code: def validation_step(
      self, dataloader_iter, batch_idx, inference=False
  ):
      # Check if iterator is exhausted
      dataloader_iter, done = self._val_iterator_done(dataloader_iter)
      if done:
          return
      batch = next(dataloader_iter)
      (
          enc_input,
          dec_input,
          labels,
          loss_mask,
          enc_mask,
          dec_mask,
          position_ids,
          taskname_ids,
      ) = batch
  
      mode = self.training
      self.eval()
      gbs = self.cfg.get(
          "validation_global_batch_size", self.cfg.global_batch_size
      )
      self._reconfigure_and_process_inference_batch(
          enc_input.size(0), gbs
      )
      loss_mean = self.fwd_bwd_step(
          itertools.chain([batch]), batch_idx, forward_only=True
      )
  
      if self.cfg.get("report_validation_metric", False):
          metrics = self.compute_accuracy(enc_input, enc_mask, labels)
          metrics["loss"] = loss_mean
      else:
          metrics = {"loss": loss_mean}
  
      self.validation_step_outputs.append(metrics)
      self.train(mode=mode)
      return metrics
  
imports: import itertools
  from typing import Any
  import torch
  from omegaconf.dictconfig import DictConfig
  from omegaconf.omegaconf import open_dict
  from pytorch_lightning.trainer.trainer import Trainer
  from nemo.collections.common.parts.adapter_modules import LinearAdapterConfig
  from nemo.collections.nlp.models.language_modeling.megatron_t5_model import MegatronT5Model
  from nemo.collections.nlp.models.language_modeling.megatron_t5_prompt_learning_model import MegatronT5PromptLearningModel
  from nemo.collections.nlp.models.language_modeling.megatron_t5_sft_model import MegatronT5SFTModel
  from nemo.collections.nlp.modules.common import VirtualPromptStyle
  from nemo.collections.nlp.modules.common.megatron.adapters.parallel_adapters import AdapterName, InfusedAdapterConfig, LoraKQVAdapterConfig, LoraKVAdapterConfig, LoraQAdapterConfig, MLPInfusedAdapterConfig, ParallelLinearAdapterConfig
  from nemo.collections.nlp.parts.utils_funcs import get_last_rank
  from nemo.core.classes.mixins import adapter_mixins
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 6 for calling the MegatronT5BaseAdapterModel obj's underlying member method code with example usage: obj.validation_step(dataloader_iter, batch_idx, inference) and returns: metrics