code: def training_step(self, train_batch, batch_idx):
      x, y = train_batch
      logits = self.forward(x)
      loss = F.nll_loss(logits, y)
      acc = self.accuracy(logits, y)
      self.log("ptl/train_loss", loss)
      self.log("ptl/train_accuracy", acc)
      return loss
  
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 4 for calling the LightningMNISTClassifier obj's underlying member method code with example usage: obj.training_step(train_batch, batch_idx) and returns: loss