code: def validation_step(self, val_batch, batch_idx):
      x, y = val_batch
      logits = self.forward(x)
      loss = F.nll_loss(logits, y)
      acc = self.accuracy(logits, y)
      return {"val_loss": loss, "val_accuracy": acc}
  
imports: import math
  import os
  import torch
  from filelock import FileLock
  import pytorch_lightning
  from torch.nn import functional
  from torch.utils.data import DataLoader, random_split
  from torchmetrics import Accuracy
  from torchvision import transforms
  from torchvision.datasets import MNIST
  from ray.tune.integration.pytorch_lightning import TuneReportCheckpointCallback
  from ray import train, tune
label_desc: Use image node_id 5 for calling the LightningMNISTClassifier obj's underlying member method code with example usage: obj.validation_step(val_batch, batch_idx) and returns: dict