docstr: create actors for parallel training.
          
docstr_tok: ["create","actors","for","parallel","training","."]
code: def create_actors(self):
      """create actors for parallel training."""
  
      parl.connect(self.config["master_address"])
      self.remote_count = 0
      for i in range(self.config["actor_num"]):
          signal_queue = queue.Queue()
          output_queue = queue.Queue()
          self.actors_signal_input_queues.append(signal_queue)
          self.actors_output_queues.append(output_queue)
  
          self.remote_count += 1
  
          remote_thread = threading.Thread(
              target=self.run_remote_sample,
              args=(signal_queue, output_queue),
          )
          remote_thread.setDaemon(True)
          remote_thread.start()
  
      logger.info("All remote actors are ready, begin to learn.")
  
imports: from parl.utils import check_version_for_fluid
  import gym
  import os
  import parl
  import numpy
  import threading
  import utils
  from es import ES
  from obs_filter import MeanStdFilter
  from mujoco_agent import MujocoAgent
  from mujoco_model import MujocoModel
  from noise import SharedNoiseTable
  from parl.utils import logger, summary
  from parl.utils.window_stat import WindowStat
  from six.moves import queue
  from actor import Actor
label_desc: Use image node_id 2 for calling the Learner obj's underlying member method code with example usage: obj.create_actors() without return types