code: def forward(self, mfgs, x):
      for i in range(len(mfgs)):
          mfg = mfgs[i]
          x_dst = x[: mfg.num_dst_nodes()]
          n_src = mfg.num_src_nodes()
          n_dst = mfg.num_dst_nodes()
          mfg = dgl.block_to_graph(mfg)
          x_skip = self.skips[i](x_dst)
          for j in range(self.num_etypes):
              subg = mfg.edge_subgraph(
                  mfg.edata["etype"] == j, relabel_nodes=False
              )
              x_skip += self.convs[i][j](subg, (x, x_dst)).view(
                  -1, self.hidden_channels
              )
          x = self.norms[i](x_skip)
          x = F.elu(x)
          x = self.dropout(x)
      return self.mlp(x)
  
imports: import argparse
  import time
  import dgl
  import dgl.function
  import dgl.nn
  import numpy
  import ogb
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
label_desc: Use image node_id 2 for calling the RGAT obj's underlying member method code with example usage: obj.forward(mfgs, x) and returns: self