code: def configure_optimizers(self):
      return self.optimizer(
          self.parameters(),
          lr=self.hparams.learning_rate,
          weight_decay=self.hparams.weight_decay,
      )
  
imports: import warnings
  from typing import Dict, List, Optional, Union, Type
  import torch.nn
  import torch.optim
  import torchmetrics
  from torch.utils.data import DataLoader
  import nni
  from ..lightning import LightningModule, _AccuracyWithLogits, Lightning
  from .trainer import Trainer
label_desc: Use image node_id 7 for calling the _MultiModelSupervisedLearningModule obj's underlying member method code with example usage: obj.configure_optimizers() and returns: self