code: def __init__(self):
      super().__init__()
      resnet = torchvision.models.resnet18()
      self.backbone = nn.Sequential(*list(resnet.children())[:-1])
      self.projection_head = NNCLRProjectionHead(512, 512, 128)
      self.prediction_head = NNCLRPredictionHead(128, 512, 128)
      self.memory_bank = NNMemoryBankModule(size=(4096, 128))
  
      self.criterion = NTXentLoss()
  
file_path: lightly/examples/pytorch_lightning/nnclr.py
imports: import pytorch_lightning
  import torch
  import torchvision
  from torch import nn
  from lightly.loss import NTXentLoss
  from lightly.models.modules import NNCLRPredictionHead, NNCLRProjectionHead, NNMemoryBankModule
  from lightly.transforms.simclr_transform import SimCLRTransform
label_desc: Use image node_id 1 to create a new NNCLR object from inherited base classes: pl with example: obj = NNCLR()