code: def test_stacked_alternating_lstm_completes_forward_pass(self):
      input_tensor = torch.rand(4, 5, 3)
      input_tensor[1, 4:, :] = 0.0
      input_tensor[2, 2:, :] = 0.0
      input_tensor[3, 1:, :] = 0.0
      input_tensor = pack_padded_sequence(
          input_tensor, [5, 4, 2, 1], batch_first=True
      )
      lstm = StackedAlternatingLstm(3, 7, 3)
      output, _ = lstm(input_tensor)
      output_sequence, _ = pad_packed_sequence(output, batch_first=True)
      numpy.testing.assert_array_equal(
          output_sequence.data[1, 4:, :].numpy(), 0.0
      )
      numpy.testing.assert_array_equal(
          output_sequence.data[2, 2:, :].numpy(), 0.0
      )
      numpy.testing.assert_array_equal(
          output_sequence.data[3, 1:, :].numpy(), 0.0
      )
  
file_path: allennlp/tests/modules/stacked_alternating_lstm_test.py
imports: import numpy
  import torch
  from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
  from allennlp.modules.stacked_alternating_lstm import StackedAlternatingLstm
  from allennlp.common.testing import AllenNlpTestCase
label_desc: Use image node_id 1 for calling the TestStackedAlternatingLstm obj's underlying member method code with example usage: obj.test_stacked_alternating_lstm_completes_forward_pass() without return types