code: def test_lookup_service(
      num_chunks,
      num_parts,
      world_size,
      num_chunks_nodes=None,
      num_chunks_edges=None,
      num_chunks_node_data=None,
      num_chunks_edge_data=None,
  ):
      with tempfile.TemporaryDirectory() as root_dir:
          g = create_chunked_dataset(
              root_dir,
              num_chunks,
              data_fmt="numpy",
              num_chunks_nodes=num_chunks_nodes,
              num_chunks_edges=num_chunks_edges,
              num_chunks_node_data=num_chunks_node_data,
              num_chunks_edge_data=num_chunks_edge_data,
          )
  
          # Step1: graph partition
          in_dir = os.path.join(root_dir, "chunked-data")
          output_dir = os.path.join(root_dir, "parted_data")
          os.system(
              "python3 tools/partition_algo/random_partition.py "
              "--in_dir {} --out_dir {} --num_partitions {}".format(
                  in_dir, output_dir, num_parts
              )
          )
  
          # metadata for original graph
          orig_config = os.path.join(in_dir, "metadata.json")
          orig_schema = read_json(orig_config)
          ntypes = orig_schema[constants.STR_NODE_TYPE]
  
          _, global_nid_ranges = get_idranges(
              orig_schema[constants.STR_NODE_TYPE],
              get_ntype_counts_map(
                  orig_schema[constants.STR_NODE_TYPE],
                  orig_schema[constants.STR_NUM_NODES_PER_TYPE],
              ),
              num_chunks=num_parts,
          )
  
          id_map = dgl.distributed.id_map.IdMap(global_nid_ranges)
  
          # run the test
          _single_machine_run(
              num_parts,
              world_size,
              output_dir,
              ntypes,
              id_map,
              _prepare_test_data(
                  output_dir, ntypes, global_nid_ranges, world_size
              ),
          )
  
imports: import logging
  import os
  import platform
  import tempfile
  from datetime import timedelta
  import dgl
  import numpy
  import pyarrow
  import pytest
  import torch.distributed
  import torch.multiprocessing
  from pytest_utils import create_chunked_dataset
  from tools.distpartitioning import constants, dist_lookup
  from tools.distpartitioning.gloo_wrapper import allgather_sizes
  from tools.distpartitioning.utils import get_idranges, get_ntype_counts_map, read_json
label_desc: Use image node_id 6 for calling a global function with example usage: test_lookup_service(num_chunks, num_parts, world_size, num_chunks_nodes, num_chunks_edges, num_chunks_node_data, num_chunks_edge_data) without return types