code: def test_histogram_graphcut_inferer(self, test_input, expected_shape):
      test_input.update({"image_path": "fakepath.nii"})
  
      # save data to file and update test dictionary
      image_file, data = Writer(label="image", nibabel=True)(test_input)
      scribbles_file, data = Writer(label="label", nibabel=True)(
          test_input
      )
  
      # add paths to file, remove any associated meta_dict
      test_input["image"] = image_file
      test_input["label"] = scribbles_file
  
      test_input.pop("image_meta_dict", None)
      test_input.pop("label_meta_dict", None)
  
      # run scribbles inferer and load results
      result_file, _ = HistogramBasedGraphCut()(test_input)
      result = LoadImage(image_only=True)(result_file)
  
      # can only check output shape due to non-deterministic results
      self.assertTupleEqual(expected_shape, result.shape)
  
imports: import unittest
  import numpy
  from monai.transforms import LoadImage
  from monai.utils import set_determinism
  from parameterized import parameterized
  from monailabel.scribbles.infer import HistogramBasedGraphCut
  from monailabel.scribbles.transforms import AddBackgroundScribblesFromROId, ApplyGraphCutOptimisationd, InteractiveSegmentationTransform, MakeISegUnaryd, MakeLikelihoodFromScribblesHistogramd, SoftenProbSoftmax
  from monailabel.transform.writer import Writer
label_desc: Use image node_id 1 for calling the TestScribblesInferers obj's underlying member method code with example usage: obj.test_histogram_graphcut_inferer(test_input, expected_shape) without return types