code: def _build_pos_and_neg_contribs(self):
      (
          inp_pos_contribs,
          inp_neg_contribs,
      ) = self._get_input_pos_and_neg_contribs()
      pos_contribs = (
          self._batchnorm_scaling_terms_only(inp_pos_contribs)
          * (hf.gt_mask(self.reshaped_gamma, 0.0))
      ) + (
          self._batchnorm_scaling_terms_only(inp_neg_contribs)
          * (hf.lt_mask(self.reshaped_gamma, 0.0))
      )
      neg_contribs = (
          self._batchnorm_scaling_terms_only(inp_neg_contribs)
          * (hf.gt_mask(self.reshaped_gamma, 0.0))
      ) + (
          self._batchnorm_scaling_terms_only(inp_pos_contribs)
          * (hf.lt_mask(self.reshaped_gamma, 0.0))
      )
      return pos_contribs, neg_contribs
  
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  import sys
  import os
  import numpy
  from collections import namedtuple
  from collections import OrderedDict
  from collections import defaultdict
  import deeplift.util
  from .helper_functions import pseudocount_near_zero, add_val_to_col
  from .None import helper_functions
  from .core import SingleInputMixin, Node
  import tensorflow
label_desc: Use image node_id 5 for calling the BatchNormalization obj's underlying member method code with example usage: obj._build_pos_and_neg_contribs() and returns: pos_contribs,  neg_contribs