class_docstr: VITS module (generator + discriminator).
  
  This is a module of VITS described in `Conditional Variational Autoencoder
  with Adversarial Learning for End-to-End Text-to-Speech`_.
  
  .. _`Conditional Variational Autoencoder with Adversarial Learning for End-to-End
      Text-to-Speech`: https://arxiv.org/abs/2006.04558
docstr: Return whether or not singing is required.
docstr_tok: ["Return","whether","or","not","singing","is","required","."]
code: def require_raw_singing(self):
      """Return whether or not singing is required."""
      return True
  
imports: from contextlib import contextmanager
  from distutils.version import LooseVersion
  from typing import Any, Dict, Optional
  import torch
  from torch.nn import functional
  from typeguard import check_argument_types
  from espnet2.gan_svs.abs_gan_svs import AbsGANSVS
  from espnet2.gan_svs.avocodo.avocodo import SBD, AvocodoDiscriminator, AvocodoDiscriminatorPlus, CoMBD
  from espnet2.gan_svs.visinger2.visinger2_vocoder import VISinger2Discriminator
  from espnet2.gan_svs.vits.generator import VISingerGenerator
  from espnet2.gan_tts.hifigan import HiFiGANMultiPeriodDiscriminator, HiFiGANMultiScaleDiscriminator, HiFiGANMultiScaleMultiPeriodDiscriminator, HiFiGANPeriodDiscriminator, HiFiGANScaleDiscriminator
  from espnet2.gan_tts.hifigan.loss import DiscriminatorAdversarialLoss, FeatureMatchLoss, GeneratorAdversarialLoss, MelSpectrogramLoss
  from espnet2.gan_tts.utils import get_segments
  from espnet2.gan_tts.vits.loss import KLDivergenceLoss, KLDivergenceLossWithoutFlow
  from espnet2.torch_utils.device_funcs import force_gatherable
label_desc: Use image node_id 2 for calling the VITS obj's underlying member method code with example usage: obj.require_raw_singing() and returns: True