code: def configure_optimizers(self):
      optimizer = torch.optim.SGD(
          self.parameters(),
          lr=self.hparams.lr,
          momentum=0.9,
          weight_decay=5e-4,
      )
      steps_per_epoch = 45000 // BATCH_SIZE
      scheduler_dict = {
          "scheduler": OneCycleLR(
              optimizer,
              0.1,
              epochs=self.trainer.max_epochs,
              steps_per_epoch=steps_per_epoch,
          ),
          "interval": "step",
      }
      return {"optimizer": optimizer, "lr_scheduler": scheduler_dict}
  
imports: import os
  from time import time
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from pytorch_lightning import LightningModule, seed_everything
  from bigdl.nano.pytorch import Trainer, InferenceOptimizer
  from pytorch_lightning.callbacks import LearningRateMonitor
  from pytorch_lightning.loggers import TensorBoardLogger
  from torch.optim.lr_scheduler import OneCycleLR
  from torchmetrics.functional import accuracy
  from pl_bolts.datamodules import CIFAR10DataModule
  from pl_bolts.transforms.dataset_normalizations import cifar10_normalization
label_desc: Use image node_id 7 for calling the LitResnet obj's underlying member method code with example usage: obj.configure_optimizers() and returns: dict