code: def forward_momentum(self, x: Tensor) -> Tensor:
      features = self.backbone_momentum(x).flatten(start_dim=1)
      projections = self.projection_head_momentum(features)
      projections = projections.detach()
      return projections
  
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 3 for calling the TiCo obj's underlying member method code with example usage: obj.forward_momentum(x) and returns: projections