code: def compute_mfcc(
      audio,
      lo_hz=20.0,
      hi_hz=8000.0,
      fft_size=1024,
      mel_bins=128,
      mfcc_bins=13,
      overlap=0.75,
      pad_end=True,
      sample_rate=16000,
  ):
      """Calculate Mel-frequency Cepstral Coefficients."""
      logmel = compute_logmel(
          audio,
          lo_hz=lo_hz,
          hi_hz=hi_hz,
          bins=mel_bins,
          fft_size=fft_size,
          overlap=overlap,
          pad_end=pad_end,
          sample_rate=sample_rate,
      )
      mfccs = tf.signal.mfccs_from_log_mel_spectrograms(logmel)
      return mfccs[..., :mfcc_bins]
  
imports: import crepe
  from ddsp import core
  from ddsp.core import safe_log
  from ddsp.core import tf_float32
  import gin
  import librosa
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
label_desc: Use image node_id 7 for calling a global function with example usage: compute_mfcc(audio, lo_hz, hi_hz, fft_size, mel_bins, mfcc_bins, overlap, pad_end, sample_rate) and returns: mfccs