code: def torch_version() -> Tuple[int, ...]:
      numbering = torch.__version__.split("+")[0].split(".")[:3]
  
      # Catch torch version if run against internal pre-releases, like `1.8.0a0fb`,
      if not numbering[2].isnumeric():
          # Two options here:
          # - either skip this version (minor number check is not relevant)
          # - or check that our codebase is not broken by this ongoing development.
  
          # Assuming that we're interested in the second usecase more than the first,
          # return the pre-release or dev numbering
          numbering[2] = "0"
  
      return tuple(int(n) for n in numbering)
  
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 21 for calling a global function with example usage: torch_version() and returns: tuple