code: def __init__(
      self, batch_size_per_device: int, num_classes: int
  ) -> None:
      super().__init__()
      self.save_hyperparameters()
      self.batch_size_per_device = batch_size_per_device
  
      resnet = resnet50()
      resnet.fc = Identity()  # Ignore classification head
      self.backbone = resnet
      self.projection_head = TiCoProjectionHead()
  
      self.backbone_momentum = copy.deepcopy(self.backbone)
      self.projection_head_momentum = copy.deepcopy(
          self.projection_head
      )
  
      self.criterion = TiCoLoss(
          beta=0.9, rho=8.0, gather_distributed=True
      )
  
      self.online_classifier = OnlineLinearClassifier(
          num_classes=num_classes
      )
  
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.tico_loss import TiCoLoss
  from lightly.models.modules.heads import TiCoProjectionHead
  from lightly.models.utils import deactivate_requires_grad, get_weight_decay_parameters, update_momentum
  from lightly.transforms import BYOLTransform
  from lightly.utils.benchmarking import OnlineLinearClassifier
  from lightly.utils.lars import LARS
  from lightly.utils.scheduler import CosineWarmupScheduler, cosine_schedule
label_desc: Use image node_id 1 to create a new TiCo object from inherited base classes: LightningModule with example: obj = TiCo(batch_size_per_device, num_classes)