code: def setup_validation_data(self, cfg):
      if (
          hasattr(self, "_validation_ds")
          and self._validation_ds is not None
      ):
          consumed_samples = 0
          logging.info(
              f"Setting up validation dataloader with len(len(self._validation_ds)): {len(self._validation_ds)} and consumed samples: {consumed_samples}"
          )
          self._validation_dl = torch.utils.data.DataLoader(
              self._validation_ds,
              batch_size=self._micro_batch_size,
              num_workers=cfg.num_workers,
              pin_memory=True,
              drop_last=False,
              persistent_workers=True,
          )
  
imports: import itertools
  from datetime import datetime
  from functools import partial
  from typing import Any
  import torch
  from omegaconf import DictConfig, open_dict
  from pytorch_lightning import Trainer
  from nemo.collections.multimodal.data.imagen.imagen_dataset import build_train_valid_datasets
  from nemo.collections.multimodal.models.text_to_image.imagen.precond import ContinousDDPMPrecond, EDMPrecond
  from nemo.collections.multimodal.modules.imagen.diffusionmodules.nets import EfficientUNetModel, UNetModel
  from nemo.collections.multimodal.modules.imagen.encoder.t5encoder import T5Encoder
  from nemo.collections.multimodal.modules.imagen.sampler.sampler import DDPMSampler, EDMSampler
  from nemo.collections.multimodal.parts.imagen.utils import random_dropout
  from nemo.collections.nlp.models.language_modeling.megatron_base_model import MegatronBaseModel
  from nemo.collections.nlp.modules.common.megatron.module import Float16Module
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.common import Serialization
  from nemo.utils import logging
label_desc: Use image node_id 8 for calling the MegatronImagen obj's underlying member method code with example usage: obj.setup_validation_data(cfg) without return types