code: def _loader(self, cfg):
      try:
          _ = cfg["dataset"]["manifest_filepath"]
      except omegaconf.errors.MissingMandatoryValue:
          logging.warning(
              "manifest_filepath was skipped. No dataset for this model."
          )
          return None
  
      dataset = instantiate(
          cfg.dataset,
          text_normalizer=self.normalizer,
          text_normalizer_call_kwargs=self.text_normalizer_call_kwargs,
          text_tokenizer=self.tokenizer,
      )
      return torch.utils.data.DataLoader(  # noqa
          dataset=dataset,
          collate_fn=dataset.collate_fn,
          **cfg.dataloader_params,
      )
  
imports: import contextlib
  import omegaconf
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from pytorch_lightning.loggers import WandbLogger
  from torch.cuda.amp import autocast
  from torch.nn import functional
  from nemo.collections.tts.data.dataset import DistributedBucketSampler
  from nemo.collections.tts.losses.vits_losses import DiscriminatorLoss, FeatureMatchingLoss, GeneratorLoss, KlLoss
  from nemo.collections.tts.models.base import TextToWaveform
  from nemo.collections.tts.modules.vits_modules import MultiPeriodDiscriminator
  from nemo.collections.tts.parts.utils.helpers import clip_grad_value_, g2p_backward_compatible_support, plot_spectrogram_to_numpy, slice_segments
  from nemo.collections.tts.torch.tts_data_types import SpeakerID
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.neural_types.elements import AudioSignal, FloatType, Index, IntType, TokenIndex
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.core.optim.lr_scheduler import CosineAnnealing
  from nemo.utils import logging, model_utils
  from nemo.utils.decorators.experimental import experimental
label_desc: Use image node_id 9 for calling the VitsModel obj's underlying member method code with example usage: obj._loader(cfg) and returns: torch, None