code: def test_correct_results(self, _, spatial_axis):
      for p in TEST_NDARRAYS_ALL:
          im = p(self.imt[0])
          init_param = {"prob": 1.0, "spatial_axis": spatial_axis}
          flip = RandFlip(**init_param)
          set_track_meta(False)
          result = flip(im)
          self.assertNotIsInstance(result, MetaTensor)
          self.assertIsInstance(result, torch.Tensor)
          set_track_meta(True)
          expected = [
              np.flip(channel, spatial_axis) for channel in self.imt[0]
          ]
          expected = np.stack(expected)
          call_param = {"img": im}
          result = flip(**call_param)
          assert_allclose(result, p(expected), type_test="tensor")
          test_local_inversion(flip, result, im)
  
          # test lazy
          test_resampler_lazy(flip, result, init_param, call_param)
  
file_path: MONAI/tests/test_rand_flip.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 import RandFlip
  from tests.lazy_transforms_utils import test_resampler_lazy
  from tests.utils import TEST_NDARRAYS_ALL, NumpyImageTestCase2D, assert_allclose, test_local_inversion
label_desc: Use image node_id 2 for calling the TestRandFlip obj's underlying member method code with example usage: obj.test_correct_results(_, spatial_axis) without return types