code: def _get_master_port(self) -> int:
      # MIN_MASTER_PORT, MAX_MASTER_PORT = (1023, 65535)
      MIN_MASTER_PORT, MAX_MASTER_PORT = (20000, 60000)
  
      master_port_str = os.environ.get("MASTER_PORT")
      if master_port_str is None:
          rng = random.Random(self._job_env.job_id)
          return rng.randint(MIN_MASTER_PORT, MAX_MASTER_PORT)
  
      master_port = int(master_port_str)
      # assert MIN_MASTER_PORT <= master_port <= MIN_MASTER_PORT
      return master_port
  
imports: import collections
  import contextlib
  import datetime
  import itertools
  import os
  import random
  import shutil
  import subprocess
  import tempfile
  import time
  import typing
  from pathlib import Path
  from .core import core
  from .core.job_environment import JobEnvironment
  from .core.utils import CommandFunction
  from .core.utils import DelayedSubmission
  from .core.utils import environment_variables
label_desc: Use image node_id 2 for calling the TorchDistributedEnvironment obj's underlying member method code with example usage: obj._get_master_port() and returns: master_port, rng