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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_encoder_from_vocab(vocab_filepath):
 """Get encoder from vocab file. If vocab is not found in output dir, it will be copied there by copy_vocab_to_output_dir to clarify the vocab used to generate the data. Args: vocab_filepath: path to vocab, either local or cns Returns: A SubwordTextEncoder vocabulary object. None if the output_parallel_text is set. """

  if not tf.gfile.Exists(vocab_filepath):
    raise ValueError("Vocab file does not exist: {}.".format(vocab_filepath))

  tf.logging.info("Found vocab file: %s", vocab_filepath)
  encoder = text_encoder.SubwordTextEncoder(vocab_filepath)
  return encoder