code: def test_raise(self, device, dtype):
      boxes = torch.tensor(
          [[100, 50, 150, 100.0]], device=device, dtype=dtype
      )
      labels = torch.tensor([1], device=device, dtype=torch.long)
      scores = torch.tensor([0.7], device=device, dtype=dtype)
  
      gt_boxes = torch.tensor(
          [[100, 50, 150, 100.0]], device=device, dtype=dtype
      )
      gt_labels = torch.tensor([1], device=device, dtype=torch.long)
  
      with pytest.raises(AssertionError):
          _ = kornia.metrics.mean_average_precision(
              boxes[0], [labels], [scores], [gt_boxes], [gt_labels], 2
          )
  
imports: import pytest
  import torch
  import kornia
  from kornia.testing import BaseTester, assert_close, tensor_to_gradcheck_var
label_desc: Use image node_id 2 for calling the TestMeanAveragePrecision obj's underlying member method code with example usage: obj.test_raise(device, dtype) without return types