code: def tts(
      model_name="tts_models/en/ljspeech/tacotron2-DCA",
      vocoder_name=None,
      use_cuda=False,
  ):
      """TTS entry point for PyTorch Hub that provides a Synthesizer object to synthesize speech from a give text.
  
      Example:
          >>> synthesizer = torch.hub.load('coqui-ai/TTS', 'tts', source='github')
          >>> wavs = synthesizer.tts("This is a test! This is also a test!!")
              wavs - is a list of values of the synthesized speech.
  
      Args:
          model_name (str, optional): One of the model names from .model.json. Defaults to 'tts_models/en/ljspeech/tacotron2-DCA'.
          vocoder_name (str, optional): One of the model names from .model.json. Defaults to 'vocoder_models/en/ljspeech/multiband-melgan'.
          pretrained (bool, optional): [description]. Defaults to True.
  
      Returns:
          TTS.utils.synthesizer.Synthesizer: Synthesizer object wrapping both vocoder and tts models.
      """
      manager = ModelManager()
  
      model_path, config_path, model_item = manager.download_model(
          model_name
      )
      vocoder_name = (
          model_item["default_vocoder"]
          if vocoder_name is None
          else vocoder_name
      )
      vocoder_path, vocoder_config_path, _ = manager.download_model(
          vocoder_name
      )
  
      # create synthesizer
      synt = Synthesizer(
          tts_checkpoint=model_path,
          tts_config_path=config_path,
          vocoder_checkpoint=vocoder_path,
          vocoder_config=vocoder_config_path,
          use_cuda=use_cuda,
      )
      return synt
  
imports: import torch
  from TTS.utils.manage import ModelManager
  from TTS.utils.synthesizer import Synthesizer
label_desc: Use image node_id 1 for calling a global function with example usage: tts(model_name, vocoder_name, use_cuda) and returns: synt