code: def configure_optimizers(self):
      lr_factor = (
          self.batch_size_per_device * self.trainer.world_size / 256
      )
  
      # Don't use weight decay for batch norm, bias parameters, and classification
      # head to improve performance.
      params, params_no_weight_decay = get_weight_decay_parameters(
          [self.backbone, self.projection_head]
      )
      optimizer = LARS(
          [
              {"name": "barlowtwins", "params": params},
              {
                  "name": "barlowtwins_no_weight_decay",
                  "params": params_no_weight_decay,
                  "weight_decay": 0.0,
                  "lr": 0.0048 * lr_factor,
              },
              {
                  "name": "online_classifier",
                  "params": self.online_classifier.parameters(),
                  "weight_decay": 0.0,
              },
          ],
          lr=0.2 * lr_factor,
          momentum=0.9,
          weight_decay=1.5e-6,
      )
  
      scheduler = {
          "scheduler": CosineWarmupScheduler(
              optimizer=optimizer,
              warmup_epochs=int(
                  self.trainer.estimated_stepping_batches
                  / self.trainer.max_epochs
                  * 10
              ),
              max_epochs=int(self.trainer.estimated_stepping_batches),
          ),
          "interval": "step",
      }
      return [optimizer], [scheduler]
  
imports: import copy
  from typing import List, Tuple
  import torch
  from pytorch_lightning import LightningModule
  from torch import Tensor
  from torch.nn import Identity
  from torchvision.models import resnet50
  from lightly.loss import BarlowTwinsLoss
  from lightly.models.modules import BarlowTwinsProjectionHead
  from lightly.models.utils import get_weight_decay_parameters
  from lightly.transforms import BYOLTransform
  from lightly.utils.benchmarking import OnlineLinearClassifier
  from lightly.utils.lars import LARS
  from lightly.utils.scheduler import CosineWarmupScheduler
label_desc: Use image node_id 5 for calling the BarlowTwins obj's underlying member method code with example usage: obj.configure_optimizers() and returns: list,  list