code: def _get_wavernn(self, *, dl_kwargs=None):
      model = WaveRNN(**self._wavernn_params)
      url = f"{_BASE_URL}/{self._wavernn_path}"
      dl_kwargs = {} if dl_kwargs is None else dl_kwargs
      state_dict = load_state_dict_from_url(url, **dl_kwargs)
      model.load_state_dict(state_dict)
      model.eval()
      return model
  
imports: import re
  from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  from torchaudio._internal import load_state_dict_from_url
  from torchaudio.functional import mu_law_decoding
  from torchaudio.models import Tacotron2, WaveRNN
  from torchaudio.transforms import GriffinLim, InverseMelScale
  from .None import utils
  from .interface import Tacotron2TTSBundle
label_desc: Use image node_id 2 for calling the _WaveRNNMixin obj's underlying member method code with example usage: obj._get_wavernn() and returns: model