code: def forward(self, g, x):
      x = self.conv(g, x)
  
      if self.num_nonl_layers == 2:
          x = F.relu(x)
          x = self.fc(x)
  
      x = F.relu(x)
      x = self.fc2(x)
      return x
  
imports: import argparse
  import math
  import dgl
  import torch
  import torch.nn.functional
  from dgl.dataloading.negative_sampler import GlobalUniform
  from dgl.nn.pytorch import GraphConv, SAGEConv
  from ogb.linkproppred import DglLinkPropPredDataset, Evaluator
  from torch.nn import Linear
  from torch.utils.data import DataLoader
label_desc: Use image node_id 3 for calling the NGNN_GCNConv obj's underlying member method code with example usage: obj.forward(g, x) and returns: x