code: def test_lambdad_slicing(self):
      for p in TEST_NDARRAYS:
          img = p(self.imt)
          data = {"img": img}
  
          def slice_func(x):
              return x[:, :, :6, ::2]
  
          lambd = Lambdad(keys=data.keys(), func=slice_func)
          expected = {}
          expected = slice_func(data["img"])
          out = lambd(data)
          out_img = out["img"]
          assert_allclose(expected, out_img, type_test=False)
          self.assertIsInstance(out_img, MetaTensor)
          self.assertEqual(len(out_img.applied_operations), 1)
          inv_img = lambd.inverse(out)["img"]
          self.assertIsInstance(inv_img, MetaTensor)
          self.assertEqual(len(inv_img.applied_operations), 0)
  
file_path: MONAI/tests/test_lambdad.py
imports: from __future__ import annotations
  import unittest
  from numpy import ndarray
  from torch import Tensor
  from monai.data.meta_tensor import MetaTensor
  from monai.transforms.utility.dictionary import Lambdad
  from monai.utils.type_conversion import convert_to_numpy, convert_to_tensor
  from tests.utils import TEST_NDARRAYS, NumpyImageTestCase2D, assert_allclose
label_desc: Use image node_id 2 for calling the TestLambdad obj's underlying member method code with example usage: obj.test_lambdad_slicing() and returns: x