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 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 ExternalNodeCollator obj's underlying member method code with example usage: obj.collate(items) and returns: input_nodes,  output_nodes,  mfgs