code: def test_forward_pass_cuda(self):
      loss = VICRegLoss()
      for bsz in range(2, 4):
          x0 = torch.randn((bsz, 32)).cuda()
          x1 = torch.randn((bsz, 32)).cuda()
  
          # symmetry
          l1 = loss(x0, x1)
          l2 = loss(x1, x0)
          self.assertAlmostEqual((l1 - l2).pow(2).item(), 0.0)
  
imports: import unittest
  import pytest
  import torch
  import torch.nn.functional
  from pytest_mock import MockerFixture
  from torch import Tensor
  from torch import distributed
  from lightly.loss import VICRegLoss
label_desc: Use image node_id 2 for calling the TestVICRegLossUnitTest obj's underlying member method code with example usage: obj.test_forward_pass_cuda() without return types