code: def test_batch_norm_convert_model_backprop(self):
      deeplift_model = kc.convert_model_from_saved_files(
          self.saved_file_path,
          nonlinear_mxts_mode=NonlinearMxtsMode.Rescale,
      )
      deeplift_multipliers_func = (
          deeplift_model.get_target_multipliers_func(
              find_scores_layer_idx=0, target_layer_idx=-1
          )
      )
      np.testing.assert_almost_equal(
          deeplift_multipliers_func(
              task_idx=0,
              input_data_list=[self.inp],
              batch_size=10,
              progress_update=None,
          ),
          self.grad_func([self.inp, 0]),
          decimal=5,
      )
  
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
  from deeplift.conversion import kerasapi_conversion
  import deeplift.layers
  from deeplift.layers import NonlinearMxtsMode, DenseMxtsMode
  from deeplift.util import compile_func
  import tensorflow
  import keras
  from keras import models
  from keras import backend
label_desc: Use image node_id 4 for calling the TestBatchNorm obj's underlying member method code with example usage: obj.test_batch_norm_convert_model_backprop() without return types