code: def test_for_tuple_unpack(self):
      def for_tuple_unpack(x, y):
          for i, j in [[3, 4], [5, 6], [7, 8]]:
              x += i
              y += j
          return x, y
  
      self.checkScript(
          for_tuple_unpack, (torch.tensor(3), torch.tensor(5))
      )
  
      def nested_tuple_unpack(x, y):
          # type: (List[int], List[int]) -> int
          sum = 0
          for i, (j, k), v in zip(x, enumerate(x), y):
              sum += i + j + k + v
          return sum
  
      self.checkScript(nested_tuple_unpack, ([1, 3, 5], [2, 4, 6]))
  
imports: import os
  import sys
  import torch
  from torch.testing._internal.jit_utils import JitTestCase, make_global
  from torch.testing._internal.common_utils import IS_WINDOWS
  from collections import namedtuple
  from typing import List, Tuple, Dict, NamedTuple
label_desc: Use image node_id 24 for calling the TestTyping obj's underlying member method code with example usage: obj.test_for_tuple_unpack() and returns: x,  y, sum