class_docstr: TextEncoder backed by a list of tokens.
  
  Tokenization splits on (and drops) non-alphanumeric characters with
  regex "\W+".
class_docstr_tok: ["TextEncoder","backed","by","a","list","of","tokens",".","Tokenization","splits","on","(","and","drops",")","non-alphanumeric","characters","with","regex","``","\\W+","''","."]
code: def save_to_file(self, filename_prefix):
      filename = self._filename(filename_prefix)
      kwargs = {
          "oov_buckets": self._oov_buckets,
          "lowercase": self._lowercase,
          "oov_token": self._oov_token,
      }
      if self._user_defined_tokenizer is not None:
          self._tokenizer.save_to_file(filename)
          kwargs["has_tokenizer"] = True
      self._write_lines_to_file(filename, self._vocab_list, kwargs)
  
imports: from __future__ import unicode_literals
  import abc
  import hashlib
  import json
  import re
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 11 for calling the TokenTextEncoder obj's underlying member method code with example usage: obj.save_to_file(filename_prefix) without return types