class_docstr: Language dependent tokenizer of text document.
class_docstr_tok: ["Language","dependent","tokenizer","of","text","document","."]
code: def _get_sentence_tokenizer(self, language):
      if language in self.SPECIAL_SENTENCE_TOKENIZERS:
          return self.SPECIAL_SENTENCE_TOKENIZERS[language]
      try:
          path = to_string("tokenizers/punkt/%s.pickle") % to_string(
              language
          )
          return nltk.data.load(path)
      except (LookupError, zipfile.BadZipfile) as e:
          raise LookupError(
              "NLTK tokenizers are missing or the language is not supported.\n"
              """Download them by following command: python -c "import nltk; nltk.download('punkt')"\n"""
              "Original error was:\n" + str(e)
          )
  
imports: from __future__ import absolute_import
  from __future__ import division, print_function, unicode_literals
  import re
  import string
  import zipfile
  import nltk
  from .._compat import to_string, to_unicode, unicode
  from ..utils import normalize_language
label_desc: Use image node_id 3 for calling the Tokenizer obj's underlying member method code with example usage: obj._get_sentence_tokenizer(language) and returns: self, nltk