def METHOD_NAME(self, case_id):
    set_determinism(2022)
    config = ConfigParser()
    config.read_config(TEST_CASES)
    config["input_keys"] = keys
    test_case = config.get_parsed_content(id=case_id, instantiate=True, lazy=False)  # transform instance
    dataset = CacheDataset(self.files, transform=test_case)
    loader = DataLoader(dataset, batch_size=3, shuffle=True)
    for x in loader:
        self.assertIsInstance(x[keys[0]], MetaTensor)
        self.assertIsInstance(x[keys[1]], MetaTensor)
        out = decollate_batch(x)  # decollate every batch should work
    # test forward patches
    loaded = out[0]
    if not monai_config.USE_META_DICT:
        self.assertEqual(len(loaded), len(keys))
    else:
        self.assertNotEqual(len(loaded), len(keys))
    img, seg = loaded[keys[0]], loaded[keys[1]]
    expected = config.get_parsed_content(id=f"{case_id}_answer", instantiate=True)  # expected results
    self.assertEqual(expected["load_shape"], list(x[keys[0]].shape))
    assert_allclose(expected["affine"], img.affine, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    assert_allclose(expected["affine"], seg.affine, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    test_cls = [type(x).__name__ for x in test_case.transforms]
    tracked_cls = [x[TraceKeys.CLASS_NAME] for x in img.applied_operations]
    self.assertTrue(len(tracked_cls) <= len(test_cls))  # tracked items should  be no more than the compose items.
    with tempfile.TemporaryDirectory() as tempdir:  # test writer
        SaveImageD(keys, resample=False, output_dir=tempdir, output_postfix=case_id)(loaded)
    test_data = reset_ops_id(deepcopy(loaded))
    for val in test_data.values():
        if isinstance(val, MetaTensor) and val.applied_operations:
            self.assertEqual(val.applied_operations[-1][TraceKeys.ID], TraceKeys.NONE)
    # test inverse
    inv = InvertD(keys, orig_keys=keys, transform=test_case, nearest_interp=True)
    out = inv(loaded)
    img, seg = out[keys[0]], out[keys[1]]
    assert_allclose(expected["inv_affine"], img.affine, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    assert_allclose(expected["inv_affine"], seg.affine, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    self.assertFalse(img.applied_operations)
    self.assertFalse(seg.applied_operations)
    assert_allclose(expected["inv_shape"], img.shape, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    assert_allclose(expected["inv_shape"], seg.shape, type_test=False, atol=TINY_DIFF, rtol=TINY_DIFF)
    with tempfile.TemporaryDirectory() as tempdir:  # test writer
        SaveImageD(keys, resample=False, output_dir=tempdir, output_postfix=case_id)(out)
        seg_file = os.path.join(tempdir, key_1, f"{key_1}_{case_id}.nii.gz")
        segout = nib.load(seg_file).get_fdata()
        segin = nib.load(FILE_PATH_1).get_fdata()
        ndiff = np.sum(np.abs(segout - segin) > 0)
        total = np.prod(segout.shape)
    self.assertTrue(ndiff / total < 0.4, f"{ndiff / total}")