code: def get_dist_run_id(cfg, num_nodes):
      """
      For multi-gpu training with PyTorch, we have to specify
      how the gpus are going to rendezvous. This requires specifying
      the communication method: file, tcp and the unique rendezvous run_id that
      is specific to 1 run.
  
      We recommend:
          1) for 1-node: use init_method=tcp and run_id=auto
          2) for multi-node, use init_method=tcp and specify run_id={master_node}:{port}
      """
      init_method = cfg.DISTRIBUTED.INIT_METHOD
      run_id = cfg.DISTRIBUTED.RUN_ID
      if init_method == "tcp" and cfg.DISTRIBUTED.RUN_ID == "auto":
          assert (
              num_nodes == 1
          ), "cfg.DISTRIBUTED.RUN_ID=auto is allowed for 1 machine only."
          port = find_free_tcp_port()
          run_id = f"localhost:{port}"
      elif init_method == "file":
          if num_nodes > 1:
              logging.warning(
                  "file is not recommended to use for distributed training on > 1 node"
              )
          # Find a unique tempfile if needed.
          if not run_id or run_id == "auto":
              unused_fno, run_id = tempfile.mkstemp()
      elif init_method == "tcp" and cfg.DISTRIBUTED.NUM_NODES > 1:
          assert cfg.DISTRIBUTED.RUN_ID, "please specify RUN_ID for tcp"
      elif init_method == "env":
          assert (
              num_nodes == 1
          ), "can not use 'env' init method for multi-node. Use tcp"
      return run_id
  
imports: import collections
  import collections.abc
  import logging
  import os
  import random
  import sys
  import tempfile
  import time
  from functools import partial, wraps
  from typing import Tuple
  import numpy
  import pkg_resources
  import torch
  import torch.multiprocessing
  from iopath.common.file_io import g_pathmgr
  from scipy.sparse import csr_matrix
  from vissl.utils.extract_features_utils import ExtractedFeaturesLoader
label_desc: Use image node_id 7 for calling a global function with example usage: get_dist_run_id(cfg, num_nodes) and returns: run_id