code: def project(self, x: Tensor) -> Tensor:
      x = self.projection_head(x)
      return F.normalize(x, dim=1, p=2)
  
imports: import math
  from typing import List, Tuple
  import torch
  from pytorch_lightning import LightningModule
  from torch import Tensor
  from torch.nn import Identity, ModuleList
  from torch.nn import functional
  from torchvision.models import resnet50
  from lightly.loss.swav_loss import SwaVLoss
  from lightly.models.modules import SwaVProjectionHead, SwaVPrototypes
  from lightly.models.modules.memory_bank import MemoryBankModule
  from lightly.models.utils import get_weight_decay_parameters
  from lightly.transforms import SwaVTransform
  from lightly.utils.benchmarking import OnlineLinearClassifier
  from lightly.utils.lars import LARS
  from lightly.utils.scheduler import CosineWarmupScheduler
label_desc: Use image node_id 3 for calling the SwAV obj's underlying member method code with example usage: obj.project(x) and returns: F