code: def inference(self, data):
      with torch.no_grad():
          input_lengths = torch.IntTensor([data.size(1)]).to(
              device=self.device, dtype=torch.int64
          )
          mel, _, _ = self.tacotron2_model.infer(data, input_lengths)
          audio = self.waveglow_model.infer(mel)
  
          return audio
  
file_path: serve/examples/text_to_speech_synthesizer/waveglow_handler.py
imports: import logging
  import os
  import uuid
  import zipfile
  import numpy
  import torch
  from scipy.io.wavfile import write
  from waveglow_model import WaveGlow
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 6 for calling the WaveGlowSpeechSynthesizer obj's underlying member method code with example usage: obj.inference(data) and returns: audio