docstr: Audio-encoding is rule-based; prepare only sets the size of the output dimension based on encoding the first example within the priming data.
  
  :param priming_data: Training data, in the form of file locations
docstr_tok: ["Audio-encoding","is","rule-based",";","prepare","only","sets","the","size","of","the","output","dimension","based","on","encoding","the","first","example","within","the","priming","data",".",":","param","priming_data",":","Training","data",",","in","the","form","of","file","locations"]
code: def prepare(self, priming_data: Iterable[str]):
      """
      Audio-encoding is rule-based; prepare only sets the size of the output dimension based on encoding the first example within the priming data.
  
      :param priming_data: Training data, in the form of file locations
      """  # noqa
      self.is_prepared = True
      priming_data = list(priming_data)
      ele = self.encode([str(priming_data[0])])[0]
      self.output_size = len(ele)
  
file_path: lightwood/lightwood/encoder/audio/mfcc.py
imports: import librosa
  import torch
  import warnings
  from lightwood.encoder.base import BaseEncoder
  from lightwood.helpers.io import read_from_path_or_url
  from lightwood.helpers.log import log
  from typing import Iterable
label_desc: Use image node_id 2 for calling the MFCCEncoder obj's underlying member method code with example usage: obj.prepare(priming_data) without return types