code: def forward(self, graph, feat, edge_weight=None):
      h = self.layers[0](graph, feat, edge_weight=edge_weight)
      hg = self.pooling(graph, h)
  
      for idx in range(self.num_layers - 1):
          h = self.layers[idx + 1](graph, h, edge_weight=edge_weight)
          hg = th.cat((hg, self.pooling(graph, h)), -1)
  
      return h, hg
  
file_path: dgl/examples/pytorch/mvgrl/graph/model.py
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from dgl.nn.pytorch.glob import SumPooling
  from utils import local_global_loss_
label_desc: Use image node_id 2 for calling the GCN obj's underlying member method code with example usage: obj.forward(graph, feat, edge_weight) and returns: h,  hg