code: def build_vocoder_from_file(
      cls,
      vocoder_config_file: Union[Path, str] = None,
      vocoder_file: Union[Path, str] = None,
      model: Optional[ESPnetSVSModel] = None,
      device: str = "cpu",
  ):
      logging.info(f"vocoder_config_file: {vocoder_config_file}")
      logging.info(f"vocoder_file: {vocoder_file}")
  
      # Build vocoder
      if vocoder_file is None:
          # If vocoder file is not provided, use griffin-lim as a vocoder
          vocoder_conf = {}
          if vocoder_config_file is not None:
              vocoder_config_file = Path(vocoder_config_file)
              with vocoder_config_file.open("r", encoding="utf-8") as f:
                  vocoder_conf = yaml.safe_load(f)
          if model.feats_extract is not None:
              vocoder_conf.update(model.feats_extract.get_parameters())
          if (
              "n_fft" in vocoder_conf
              and "n_shift" in vocoder_conf
              and "fs" in vocoder_conf
          ):
              return Spectrogram2Waveform(**vocoder_conf)
          else:
              logging.warning(
                  "Vocoder is not available. Skipped its building."
              )
              return None
  
      elif str(vocoder_file).endswith(".pkl"):
          # If the extension is ".pkl", the model is trained with parallel_wavegan
          vocoder = ParallelWaveGANPretrainedVocoder(
              vocoder_file, vocoder_config_file
          )
          return vocoder.to(device)
  
      else:
          raise ValueError(f"{vocoder_file} is not supported format.")
  
imports: import argparse
  import logging
  from pathlib import Path
  from typing import Callable, Collection, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  import yaml
  from typeguard import check_argument_types, check_return_type
  from espnet2.gan_svs.joint import JointScore2Wav
  from espnet2.gan_svs.vits import VITS
  from espnet2.layers.abs_normalize import AbsNormalize
  from espnet2.layers.global_mvn import GlobalMVN
  from espnet2.svs.abs_svs import AbsSVS
  from espnet2.svs.espnet_model import ESPnetSVSModel
  from espnet2.svs.feats_extract.score_feats_extract import FrameScoreFeats, SyllableScoreFeats
  from espnet2.svs.naive_rnn.naive_rnn import NaiveRNN
  from espnet2.svs.naive_rnn.naive_rnn_dp import NaiveRNNDP
  from espnet2.svs.singing_tacotron.singing_tacotron import singing_tacotron
  from espnet2.svs.xiaoice.XiaoiceSing import XiaoiceSing
  from espnet2.tasks.abs_task import AbsTask
  from espnet2.train.class_choices import ClassChoices
  from espnet2.train.collate_fn import CommonCollateFn
  from espnet2.train.preprocessor import SVSPreprocessor
  from espnet2.train.trainer import Trainer
  from espnet2.tts.feats_extract.abs_feats_extract import AbsFeatsExtract
  from espnet2.tts.feats_extract.dio import Dio
  from espnet2.tts.feats_extract.energy import Energy
  from espnet2.tts.feats_extract.linear_spectrogram import LinearSpectrogram
  from espnet2.tts.feats_extract.log_mel_fbank import LogMelFbank
  from espnet2.tts.feats_extract.log_spectrogram import LogSpectrogram
  from espnet2.tts.feats_extract.ying import Ying
  from espnet2.tts.utils import ParallelWaveGANPretrainedVocoder
  from espnet2.utils.get_default_kwargs import get_default_kwargs
  from espnet2.utils.griffin_lim import Spectrogram2Waveform
  from espnet2.utils.nested_dict_action import NestedDictAction
  from espnet2.utils.types import int_or_none, str2bool, str_or_none
label_desc: Use image node_id 7 for calling the SVSTask obj's underlying member method code with example usage: obj.build_vocoder_from_file(cls, vocoder_config_file, vocoder_file, model, device) and returns: Spectrogram2Waveform, None, vocoder