code: def training_step(self, batch, batch_idx):
      x, y = batch
      logits = self(x)
      loss = F.nll_loss(logits, y)
      self.log("train_loss", loss)
      return loss
  
imports: import os
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from pytorch_lightning import LightningModule, Trainer, seed_everything
  from pytorch_lightning.callbacks import LearningRateMonitor
  from pytorch_lightning.loggers import TensorBoardLogger
  from torch.optim.lr_scheduler import OneCycleLR
  from torchmetrics.functional import accuracy
  from pl_bolts.datamodules import CIFAR10DataModule
  from pl_bolts.transforms.dataset_normalizations import cifar10_normalization
label_desc: Use image node_id 3 for calling the LitResnet obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss