code: def collate(self, items):
      input_nodes, output_nodes, mfgs = super().collate(items)
      # Copy input features
      mfgs[0].srcdata["x"] = torch.FloatTensor(self.feats[input_nodes])
      mfgs[-1].dstdata["y"] = torch.LongTensor(
          self.label[output_nodes - self.offset]
      )
      return input_nodes, output_nodes, mfgs
  
imports: import argparse
  import math
  import sys
  from collections import OrderedDict
  import dgl
  import dgl.nn
  import numpy
  import torch
  import torch.multiprocessing
  import torch.nn
  import torch.nn.functional
  import tqdm
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 2 for calling the ExternalNodeCollator obj's underlying member method code with example usage: obj.collate(items) and returns: input_nodes,  output_nodes,  mfgs