def audio(self, tag, audiodata, step=None, sample_rate=44100):
    """Saves audio.

    NB: single channel only right now.

    Args:
      tag: str: label for this data
      audiodata: ndarray [Nsamples,]: data between (-1.0,1.0) to save as wave
      step: int: training step
      sample_rate: sample rate of passed in audio buffer
    """
    audiodata = onp.array(audiodata)
    if step is None:
      step = self._step
    else:
      self._step = step
    audiodata = onp.clip(onp.squeeze(audiodata), -1, 1)
    if audiodata.ndim != 1:
      raise ValueError('Audio data must be 1D.')
    sample_list = (32767.0 * audiodata).astype(int).tolist()
    wio = io.BytesIO()
    wav_buf = wave.open(wio, 'wb')
    wav_buf.setnchannels(1)
    wav_buf.setsampwidth(2)
    wav_buf.setframerate(sample_rate)
    enc = b''.join([struct.pack('<h', v) for v in sample_list])
    wav_buf.writeframes(enc)
    wav_buf.close()
    encoded_audio_bytes = wio.getvalue()
    wio.close()
    audio = Summary.Audio(
        sample_rate=sample_rate,
        num_channels=1,
        length_frames=len(sample_list),
        encoded_audio_string=encoded_audio_bytes,
        content_type='audio/wav')
    summary = Summary(value=[Summary.Value(tag=tag, audio=audio)])
    self.add_summary(summary, step)
Saves audio.

    NB: single channel only right now.

    Args:
      tag: str: label for this data
      audiodata: ndarray [Nsamples,]: data between (-1.0,1.0) to save as wave
      step: int: training step
      sample_rate: sample rate of passed in audio buffer