code: def start_client_mul_role(i):
      os.environ["DGL_DIST_MODE"] = "distributed"
      # Initialize creates kvstore !
      dgl.distributed.initialize(ip_config="kv_ip_mul_config.txt")
      if i == 0:  # block one trainer
          time.sleep(5)
      kvclient = dgl.distributed.kvstore.get_kvstore()
      kvclient.barrier()
      print("i: %d role: %s" % (i, kvclient.role))
  
      assert dgl.distributed.role.get_num_trainers() == 2
      assert dgl.distributed.role.get_trainer_rank() < 2
      print(
          "trainer rank: %d, global rank: %d"
          % (
              dgl.distributed.role.get_trainer_rank(),
              dgl.distributed.role.get_global_rank(),
          )
      )
      dgl.distributed.exit_client()
  
imports: import multiprocessing
  import os
  import socket
  import time
  import unittest
  import backend
  import dgl
  import numpy
  from dgl.graph_index import create_graph_index
  from numpy.testing import assert_array_equal
  from scipy import sparse
  from utils import generate_ip_config, reset_envs
label_desc: Use image node_id 8 for calling a global function with example usage: start_client_mul_role(i) without return types