class_docstr: A language model on English Wikipedia.
  
  XML dump is chopped arbitrarily into sequences of length 1024 tokens,
  without regard to article boundaries.
class_docstr_tok: ["A","language","model","on","English","Wikipedia",".","XML","dump","is","chopped","arbitrarily","into","sequences","of","length","1024","tokens",",","without","regard","to","article","boundaries","."]
docstr: Number of characters of training data to use for generating vocab.
docstr_tok: ["Number","of","characters","of","training","data","to","use","for","generating","vocab","."]
code: def max_chars_for_vocab(self):
      """Number of characters of training data to use for generating vocab."""
      # magic number for backwards compatibility
      return 41800829
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import subprocess
  import numpy
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 8 for calling the LanguagemodelWikiXmlV8kL1k obj's underlying member method code with example usage: obj.max_chars_for_vocab() and returns: int