code: def test_backward(self) -> None:
      torch.manual_seed(0)
      head = MSNProjectionHead(5, 16, 6)
      criterion = MSNLoss()
      optimizer = SGD(head.parameters(), lr=0.1)
      anchors = torch.rand((8 * 4, 5))
      targets = torch.rand((8, 5))
      prototypes = nn.Linear(6, 4).weight  # 4 prototypes with dim 6
      optimizer.zero_grad()
      anchors = head(anchors)
      with torch.no_grad():
          targets = head(targets)
      loss = criterion(anchors, targets, prototypes)
      loss.backward()
      weights_before = head.layers[0].weight.data.clone()
      optimizer.step()
      weights_after = head.layers[0].weight.data
      # backward pass should update weights
      self.assertTrue(torch.any(weights_before != weights_after))
  
imports: import unittest
  from unittest import TestCase
  import pytest
  import torch
  import torch.nn.functional
  from pytest_mock import MockerFixture
  from torch import distributed
  from torch import nn
  from torch.optim import SGD
  from lightly.loss import msn_loss
  from lightly.loss.msn_loss import MSNLoss
  from lightly.models.modules.heads import MSNProjectionHead
label_desc: Use image node_id 10 for calling the TestMSNLossUnitTest obj's underlying member method code with example usage: obj.test_backward() without return types