code: def griffin_lim(mag, phase_angle, n_fft, hop, num_iters):
      """Iterative algorithm for phase retrieval from a magnitude spectrogram.
  
      Args:
        mag: Magnitude spectrogram.
        phase_angle: Initial condition for phase.
        n_fft: Size of the FFT.
        hop: Stride of FFT. Defaults to n_fft/2.
        num_iters: Griffin-Lim iterations to perform.
  
      Returns:
        audio: 1-D array of float32 sound samples.
      """
      fft_config = dict(
          n_fft=n_fft, win_length=n_fft, hop_length=hop, center=True
      )
      ifft_config = dict(win_length=n_fft, hop_length=hop, center=True)
      complex_specgram = inv_magphase(mag, phase_angle)
      for i in range(num_iters):
          audio = librosa.istft(complex_specgram, **ifft_config)
          if i != num_iters - 1:
              complex_specgram = librosa.stft(audio, **fft_config)
              _, phase = librosa.magphase(complex_specgram)
              phase_angle = np.angle(phase)
              complex_specgram = inv_magphase(mag, phase_angle)
      return audio
  
imports: import importlib
  import os
  import librosa
  import numpy
  import tensorflow.compat.v1
  import tf_slim
label_desc: Use image node_id 11 for calling a global function with example usage: griffin_lim(mag, phase_angle, n_fft, hop, num_iters) and returns: audio