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 os
  import matplotlib.pyplot
  import numpy
  import pytorch_lightning
  import torch
  import torch.nn
  import torchvision
  from PIL import Image
  from sklearn.neighbors import NearestNeighbors
  from sklearn.preprocessing import normalize
  from lightly.data import LightlyDataset
  from lightly.transforms import SimCLRTransform, utils
  from lightly.loss import NTXentLoss
  from lightly.models.modules.heads import SimCLRProjectionHead
label_desc: Use image node_id 4 for calling the SimCLRModel obj's underlying member method code with example usage: obj.configure_optimizers() and returns: list,  list