code: def test_n_trans(self, transform, expected_shape):
      data_array = np.random.randint(0, 2, size=[128, 128, 128]).astype(
          float
      )
      test_image = nib.Nifti1Image(data_array, np.eye(4))
      with tempfile.TemporaryDirectory() as tempdir:
          nib.save(
              test_image, os.path.join(tempdir, "test_image.nii.gz")
          )
          test_data = [
              {"image": os.path.join(tempdir, "test_image.nii.gz")}
          ]
  
          cache_dir = os.path.join(
              os.path.join(tempdir, "cache"), "data"
          )
          dataset_precached = CacheNTransDataset(
              data=test_data,
              transform=transform,
              cache_dir=cache_dir,
              cache_n_trans=2,
          )
          data_precached = dataset_precached[0]
          self.assertTupleEqual(
              data_precached["image"].shape, expected_shape
          )
  
          dataset_postcached = CacheNTransDataset(
              data=test_data,
              transform=transform,
              cache_dir=cache_dir,
              cache_n_trans=2,
          )
          data_postcached = dataset_postcached[0]
          self.assertTupleEqual(
              data_postcached["image"].shape, expected_shape
          )
          np.testing.assert_allclose(
              data_array + 6.0, data_postcached["image"]
          )
          np.testing.assert_allclose(
              data_precached["image"], data_postcached["image"]
          )
  
file_path: MONAI/tests/test_cachentransdataset.py
imports: from __future__ import annotations
  import os
  import tempfile
  import unittest
  import nibabel
  import numpy
  from parameterized import parameterized
  from monai.data import CacheNTransDataset
  from monai.transforms import LoadImaged, ShiftIntensityd
label_desc: Use image node_id 1 for calling the TestCacheNTransDataset obj's underlying member method code with example usage: obj.test_n_trans(transform, expected_shape) without return types