code: def test_dropword(self):
      # 测试是否可以通过drop word
      vocab = Vocabulary().add_word_lst([chr(i) for i in range(1, 200)])
      embed = StaticEmbedding(
          vocab,
          model_dir_or_name=None,
          embedding_dim=10,
          dropout=0.1,
          word_dropout=0.4,
      )
      for i in range(10):
          length = torch.randint(1, 50, (1,)).item()
          batch = torch.randint(1, 4, (1,)).item()
          words = torch.randint(1, 200, (batch, length)).long()
          embed(words)
  
file_path: fastNLP/tests/embeddings/torch/test_static_embedding.py
imports: import pytest
  import os
  from fastNLP.embeddings.torch import StaticEmbedding
  from fastNLP import Vocabulary
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
  import numpy
label_desc: Use image node_id 3 for calling the TestLoad obj's underlying member method code with example usage: obj.test_dropword() without return types