code: def test_forward_works_even_with_empty_sequences(self):
      lstm = LSTM(
          bidirectional=True,
          num_layers=3,
          input_size=3,
          hidden_size=7,
          batch_first=True,
      )
      encoder = PytorchSeq2SeqWrapper(lstm)
  
      tensor = torch.rand([5, 7, 3])
      tensor[1, 6:, :] = 0
      tensor[2, :, :] = 0
      tensor[3, 2:, :] = 0
      tensor[4, :, :] = 0
      mask = torch.ones(5, 7)
      mask[1, 6:] = 0
      mask[2, :] = 0
      mask[3, 2:] = 0
      mask[4, :] = 0
  
      results = encoder(tensor, mask)
  
      for i in (0, 1, 3):
          assert not (results[i] == 0.0).data.all()
      for i in (2, 4):
          assert (results[i] == 0.0).data.all()
  
imports: from __future__ import with_statement
  from __future__ import absolute_import
  import numpy
  from numpy.testing import assert_almost_equal
  import pytest
  import torch
  from torch.nn import LSTM, GRU
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.modules.seq2seq_encoders import PytorchSeq2SeqWrapper
  from allennlp.nn.util import sort_batch_by_length, get_lengths_from_binary_sequence_mask
label_desc: Use image node_id 2 for calling the TestPytorchSeq2SeqWrapper obj's underlying member method code with example usage: obj.test_forward_works_even_with_empty_sequences() without return types