code: def _maybe_download_corpus(tmp_dir):
      """Download and unpack the corpus.
  
      Args:
        tmp_dir: directory containing dataset.
      """
      corpus_url = (
          "http://www.statmt.org/lm-benchmark/"
          "1-billion-word-language-modeling-benchmark-r13output.tar.gz"
      )
      corpus_filename = os.path.basename(corpus_url)
      corpus_filepath = os.path.join(tmp_dir, corpus_filename)
      if not os.path.exists(corpus_filepath):
          generator_utils.maybe_download(
              tmp_dir, corpus_filename, corpus_url
          )
          with tarfile.open(corpus_filepath, "r:gz") as corpus_tar:
              corpus_tar.extractall(tmp_dir)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tarfile
  from six.moves import range
  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 5 for calling a global function with example usage: _maybe_download_corpus(tmp_dir) without return types