code: def test_swav_frozen_prototypes(self, device: str = "cpu", seed=0):
      criterion = torch.nn.L1Loss()
      linear_layer = torch.nn.Linear(8, 8, bias=False)
      prototypes = SwaVPrototypes(
          input_dim=8, n_prototypes=8, n_steps_frozen_prototypes=2
      )
      optimizer = torch.optim.SGD(prototypes.parameters(), lr=0.01)
      torch.manual_seed(seed)
      in_features = torch.rand(4, 8, device="cpu")
      target_features = torch.ones(4, 8, device="cpu")
      for step in range(4):
          out_features = linear_layer(in_features)
          out_features = prototypes.forward(out_features, step)
          loss = criterion(out_features, target_features)
          loss.backward()
          optimizer.step()
          optimizer.zero_grad()
          if step == 0:
              loss0 = loss
          if step <= 2:
              self.assertEqual(loss, loss0)
          if step > 2:
              self.assertNotEqual(loss, loss0)
  
file_path: lightly/tests/models/test_ProjectionHeads.py
imports: import unittest
  import torch
  import lightly
  from lightly.models.modules.heads import BarlowTwinsProjectionHead, BYOLPredictionHead, BYOLProjectionHead, DINOProjectionHead, MoCoProjectionHead, MSNProjectionHead, NNCLRPredictionHead, NNCLRProjectionHead, SimCLRProjectionHead, SimSiamPredictionHead, SimSiamProjectionHead, SwaVProjectionHead, SwaVPrototypes, TiCoProjectionHead, VicRegLLocalProjectionHead
label_desc: Use image node_id 5 for calling the TestProjectionHeads obj's underlying member method code with example usage: obj.test_swav_frozen_prototypes(device, seed) without return types