code: def set_up_prediction_func_and_deeplift_func(self, out_layer):
      out_layer.set_inputs(self.dense_layer)
      out_layer.build_fwd_pass_vars()
      self.input_layer.reset_mxts_updated()
      out_layer.set_scoring_mode(layers.ScoringMode.OneAndZeros)
      out_layer.set_active()
      self.input_layer.update_mxts()
  
      fprop_func = compile_func(
          [self.input_layer.get_activation_vars()],
          out_layer.get_activation_vars(),
      )
      fprop_results = [list(x) for x in fprop_func(self.inp)]
  
      bprop_func = compile_func(
          [
              self.input_layer.get_activation_vars(),
              self.input_layer.get_reference_vars(),
          ],
          self.input_layer.get_mxts(),
      )
      bprop_results_each_task = []
      for task_idx in range(len(fprop_results[0])):
          out_layer.update_task_index(task_index=task_idx)
          bprop_results_task = [
              list(x)
              for x in bprop_func([self.inp, np.zeros_like(self.inp)])
          ]
          bprop_results_each_task.append(bprop_results_task)
  
      out_layer.set_inactive()
      return fprop_results, bprop_results_each_task
  
file_path: deeplift/tests/layers/test_activation.py
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  import unittest
  from unittest import skip
  import sys
  import os
  import numpy
  import deeplift.layers
  from deeplift.layers import DenseMxtsMode
  from deeplift.util import compile_func
  import tensorflow
label_desc: Use image node_id 2 for calling the TestActivations obj's underlying member method code with example usage: obj.set_up_prediction_func_and_deeplift_func(out_layer) and returns: fprop_results,  bprop_results_each_task