code: def _maybe_download_corpus(tmp_dir, vocab_type):
    
    filename = os.path.basename(PTB_URL)
    compressed_filepath = generator_utils.maybe_download(
        tmp_dir, filename, PTB_URL)
    ptb_files = []
    ptb_char_files = []
  
    with tarfile.open(compressed_filepath, "r:gz") as tgz:
      files = []
      # Selecting only relevant files.
      for m in tgz.getmembers():
        if "ptb" in m.name and ".txt" in m.name:
          if "char" in m.name:
            ptb_char_files += [m.name]
          else:
            ptb_files += [m.name]
          files += [m]
  
      tgz.extractall(tmp_dir, members=files)
  
    if vocab_type == text_problems.VocabType.CHARACTER:
      return ptb_char_files
    else:
      return ptb_files
docs: Download and unpack the corpus.
  
    Args:
      tmp_dir: directory containing dataset.
      vocab_type: which vocabulary are we using.
  
    Returns:
      The list of names of files.