code: def forward(self, g, in_feat):
      h = self.conv1(g, in_feat)
      h = F.relu(h)
      h = self.conv2(g, h)
      g.ndata["h"] = h
      return dgl.mean_nodes(g, "h")
  
file_path: dgl/tutorials/blitz/5_graph_classification.py
imports: import os
  import dgl
  import dgl.data
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.dataloading import GraphDataLoader
  from torch.utils.data.sampler import SubsetRandomSampler
  from dgl.nn import GraphConv
label_desc: Use image node_id 2 for calling the GCN obj's underlying member method code with example usage: obj.forward(g, in_feat) and returns: dgl