class_docstr: Train sentences tokenizer
docstr: Train sentences tokenizer.
docstr_tok: ["Train","sentences","tokenizer","."]
code: def train_sentence_tokenizer(self, text: str):
      """
      Train sentences tokenizer.
      """
      language_punkt_vars = PunktLanguageVars
  
      # Set punctuation
      if self.punctuation:
          if self.strict:
              language_punkt_vars.sent_end_chars = (
                  self.punctuation + self.strict_punctuation
              )
          else:
              language_punkt_vars.sent_end_chars = self.punctuation
  
      # Set abbreviations
      trainer = PunktTrainer(text, language_punkt_vars)
      trainer.INCLUDE_ALL_COLLOCS = True
      trainer.INCLUDE_ABBREV_COLLOCS = True
  
      tokenizer = PunktSentenceTokenizer(trainer.get_params())
  
      if self.abbreviations:
          for abbreviation in self.abbreviations:
              tokenizer._params.abbrev_types.add(abbreviation)
  
      return tokenizer
  
file_path: cltk/src/cltk/tokenizers/utils.py
imports: import inspect
  import pickle
  from abc import abstractmethod
  from typing import Any, Dict, Generator, List, Set, Tuple
  from nltk.tokenize.punkt import PunktLanguageVars, PunktSentenceTokenizer, PunktTrainer
label_desc: Use image node_id 2 for calling the SentenceTokenizerTrainer obj's underlying member method code with example usage: obj.train_sentence_tokenizer(text) and returns: tokenizer