code: def test_tagged_corpus_make_vocab_dictionary():
      train_sentence = Sentence("used in training. training is cool.")
  
      corpus: Corpus = Corpus(
          FlairDatapointDataset([train_sentence]),
          sample_missing_splits=False,
      )
  
      vocab = corpus.make_vocab_dictionary(max_tokens=2, min_freq=-1)
  
      assert len(vocab) == 3
      assert "<unk>" in vocab.get_items()
      assert "training" in vocab.get_items()
      assert "." in vocab.get_items()
  
      vocab = corpus.make_vocab_dictionary(max_tokens=-1, min_freq=-1)
  
      assert len(vocab) == 7
  
      vocab = corpus.make_vocab_dictionary(max_tokens=-1, min_freq=2)
  
      assert len(vocab) == 3
      assert "<unk>" in vocab.get_items()
      assert "training" in vocab.get_items()
      assert "." in vocab.get_items()
  
imports: import os
  import pytest
  import flair
  from flair.data import Corpus, Dictionary, Label, Sentence
  from flair.datasets import ColumnCorpus, FlairDatapointDataset, SentenceDataset
label_desc: Use image node_id 8 for calling a global function with example usage: test_tagged_corpus_make_vocab_dictionary() without return types