code: def _load_tacotron2_model(self, model_dir):
      from PyTorch.SpeechSynthesis.Tacotron2.tacotron2 import (
          model as tacotron2,
      )
      from PyTorch.SpeechSynthesis.Tacotron2.tacotron2.text import (
          text_to_sequence,
      )
  
      tacotron2_checkpoint = torch.load(
          os.path.join(
              model_dir, "nvidia_tacotron2pyt_fp32_20190427.pth"
          )
      )
      tacotron2_state_dict = self._unwrap_distributed(
          tacotron2_checkpoint["state_dict"]
      )
      tacotron2_config = tacotron2_checkpoint["config"]
      self.tacotron2_model = tacotron2.Tacotron2(**tacotron2_config)
      self.tacotron2_model.load_state_dict(tacotron2_state_dict)
      self.tacotron2_model.text_to_sequence = text_to_sequence
      self.tacotron2_model.to(self.device)
  
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 3 for calling the WaveGlowSpeechSynthesizer obj's underlying member method code with example usage: obj._load_tacotron2_model(model_dir) without return types