code: def test_set_data(self):
      from monai.transforms import Compose, Lambda, RandLambda
  
      images = [
          np.arange(2, 18, dtype=float).reshape(1, 4, 4),
          np.arange(16, dtype=float).reshape(1, 4, 4),
      ]
  
      transform = Compose(
          [
              Lambda(func=lambda x: np.array(x * 10)),
              RandLambda(func=lambda x: x + 1),
          ],
          map_items=False,
      )
      patch_iter = PatchIter(patch_size=(2, 2), start_pos=(0, 0))
      dataset = GridPatchDataset(
          data=images,
          patch_iter=patch_iter,
          transform=transform,
          cache=True,
          cache_rate=1.0,
          copy_cache=not sys.platform == "linux",
      )
  
      num_workers = 2 if sys.platform == "linux" else 0
      for item in DataLoader(
          dataset, batch_size=2, shuffle=False, num_workers=num_workers
      ):
          np.testing.assert_equal(tuple(item[0].shape), (2, 1, 2, 2))
      np.testing.assert_allclose(
          item[0],
          np.array(
              [[[[81, 91], [121, 131]]], [[[101, 111], [141, 151]]]]
          ),
          rtol=1e-4,
      )
      np.testing.assert_allclose(
          item[1],
          np.array(
              [[[0, 1], [2, 4], [0, 2]], [[0, 1], [2, 4], [2, 4]]]
          ),
          rtol=1e-5,
      )
      # simulate another epoch, the cache content should not be modified
      for item in DataLoader(
          dataset, batch_size=2, shuffle=False, num_workers=num_workers
      ):
          np.testing.assert_equal(tuple(item[0].shape), (2, 1, 2, 2))
      np.testing.assert_allclose(
          item[0],
          np.array(
              [[[[81, 91], [121, 131]]], [[[101, 111], [141, 151]]]]
          ),
          rtol=1e-4,
      )
      np.testing.assert_allclose(
          item[1],
          np.array(
              [[[0, 1], [2, 4], [0, 2]], [[0, 1], [2, 4], [2, 4]]]
          ),
          rtol=1e-5,
      )
  
      # update the datalist and fill the cache content
      data_list2 = [np.arange(1, 17, dtype=float).reshape(1, 4, 4)]
      dataset.set_data(data=data_list2)
      # rerun with updated cache content
      for item in DataLoader(
          dataset, batch_size=2, shuffle=False, num_workers=num_workers
      ):
          np.testing.assert_equal(tuple(item[0].shape), (2, 1, 2, 2))
      np.testing.assert_allclose(
          item[0],
          np.array(
              [[[[91, 101], [131, 141]]], [[[111, 121], [151, 161]]]]
          ),
          rtol=1e-4,
      )
      np.testing.assert_allclose(
          item[1],
          np.array(
              [[[0, 1], [2, 4], [0, 2]], [[0, 1], [2, 4], [2, 4]]]
          ),
          rtol=1e-5,
      )
  
imports: from __future__ import annotations
  import sys
  import unittest
  import numpy
  from parameterized import parameterized
  from monai.data import DataLoader, GridPatchDataset, PatchIter, PatchIterd, iter_patch
  from monai.transforms import RandShiftIntensity, RandShiftIntensityd
  from monai.utils import set_determinism
  from tests.utils import TEST_NDARRAYS, assert_allclose, get_arange_img
label_desc: Use image node_id 9 for calling the TestGridPatchDataset obj's underlying member method code with example usage: obj.test_set_data() without return types