code: def test_wrapper_works_with_alternating_lstm(self):
      model = PytorchSeq2VecWrapper(
          StackedAlternatingLstm(
              input_size=4, hidden_size=5, num_layers=3
          )
      )
  
      input_tensor = torch.randn(2, 3, 4)
      mask = torch.ones(2, 3).bool()
      output = model(input_tensor, mask)
      assert tuple(output.size()) == (2, 5)
  
file_path: allennlp/tests/modules/seq2vec_encoders/pytorch_seq2vec_wrapper_test.py
imports: import pytest
  from numpy.testing import assert_almost_equal
  import torch
  from torch.nn import LSTM
  from torch.nn.utils.rnn import pack_padded_sequence
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.modules.seq2vec_encoders import PytorchSeq2VecWrapper
  from allennlp.nn.util import sort_batch_by_length, get_lengths_from_binary_sequence_mask
  from allennlp.modules.stacked_alternating_lstm import StackedAlternatingLstm
label_desc: Use image node_id 7 for calling the TestPytorchSeq2VecWrapper obj's underlying member method code with example usage: obj.test_wrapper_works_with_alternating_lstm() without return types