code: def test_forward_pass_cuda(self):
      loss = NTXentLoss(memory_bank_size=0)
      for bsz in range(1, 20):
          batch_1 = torch.randn((bsz, 32)).cuda()
          batch_2 = torch.randn((bsz, 32)).cuda()
  
          # symmetry
          l1 = loss(batch_1, batch_2)
          l2 = loss(batch_2, batch_1)
          self.assertAlmostEqual((l1 - l2).pow(2).item(), 0.0)
  
imports: import unittest
  import numpy
  import pytest
  import torch
  from pytest_mock import MockerFixture
  from torch import distributed
  from lightly.loss import NTXentLoss
label_desc: Use image node_id 9 for calling the TestNTXentLossUnitTest obj's underlying member method code with example usage: obj.test_forward_pass_cuda() without return types