code: def test_forward_does_not_compress_tensors_padded_to_greater_than_the_max_sequence_length(
      self,
  ):
      lstm = LSTM(
          bidirectional=True,
          num_layers=3,
          input_size=3,
          hidden_size=7,
          batch_first=True,
      )
      encoder = PytorchSeq2SeqWrapper(lstm)
      input_tensor = torch.rand([5, 8, 3])
      input_tensor[:, 7, :] = 0
      mask = torch.ones(5, 8).bool()
      mask[:, 7] = False
  
      encoder_output = encoder(input_tensor, mask)
      assert encoder_output.size(1) == 8
  
imports: 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 6 for calling the TestPytorchSeq2SeqWrapper obj's underlying member method code with example usage: obj.test_forward_does_not_compress_tensors_padded_to_greater_than_the_max_sequence_length() without return types