code: def test_case(self):
      vocab = Vocabulary().add_word_lst("This is a test .".split())
      embed = StaticEmbedding(vocab, embedding_dim=5)
      encoder = LSTMSeq2SeqEncoder(embed, hidden_size=5, num_layers=1)
      words_idx = torch.LongTensor([0, 1, 2]).unsqueeze(0)
      seq_len = torch.LongTensor([3])
  
      encoder_output, encoder_mask = encoder(words_idx, seq_len)
      assert encoder_mask.size() == (1, 3)
  
imports: import pytest
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
  from fastNLP import Vocabulary
label_desc: Use image node_id 1 for calling the TestBiLSTMEncoder obj's underlying member method code with example usage: obj.test_case() without return types