code: def validation_step(self, batch, batch_idx):
      inputs = {
          "input_ids": batch[0],
          "attention_mask": batch[1],
          "labels": batch[3],
      }
  
      if self.config.model_type not in ["distilbert", "bart"]:
          inputs["token_type_ids"] = (
              batch[2]
              if self.config.model_type in ["bert", "xlnet", "albert"]
              else None
          )
  
      outputs = self(**inputs)
      tmp_eval_loss, logits = outputs[:2]
      preds = logits.detach().cpu().numpy()
      out_label_ids = inputs["labels"].detach().cpu().numpy()
  
      return {
          "val_loss": tmp_eval_loss.detach().cpu(),
          "pred": preds,
          "target": out_label_ids,
      }
  
imports: import argparse
  import glob
  import logging
  import os
  import time
  from argparse import Namespace
  import numpy
  import torch
  from lightning_base import BaseTransformer, add_generic_args, generic_train
  from torch.utils.data import DataLoader, TensorDataset
  from transformers import glue_compute_metrics
  from transformers import glue_convert_examples_to_features
  from transformers import glue_output_modes, glue_tasks_num_labels
  from transformers import glue_processors
label_desc: Use image node_id 6 for calling the GLUETransformer obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) and returns: dict