code: def eval_model_multithread(pred, nr_eval, get_player_fn):
      """
      Args:
          pred (OfflinePredictor): state -> [#action]
      """
      NR_PROC = min(multiprocessing.cpu_count() // 2, 8)
      with pred.sess.as_default():
          mean, max = eval_with_funcs(
              [pred] * NR_PROC, nr_eval, get_player_fn, verbose=True
          )
      logger.info("Average Score: {}; Max Score: {}".format(mean, max))
  
file_path: tensorpack/examples/DeepQNetwork/common.py
imports: import multiprocessing
  import numpy
  import random
  import time
  from six.moves import queue
  from tensorpack.callbacks import Callback
  from tensorpack.utils import logger, get_tqdm
  from tensorpack.utils.concurrency import ShareSessionThread, StoppableThread
  from tensorpack.utils.stats import StatCounter
label_desc: Use image node_id 4 for calling a global function with example usage: eval_model_multithread(pred, nr_eval, get_player_fn) without return types