code: def get_prediction_function(self, input_layer_idx, output_layer_idx):
      return self._get_prediction_function(
          inputs=[
              self.get_layers()[input_layer_idx].get_activation_vars()
          ],
          output=self.get_layers()[
              output_layer_idx
          ].get_activation_vars(),
      )
  
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  import sys
  import os
  import numpy
  import yaml
  from collections import namedtuple
  from collections import OrderedDict
  from collections import defaultdict
  import deeplift.util
  from deeplift import layers
  from deeplift.layers import *
  from deeplift.layers import ScoringMode
  from deeplift.util import compile_func
label_desc: Use image node_id 4 for calling the SequentialModel obj's underlying member method code with example usage: obj.get_prediction_function(input_layer_idx, output_layer_idx) and returns: self