code: def test_unpack_sequence(self):
      # single dimensional
      a = torch.tensor([1, 2, 3])
      b = torch.tensor([4, 5])
      c = torch.tensor([6])
      sequences = [a, b, c]
  
      packed_sequences = rnn_utils.pack_sequence(
          sequences, enforce_sorted=False
      )
      unpacked_sequences = rnn_utils.unpack_sequence(packed_sequences)
      self.assertEqual(sequences, unpacked_sequences)
  
      # more dimensions
      maxlen = 9
      for num_dim in (0, 1, 2, 3):
          sequences = []
          trailing_dims = [4] * num_dim
          for i in range(1, maxlen + 1):
              seq_len = i * i
              sequences.append(torch.rand(seq_len, 5, *trailing_dims))
          random.shuffle(sequences)
  
          packed_sequences = rnn_utils.pack_sequence(
              sequences, enforce_sorted=False
          )
          unpacked_sequences = rnn_utils.unpack_sequence(
              packed_sequences
          )
          self.assertEqual(sequences, unpacked_sequences)
  
imports: import itertools
  import random
  import torch
  from torch.testing._internal.common_utils import TestCase, run_tests
  import torch.nn.utils.rnn
label_desc: Use image node_id 14 for calling the PackedSequenceTest obj's underlying member method code with example usage: obj.test_unpack_sequence() without return types