code: def forward(self, x, edge_index):
      for conv in self.convs[:-1]:
          x = conv(x, edge_index)
          x = F.relu(x)
          x = F.dropout(x, p=self.dropout, training=self.training)
      x = self.convs[-1](x, edge_index)
      return x
  
imports: import argparse
  import torch
  import numpy
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from torch_sparse import SparseTensor
  from torch_geometric.data import GraphSAINTRandomWalkSampler
  from torch_geometric.nn import GCNConv
  from torch_geometric.utils import to_undirected
  from ogb.linkproppred import PygLinkPropPredDataset, Evaluator
  from logger import Logger
label_desc: Use image node_id 3 for calling the GCN obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x