code: def read_orig_ids(out_dir, fname, num_parts):
      """Read original id files for the partitioned graph objects
  
      Parameters:
      -----------
      out_dir : string
          specifying the directory where the files are located
      fname : string
          file name to read from
      num_parts : integer
          no. of partitions
  
      Returns:
      --------
      dictionary :
          where keys are node/edge types and values are original node
          or edge ids from the original graph
      """
      orig_ids = {}
      for i in range(num_parts):
          ids_path = os.path.join(out_dir, f"part{i}", fname)
          part_ids = load_tensors(ids_path)
          for type, data in part_ids.items():
              if type not in orig_ids:
                  orig_ids[type] = data.numpy()
              else:
                  orig_ids[type] = np.concatenate(
                      (orig_ids[type], data)
                  )
      return orig_ids
  
file_path: dgl/tools/verification_utils.py
imports: import json
  import os
  import constants
  import dgl
  import numpy
  import pyarrow
  import pyarrow.parquet
  import pytest
  import torch
  from dgl.data.utils import load_tensors
  from dgl.distributed.partition import _etype_str_to_tuple, _etype_tuple_to_str, _get_inner_edge_mask, _get_inner_node_mask, RESERVED_FIELD_DTYPE
  from distpartitioning.utils import get_idranges
label_desc: Use image node_id 8 for calling a global function with example usage: read_orig_ids(out_dir, fname, num_parts) and returns: orig_ids