code: def test_correct_results(self):
      for p in TEST_NDARRAYS_ALL:
          flip = RandAxisFlipd(keys="img", prob=1.0)
          flip.set_random_state(seed=1234)
          im = p(self.imt[0])
          call_param = {"data": {"img": im}}
          result = flip(**call_param)
  
          # test lazy
          test_resampler_lazy(
              flip,
              result,
              call_param=call_param,
              output_key="img",
              seed=1234,
          )
          flip.lazy = False
  
          test_local_inversion(flip, result, {"img": im}, "img")
          expected = [
              np.flip(channel, flip.flipper._axis)
              for channel in self.imt[0]
          ]
          assert_allclose(
              result["img"], p(np.stack(expected)), type_test="tensor"
          )
  
          set_track_meta(False)
          result = flip({"img": im})["img"]
          self.assertNotIsInstance(result, MetaTensor)
          self.assertIsInstance(result, torch.Tensor)
          set_track_meta(True)
  
file_path: MONAI/tests/test_rand_axis_flipd.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from monai.data import MetaTensor, set_track_meta
  from monai.transforms import RandAxisFlipd
  from tests.lazy_transforms_utils import test_resampler_lazy
  from tests.utils import TEST_NDARRAYS_ALL, NumpyImageTestCase3D, assert_allclose, test_local_inversion
label_desc: Use image node_id 1 for calling the TestRandAxisFlip obj's underlying member method code with example usage: obj.test_correct_results() without return types