code: def forward(self, x, edge_index=None):
      x = F.dropout(x, p=0.5, training=self.training)
      x = self.conv1(x, edge_index).relu()
      x = F.dropout(x, p=0.5, training=self.training)
      x = self.conv2(x, edge_index)
      return x
  
file_path: pytorch_geometric/examples/multi_gpu/papers100m_gcn.py
imports: import os
  import time
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn.functional
  from ogb.nodeproppred import PygNodePropPredDataset
  from torch.nn.parallel import DistributedDataParallel
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import GCNConv
label_desc: Use image node_id 2 for calling the GCN obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x