code: def test_smoke(self, device, dtype):
      batch_size, channels, height, width = 1, 2, 3, 4
      img_b = torch.rand(
          batch_size,
          channels,
          height,
          width,
          device=device,
          dtype=dtype,
      )
      H_ab = kornia.eye_like(3, img_b)
      img_a = kornia.geometry.warp_perspective(
          img_b, H_ab, (height, width)
      )
      assert_close(img_b, img_a)
  
imports: import sys
  import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
  from kornia.utils._compat import torch_version, torch_version_lt
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 1 for calling the TestWarpPerspective obj's underlying member method code with example usage: obj.test_smoke(device, dtype) without return types