code: def test_translation(self, shape, device, dtype):
      # create input data
      offset = 2.0  # in pixel
      height, width = shape
      patch_src = torch.rand(
          1, 1, height, width, device=device, dtype=dtype
      )
      dst_homo_src = utils.create_eye_batch(
          batch_size=1, eye_size=3, device=device, dtype=dtype
      )
      dst_homo_src[..., 0, 2] = offset / (
          width - 1
      )  # apply offset in x
  
      # instantiate warper and from source to destination
      warper = kornia.geometry.transform.HomographyWarper(
          height, width, align_corners=True
      )
      patch_dst = warper(patch_src, dst_homo_src)
      assert_close(
          patch_src[..., 1:], patch_dst[..., :-1], atol=1e-4, rtol=1e-4
      )
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
  from kornia.utils.helpers import _torch_inverse_cast
label_desc: Use image node_id 9 for calling the TestHomographyWarper obj's underlying member method code with example usage: obj.test_translation(shape, device, dtype) without return types