code: def _normalise_logits(self, data, axis=0):
      # check if logits is a true prob, if not then apply softmax
      if not np.allclose(np.sum(data, axis=axis), 1.0):
          logger.info(
              "found non normalized logits, normalizing using Softmax"
          )
          data = softmax(data, axis=axis)
  
      return data
  
imports: import logging
  from copy import deepcopy
  from typing import Optional
  import numpy
  import torch
  from monai.data import MetaTensor
  from monai.networks.blocks import CRF
  from monai.transforms import Transform
  from scipy.special import softmax
  from .utils import make_iseg_unary, make_likelihood_image_gmm, make_likelihood_image_histogram, maxflow
label_desc: Use image node_id 4 for calling the InteractiveSegmentationTransform obj's underlying member method code with example usage: obj._normalise_logits(data, axis) and returns: data