<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _beam_decode(self, features, decode_length, beam_size, top_beams, alpha, use_tpu=False):
 """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 """

    return self._beam_decode_slow(features, decode_length, beam_size, top_beams,
                                  alpha, use_tpu)