code: def configure_optimizers(self):
      return self.optimizer(
          self.parameters(),
          lr=self.hparams.learning_rate,
          weight_decay=self.hparams.weight_decay,
      )
  
imports: import logging
  import os
  import warnings
  from pathlib import Path
  from typing import Any, Dict, Union, Optional, List, Type
  import pytorch_lightning
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchmetrics
  import torchmetrics.classification
  import torch.utils.data
  import nni
  from nni.common.serializer import is_traceable
  from nni.nas.evaluator import MutableEvaluator
label_desc: Use image node_id 6 for calling the SupervisedLearningModule obj's underlying member method code with example usage: obj.configure_optimizers() and returns: self