code: def build_train_valid_test_datasets(self):
      logging.info("Building datasets for Imagen...")
      if self.trainer.limit_val_batches > 1.0 and isinstance(
          self.trainer.limit_val_batches, float
      ):
          raise ValueError(
              "limit_val_batches must be an integer or float less than or equal to 1.0."
          )
      self._train_ds, self._validation_ds = build_train_valid_datasets(
          model_cfg=self.cfg,
          consumed_samples=self.compute_consumed_samples(0),
      )
      # We do not have test dataset
      self._test_ds = None
  
      if self._train_ds is not None:
          logging.info(
              f"Length of train dataset: {len(self._train_ds)}"
          )
      if self._validation_ds is not None:
          logging.info(
              f"Length of val dataset: {len(self._validation_ds)}"
          )
      if self._test_ds is not None:
          logging.info(f"Length of test dataset: {len(self._test_ds)}")
      logging.info(f"Finished building datasets for LatentDiffusion.")
      return self._train_ds, self._validation_ds, self._test_ds
  
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 6 for calling the MegatronImagen obj's underlying member method code with example usage: obj.build_train_valid_test_datasets() and returns: self,  self,  self