docstr: Test that the vocab cutoff leaves words we expect in the vocab, but not rare words
docstr_tok: ["Test","that","the","vocab","cutoff","leaves","words","we","expect","in","the","vocab",",","but","not","rare","words"]
code: def test_vocab_cutoff(self, tmp_path, wordvec_pretrain_file):
      """
      Test that the vocab cutoff leaves words we expect in the vocab, but not rare words
      """
      trainer = self.run_training(
          tmp_path,
          wordvec_pretrain_file,
          TRAIN_DATA,
          DEV_DATA,
          extra_args=["--word_cutoff", "3"],
      )
      word_vocab = trainer.vocab["word"]
      assert "of" in word_vocab
      assert "officials" in TRAIN_DATA
      assert "officials" not in word_vocab
  
imports: import os
  import pytest
  import torch
  from stanza.models import tagger
  from stanza.models.common import pretrain
  from stanza.models.pos.trainer import Trainer
  from stanza.tests import TEST_WORKING_DIR, TEST_MODELS_DIR
  from stanza.utils.training.common import choose_pos_charlm, build_charlm_args
label_desc: Use image node_id 5 for calling the TestTagger obj's underlying member method code with example usage: obj.test_vocab_cutoff(tmp_path, wordvec_pretrain_file) without return types