docstr: Uses `librosa` to compute the Mel-frequency spectral coefficients (MFCCs) of data within an audio file. They are a common feature used in speech and audio processing. Example: https://centaur.reading.ac.uk/88046/3/ESR_for_home_AI.pdf
  
  Input data to this mixer MUST BE the location of the audio files.
  
  The output feature for any given audio file is a 2D array, flattened into a 1D one to comply with the expected format in lightwood mixers.
  
  This encoder currently does not support a `decode()` call; models with an audio output will not work. 
  
  :param is_target: whether this encoder's column is the target. Is always false, as decoded audio is not available.
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code: def __init__(self, is_target: bool = False):
      """
  
      Uses `librosa` to compute the Mel-frequency spectral coefficients (MFCCs) of data within an audio file. They are a common feature used in speech and audio processing. Example: https://centaur.reading.ac.uk/88046/3/ESR_for_home_AI.pdf
  
      Input data to this mixer MUST BE the location of the audio files.
  
      The output feature for any given audio file is a 2D array, flattened into a 1D one to comply with the expected format in lightwood mixers.
  
      This encoder currently does not support a `decode()` call; models with an audio output will not work.
  
      :param is_target: whether this encoder's column is the target. Is always false, as decoded audio is not available.
      """  # noqa
      assert not is_target
      super().__init__(is_target)
  
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 1 to create a new MFCCEncoder object from inherited base classes: BaseEncoder with example: obj = MFCCEncoder(is_target)