code: def validation_step(self, batch, batch_idx):
      x, y = batch
      output = self.forward(x)
      loss = self.criterion(output, y)
      pred = torch.argmax(output, dim=1)
      acc = torch.sum(y == pred).item() / (len(y) * 1.0)
      metrics = {"test_acc": acc, "test_loss": loss}
      self.log_dict(metrics)
  
file_path: BigDL/python/nano/tutorial/training/pytorch-lightning/lightning_cv_data_pipeline.py
imports: import torch
  import torchvision
  from typing import Any
  from torch.utils.data.dataloader import DataLoader
  from torchvision.models import resnet18
  from bigdl.nano.pytorch import Trainer
  import pytorch_lightning
  from os.path import split, join, realpath
  import cv2
  from logging import warning
  import os
  from bigdl.nano.pytorch.vision.datasets import OxfordIIITPet
label_desc: Use image node_id 4 for calling the MyLightningModule obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) without return types