class_docstr: Encoder class for saving and loading waveforms.
class_docstr_tok: ["Encoder","class","for","saving","and","loading","waveforms","."]
docstr: Transform a sequence of float32 into a waveform.
  
  Args:
    ids: list of integers to be converted.
  
  Returns:
    Path to the temporary file where the waveform was saved.
  
  Raises:
    ValueError: if the ids are not of the appropriate size.
docstr_tok: ["Transform","a","sequence","of","float32","into","a","waveform",".","Args",":","ids",":","list","of","integers","to","be","converted",".","Returns",":","Path","to","the","temporary","file","where","the","waveform","was","saved",".","Raises",":","ValueError",":","if","the","ids","are","not","of","the","appropriate","size","."]
code: def decode(self, ids):
      """Transform a sequence of float32 into a waveform.
  
      Args:
        ids: list of integers to be converted.
  
      Returns:
        Path to the temporary file where the waveform was saved.
  
      Raises:
        ValueError: if the ids are not of the appropriate size.
      """
      _, tmp_file_path = tempfile.mkstemp()
      wavfile.write(tmp_file_path, self._sample_rate, np.asarray(ids))
      return tmp_file_path
  
file_path: tensor2tensor/tensor2tensor/data_generators/audio_encoder.py
imports: import os
  from subprocess import call
  import tempfile
  import numpy
  from scipy.io import wavfile
label_desc: Use image node_id 4 for calling the AudioEncoder obj's underlying member method code with example usage: obj.decode(ids) and returns: tmp_file_path