code: def training_step(self, batch, batch_idx):
      x, y = batch
      logits = self(x)
      loss = F.nll_loss(logits, y)
      self.log(
          "train_loss", x, on_step=True, on_epoch=True, logger=False
      )
      return loss
  
imports: import json
  from glob import glob
  import os
  import torch
  from torch.nn import functional
  from torch import nn
  from pytorch_lightning.core.lightning import LightningModule
  from pytorch_lightning import Trainer
  from torch.optim import Adam
  from torch.utils.data import DataLoader, random_split, Subset
  from torch.utils.data.dataset import Dataset
  from torchvision.datasets import MNIST
  from torchvision import transforms
  import pytest
  import urllib
  from keepsake.pl_callback import KeepsakeCallback
label_desc: Use image node_id 6 for calling the ModelNoValidation obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss