code: def griffin_lim(magnitudes, n_iters=50, n_fft=1024):
      """
      Griffin-Lim algorithm to convert magnitude spectrograms to audio signals
      """
      phase = np.exp(2j * np.pi * np.random.rand(*magnitudes.shape))
      complex_spec = magnitudes * phase
      signal = librosa.istft(complex_spec)
      if not np.isfinite(signal).all():
          logging.warning("audio was not finite, skipping audio saving")
          return np.array([0])
  
      for _ in range(n_iters):
          _, phase = librosa.magphase(librosa.stft(signal, n_fft=n_fft))
          complex_spec = magnitudes * phase
          signal = librosa.istft(complex_spec)
      return signal
  
imports: from enum import Enum
  from typing import Optional, Tuple
  import librosa
  import matplotlib.pylab
  import numpy
  import torch
  from einops import rearrange
  from numba import jit, prange
  from nemo.collections.tts.torch.tts_data_types import DATA_STR2DATA_CLASS, MAIN_DATA_TYPES, WithLens
  from nemo.utils import logging
  from nemo.utils.decorators import deprecated
label_desc: Use image node_id 11 for calling a global function with example usage: griffin_lim(magnitudes, n_iters, n_fft) and returns: signal, np