code: def audio_preprocess(wav, sample_rate):
      wav = wav.numpy()
      melspec = compute_melspec(wav, sample_rate)
      image = mono_to_color(melspec)
      image = normalize(image, mean=None, std=None)
      image = torch.from_numpy(image)
      return image
  
file_path: gradio/demo/musical_instrument_identification/data_setups.py
imports: import os
  import librosa
  import torch
  import numpy
  from torchaudio.transforms import Resample
label_desc: Use image node_id 6 for calling a global function with example usage: audio_preprocess(wav, sample_rate) and returns: image