code: def test_two_classes(self, device, dtype):
      num_classes = 2
      actual = torch.tensor(
          [[1, 1, 1, 1, 0, 0, 0, 0]], device=device, dtype=torch.long
      )
      predicted = torch.tensor(
          [[1, 1, 1, 1, 0, 0, 0, 1]], device=device, dtype=torch.long
      )
  
      conf_mat = kornia.metrics.confusion_matrix(
          predicted, actual, num_classes
      )
      conf_mat_real = torch.tensor(
          [[[3, 1], [0, 4]]], device=device, dtype=torch.float32
      )
      assert_close(conf_mat, conf_mat_real)
  
imports: import pytest
  import torch
  import kornia
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 1 for calling the TestConfusionMatrix obj's underlying member method code with example usage: obj.test_two_classes(device, dtype) without return types