code: def _get_gradient_at_default_activation_var(self):
      return self._gradient_at_default_activation
  
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  from .core import SingleInputMixin, OneDimOutputMixin, Node, ScoringMode, NonlinearMxtsMode
  import tensorflow
  from deeplift.util import NEAR_ZERO_THRESHOLD
  from deeplift.layers import helper_functions
label_desc: Use image node_id 5 for calling the Activation obj's underlying member method code with example usage: obj._get_gradient_at_default_activation_var() and returns: self