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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_or_generate_vocabulary(data_dir, tmp_dir, data_prefix, max_page_size_exp, approx_vocab_size=32768, strip=True):
 """Get or generate the vocabulary. Args: data_dir: a string tmp_dir: a string data_prefix: a string max_page_size_exp: an integer approx_vocab_size: an integer strip: a boolean Returns: a TextEncoder """

  num_pages_for_vocab_generation = approx_vocab_size // 3
  vocab_file = vocab_filename(approx_vocab_size, strip)

  def my_generator(data_prefix):
    """Line generator for vocab."""
    count = 0
    for page in corpus_page_generator(
        all_corpus_files(data_prefix)[::-1], tmp_dir, max_page_size_exp):
      revisions = page["revisions"]
      if revisions:
        text = get_text(revisions[-1], strip=strip)
        yield text
        count += 1
        if count % 100 == 0:
          tf.logging.info("reading pages for vocab %d" % count)
        if count > num_pages_for_vocab_generation:
          break

  return generator_utils.get_or_generate_vocab_inner(data_dir, vocab_file,
                                                     approx_vocab_size,
                                                     my_generator(data_prefix))