code: def _beam_decode(self,
                     features,
                     decode_length,
                     beam_size,
                     top_beams,
                     alpha,
                     use_tpu=False):
      
      return self._beam_decode_slow(features, decode_length, beam_size, top_beams,
                                    alpha, use_tpu)
docs: Beam search decoding.
  
      Models should ideally implement a more efficient version of this function.
  
      Args:
        features: an map of string to `Tensor`
        decode_length: an integer.  How many additional timesteps to decode.
        beam_size: number of beams.
        top_beams: an integer. How many of the beams to return.
        alpha: Float that controls the length penalty. larger the alpha, stronger
          the preference for longer translations.
        use_tpu: A bool, whether to do beam decode on TPU.
  
      Returns:
         samples: an integer `Tensor`. Top samples from the beam search