docstr: Return the gradients at a specific supplied activation
docstr_tok: ["Return","the","gradients","at","a","specific","supplied","activation"]
code: def _get_gradient_at_activation(self, activation_vars):
      """
      Return the gradients at a specific supplied activation
      """
      raise NotImplementedError()
  
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 11 for calling the Activation obj's underlying member method code with example usage: obj._get_gradient_at_activation(activation_vars) without return types