code: def loss(self, batch, prediction):
      # An arbitrary loss to have a loss that updates the model weights during `Trainer.fit` calls
      return torch.nn.functional.mse_loss(
          prediction, torch.ones_like(prediction)
      )
  
imports: from typing import Optional
  import torch
  from pytorch_lightning import LightningDataModule, LightningModule
  from torch.utils.data import DataLoader, Dataset, Subset
label_desc: Use image node_id 3 for calling the BoringModel obj's underlying member method code with example usage: obj.loss(batch, prediction) and returns: torch