class_docstr: Configure TF Encrypted to use threads on the local CPU.
  
  Each thread instantiates a different Player to simulate secure computations
  without requiring networking. Mostly intended for development/debugging use.
  
  By default new players will be added when looked up for the first time;
  this is useful for  instance to get a complete list of players involved
  in a particular computation (see `auto_add_unknown_players`).
  
  :param (str) player_names: List of players to be used in the session.
  :param str job_name: The name of the job.
  :param bool auto_add_unknown_players: Auto-add player on first lookup.
code: def get_players(self, names):
      if isinstance(names, str):
          names = [name.strip() for name in names.split(",")]
      assert isinstance(names, list)
      return [
          player for player in self._players if player.name in names
      ]
  
imports: import json
  import logging
  import math
  from abc import ABC
  from abc import abstractmethod
  from collections import OrderedDict
  from pathlib import Path
  import tensorflow
  from .player import Player
label_desc: Use image node_id 5 for calling the LocalConfig obj's underlying member method code with example usage: obj.get_players(names) and returns: unknown