code: def test_center_crop_h4_w2_batch(self, device, dtype):
      inp = torch.tensor(
          [
              [
                  [
                      [1.0, 2.0, 3.0, 4.0],
                      [5.0, 6.0, 7.0, 8.0],
                      [9.0, 10.0, 11.0, 12.0],
                      [13.0, 14.0, 15.0, 16.0],
                  ]
              ],
              [
                  [
                      [1.0, 5.0, 9.0, 13.0],
                      [2.0, 6.0, 10.0, 14.0],
                      [3.0, 7.0, 11.0, 15.0],
                      [4.0, 8.0, 12.0, 16.0],
                  ]
              ],
          ],
          device=device,
          dtype=dtype,
      )
  
      expected = torch.tensor(
          [
              [[[2.0, 3.0], [6.0, 7.0], [10.0, 11.0], [14.0, 15.0]]],
              [[[5.0, 9.0], [6.0, 10.0], [7.0, 11.0], [8.0, 12.0]]],
          ],
          device=device,
          dtype=dtype,
      )
  
      out_crop = kornia.geometry.transform.center_crop(inp, (4, 2))
      assert_close(out_crop, expected, rtol=1e-4, atol=1e-4)
  
imports: import torch
  from torch.autograd import gradcheck
  import kornia
  import kornia.testing
  from kornia.testing import assert_close
label_desc: Use image node_id 3 for calling the TestCenterCrop obj's underlying member method code with example usage: obj.test_center_crop_h4_w2_batch(device, dtype) without return types