code: def unpack_variables(args):
      if isinstance(args, tuple):
          return tuple(unpack_variables(elem) for elem in args)
      else:
          return args
  
imports: from torch.jit.annotations import BroadcastingList2, BroadcastingList3
  import torch.nn.functional
  import torch
  import torch.cuda
  import torch.jit
  import torch.jit._logging
  import torch.jit.frontend
  from torch.testing._internal.common_nn import module_tests, new_module_tests
  from torch.testing._internal.common_utils import is_iterable_of_tensors, noncontiguous_like
  import collections
  from copy import deepcopy
  from typing import Any, Dict, List, Union
  import math
  from torch import inf
label_desc: Use image node_id 1 for calling a global function with example usage: unpack_variables(args) and returns: tuple, args