code: def compact_and_copy(frontier, seeds):
      block = dgl.to_block(frontier, seeds)
      for col, data in frontier.edata.items():
          if col == dgl.EID:
              continue
          block.edata[col] = data[block.edata[dgl.EID]]
      return block
  
imports: import argparse
  import pickle
  import time
  import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader, IterableDataset
  from ..None import utils
label_desc: Use image node_id 2 for calling a global function with example usage: compact_and_copy(frontier, seeds) and returns: block