code: def forward(self, x, batch):
      x = self.node_net(x)
      if self.use_gate:
          gates = torch.sigmoid(x[:, : self.graph_feat_dim])
          x = x[:, self.graph_feat_dim :] * gates
      graph_feat = self.pool(x, batch)
      graph_feat = self.graph_net(graph_feat)
  
      return graph_feat
  
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 4 for calling the Readout obj's underlying member method code with example usage: obj.forward(x, batch) and returns: graph_feat