code: def load_tacotron(tacotron_model_path, max_decoder_steps):
      ckpt_dict = torch.load(tacotron_model_path)
      hparams = ckpt_dict["hparams"]
      hparams.max_decoder_steps = max_decoder_steps
      sr = hparams.sampling_rate
      model = Tacotron2(hparams)
      model.load_state_dict(ckpt_dict["model_dict"])
      model = model.cuda().eval().half()
      return model, sr, hparams
  
imports: import torch
  from examples.textless_nlp.gslm.unit2speech.tacotron2.model import Tacotron2
  from examples.textless_nlp.gslm.unit2speech.tacotron2.waveglow_denoiser import Denoiser
label_desc: Use image node_id 3 for calling a global function with example usage: load_tacotron(tacotron_model_path, max_decoder_steps) and returns: model,  sr,  hparams