code: def test_transforms(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}")
  
file_path: MONAI/tests/test_metatensor_integration.py
imports: from __future__ import annotations
  import os
  import tempfile
  import unittest
  from copy import deepcopy
  import numpy
  from parameterized import parameterized
  from monai import config
  from monai.bundle import ConfigParser
  from monai.data import CacheDataset, DataLoader, MetaTensor, decollate_batch
  from monai.data.utils import TraceKeys
  from monai.transforms import InvertD, SaveImageD, reset_ops_id
  from monai.utils import optional_import, set_determinism
  from tests.utils import assert_allclose, download_url_or_skip_test, testing_data_config
label_desc: Use image node_id 3 for calling the TestMetaTensorIntegration obj's underlying member method code with example usage: obj.test_transforms(case_id) without return types