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: Download corpus if necessary, decompress, split into multiple text files.
  
  Args:
    tmp_dir: directory containing dataset.
  
  Returns:
    list of filepaths for local text files.
docstr_tok: ["Download","corpus","if","necessary",",","decompress",",","split","into","multiple","text","files",".","Args",":","tmp_dir",":","directory","containing","dataset",".","Returns",":","list","of","filepaths","for","local","text","files","."]
code: def maybe_prepare_text(self, tmp_dir):
      """Download corpus if necessary, decompress, split into multiple text files.
  
      Args:
        tmp_dir: directory containing dataset.
  
      Returns:
        list of filepaths for local text files.
      """
      compressed_filename = os.path.basename(self.corpus_url)
      compressed_filepath = os.path.join(tmp_dir, compressed_filename)
      decompressed_filepath = compressed_filepath[:-4]
      split_file_prefix = decompressed_filepath + "-part-"
      split_filepattern = split_file_prefix + "?????"
      split_files = sorted(tf.gfile.Glob(split_filepattern))
      if not split_files:
          if not tf.gfile.Exists(decompressed_filepath):
              if not tf.gfile.Exists(compressed_filepath):
                  generator_utils.maybe_download(
                      tmp_dir, compressed_filepath, self.corpus_url
                  )
              assert not subprocess.call(
                  ["bunzip2", compressed_filepath]
              )
          assert tf.gfile.Exists(decompressed_filepath)
          assert not subprocess.call(
              [
                  "split",
                  "--line-bytes=4M",
                  "--suffix-length=5",
                  "--numeric-suffixes",
                  decompressed_filepath,
                  split_file_prefix,
              ]
          )
          split_files = sorted(tf.gfile.Glob(split_filepattern))
      assert split_files
      return split_files
  
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 1 for calling the LanguagemodelWikiXmlV8kL1k obj's underlying member method code with example usage: obj.maybe_prepare_text(tmp_dir) and returns: split_files