code: def configure_optimizers(self):
      optim = torch.optim.SGD(
          self.parameters(),
          lr=6e-2,
          momentum=0.9,
          weight_decay=5e-4,
      )
      scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(
          optim, max_epochs
      )
      return [optim], [scheduler]
  
imports: import copy
  import pytorch_lightning
  import torch
  import torch.nn
  import torchvision
  from lightly.data import LightlyDataset
  from lightly.loss import NTXentLoss
  from lightly.models import ResNetGenerator
  from lightly.models.modules.heads import MoCoProjectionHead
  from lightly.models.utils import batch_shuffle, batch_unshuffle, deactivate_requires_grad, update_momentum
  from lightly.transforms import MoCoV2Transform, utils
label_desc: Use image node_id 5 for calling the MocoModel obj's underlying member method code with example usage: obj.configure_optimizers() and returns: list,  list