code: def test_soften_prob_softmax_transforms(self):
      soften_tx = SoftenProbSoftmax(
          logits="logits", meta_key_postfix="meta_dict", prob="prob"
      )
      data = {"logits": np.random.rand(2, 128, 128, 128)}
      output_data = soften_tx(data)
  
      # minimum should be close to 0,1
      self.assertAlmostEqual(round(output_data["prob"].min(), 1), 0.1)
      # maximum should be close to 0.9
      self.assertAlmostEqual(round(output_data["prob"].max(), 1), 0.9)
  
      # shape should be same as input
      self.assertEqual(output_data["prob"].shape, data["logits"].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 6 for calling the TestScribblesTransforms obj's underlying member method code with example usage: obj.test_soften_prob_softmax_transforms() without return types