class_docstr: Synchronizes policy updates and other information across workers on local machine.
  
  Used for dummy and sub-process distribution scenarios.
  
  The BroadcastingContainer object can be read by all workers in order to update their policy, and it can be
  accessed by the main thread to write the updated policy from the learner into it.
class_docstr_tok: ["Synchronizes","policy","updates","and","other","information","across","workers","on","local","machine",".","Used","for","dummy","and","sub-process","distribution","scenarios",".","The","BroadcastingContainer","object","can","be","read","by","all","workers","in","order","to","update","their","policy",",","and","it","can","be","accessed","by","the","main","thread","to","write","the","updated","policy","from","the","learner","into","it","."]
docstr: Return the current policy version number (to check whether fetching a new state dict is necessary).
docstr_tok: ["Return","the","current","policy","version","number","(","to","check","whether","fetching","a","new","state","dict","is","necessary",")","."]
code: def policy_version(self) -> int:
      """Return the current policy version number (to check whether fetching a new state dict is necessary)."""
      return self._policy_version_counter
  
file_path: maze/maze/train/parallelization/broadcasting_container.py
imports: from multiprocessing.managers import BaseManager
  from typing import Dict, NoReturn, Optional
  import cloudpickle
label_desc: Use image node_id 4 for calling the BroadcastingContainer obj's underlying member method code with example usage: obj.policy_version() and returns: self