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","."]
code: def train_text_filepaths(self, tmp_dir):
      all_files = self.maybe_prepare_text(tmp_dir)
      return [
          f
          for i, f in enumerate(all_files)
          if i % self.dev_fraction != 0
      ]
  
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 2 for calling the LanguagemodelWikiXmlV8kL1k obj's underlying member method code with example usage: obj.train_text_filepaths(tmp_dir) and returns: unknown