code: def configure_optimizers(self):
      return torch.optim.Adam(self.parameters(), lr=self.lr)
  
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 3 for calling the LightningMNISTClassifier obj's underlying member method code with example usage: obj.configure_optimizers() and returns: torch