update(x2, messages2, attentions2)
  
      return new_x1, new_x2
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch_scatter import scatter
  from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GINConv
label_desc: Use image node_id 8 for calling the GMNConv obj's underlying member method code with example usage: obj.forward(x1, edge_index1, batch1, x2, edge_index2, batch2) and returns: new_x1,  new_x2