code: def synthesis_with_griffinlim(self, mel_output, cfg):
      # synthesis with griffin-lim
      mel_output = fluid.layers.transpose(
          fluid.layers.squeeze(mel_output, [0]), [1, 0]
      )
      mel_output = np.exp(mel_output.numpy())
      basis = librosa.filters.mel(
          cfg["sr"],
          cfg["n_fft"],
          cfg["num_mels"],
          fmin=cfg["fmin"],
          fmax=cfg["fmax"],
      )
      inv_basis = np.linalg.pinv(basis)
      spec = np.maximum(1e-10, np.dot(inv_basis, mel_output))
  
      wav = librosa.core.griffinlim(
          spec ** cfg["power"],
          hop_length=cfg["hop_length"],
          win_length=cfg["win_length"],
      )
  
      return wav
  
imports: import os
  import ast
  import argparse
  import importlib.util
  import nltk
  import paddle.fluid
  import paddle.fluid.dygraph
  import paddlehub
  from paddlehub.module.module import runnable
  from paddlehub.common.utils import mkdir
  from paddlehub.module.nlp_module import DataFormatError
  from paddlehub.common.logger import logger
  from paddlehub.module.module import moduleinfo, serving
  from paddlehub.common.dir import THIRD_PARTY_HOME
  from paddlehub.common.downloader import default_downloader
label_desc: Use image node_id 3 for calling the TransformerTTS obj's underlying member method code with example usage: obj.synthesis_with_griffinlim(mel_output, cfg) and returns: wav