code: def compute_spectral_contrast(
      audio_data, sample_rate, n_bands=6, fmin=200.0
  ):
      spectral_contrast = librosa.feature.spectral_contrast(
          y=audio_data, sr=sample_rate, n_bands=n_bands, fmin=fmin
      )
      return np.mean(spectral_contrast)
  
imports: import logging
  import os
  import re
  from glob import glob
  from typing import Dict, List
  import librosa
  import numpy
  import torch
  import torchaudio
  import tqdm
  from encodec.utils import convert_audio
  from scipy.special import softmax
  from torch.nn import functional
  from TTS.tts.layers.bark.hubert.hubert_manager import HubertManager
  from TTS.tts.layers.bark.hubert.kmeans_hubert import CustomHubert
  from TTS.tts.layers.bark.hubert.tokenizer import HubertTokenizer
  from TTS.tts.layers.bark.load_model import clear_cuda_cache, inference_mode
label_desc: Use image node_id 8 for calling a global function with example usage: compute_spectral_contrast(audio_data, sample_rate, n_bands, fmin) and returns: np