code: def learn(self):
      result_q = queue.Queue()
      th_list = []
      for j in range(args.ensemble_num):
          t = threading.Thread(
              target=self.train_single_model, args=(j, result_q)
          )
          th_list.append(t)
      start_time = time.time()
      for t in th_list:
          t.start()
      for t in th_list:
          t.join()
  
      logger.info(
          "[learn] {} heads, time consuming:{}".format(
              args.ensemble_num, time.time() - start_time
          )
      )
      for t in th_list:
          result = result_q.get()
          for critic_loss in result:
              self.scalars_manager.feed_critic_loss(critic_loss)
  
imports: import grpc
  import json
  import numpy
  import os
  import queue
  import simulator_pb2
  import simulator_pb2_grpc
  import six
  import time
  import threading
  from args import get_server_args
  from collections import defaultdict
  from concurrent import futures
  from multi_head_ddpg import MultiHeadDDPG
  from opensim_agent import OpenSimAgent
  from opensim_model import OpenSimModel
  from parl.utils import logger
  from replay_memory import ReplayMemory
  from utils import calc_indicators, ScalarsManager, TransitionExperience
label_desc: Use image node_id 6 for calling the SimulatorServer obj's underlying member method code with example usage: obj.learn() without return types