code: def test_grid_patch(self, in_type, input_parameters, image, expected):
      input_image = in_type(image)
      splitter = GridPatch(**input_parameters)
      output = splitter(input_image)
      self.assertEqual(len(output), len(expected))
      for output_patch, expected_patch in zip(output, expected):
          assert_allclose(
              output_patch,
              in_type(expected_patch),
              type_test=False,
              device_test=bool(
                  isinstance(in_type(expected_patch), torch.Tensor)
              ),
          )
  
file_path: MONAI/tests/test_grid_patch.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data import MetaTensor, set_track_meta
  from monai.transforms.spatial.array import GridPatch
  from tests.utils import TEST_NDARRAYS, SkipIfBeforePyTorchVersion, assert_allclose
label_desc: Use image node_id 1 for calling the TestGridPatch obj's underlying member method code with example usage: obj.test_grid_patch(in_type, input_parameters, image, expected) without return types