code: def __init__(self, seed):
      assert isinstance(seed, int)
      self.rng_state = get_rng_state()
  
      torch.manual_seed(seed)
      if torch.cuda.is_available():
          torch.cuda.manual_seed(seed)
  
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 1 to create a new set_torch_seed object  with example: obj = set_torch_seed(seed)