code: def test_crop_by_boxes_no_resizing(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],
                  ]
              ]
          ],
          device=device,
          dtype=dtype,
      )
  
      src = torch.tensor(
          [[[1.0, 1.0], [2.0, 1.0], [2.0, 2.0], [1.0, 2.0]]],
          device=device,
          dtype=dtype,
      )  # 1x4x2
  
      dst = torch.tensor(
          [[[0.0, 0.0], [1.0, 0.0], [1.0, 1.0], [0.0, 1.0]]],
          device=device,
          dtype=dtype,
      )  # 1x4x2
  
      expected = torch.tensor(
          [[[[6.0, 7.0], [10.0, 11.0]]]], device=device, dtype=dtype
      )
  
      patches = kornia.geometry.transform.crop_by_boxes(inp, src, dst)
      assert_close(patches, expected)
  
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 1 for calling the TestCropByBoxes obj's underlying member method code with example usage: obj.test_crop_by_boxes_no_resizing(device, dtype) without return types