code: def test_dense_backprop(self):
      conv_layer = layers.Conv2D(
          kernel=self.conv_W,
          bias=self.conv_b,
          strides=(1, 1),
          padding=PaddingMode.valid,
          data_format="channels_last",
          conv_mxts_mode="Linear",
      )
      self.create_small_net_with_conv_layer(
          conv_layer, outputs_per_channel=9
      )
  
      self.dense_layer.update_task_index(task_index=0)
      func = compile_func(
          [
              self.input_layer.get_activation_vars(),
              self.input_layer.get_reference_vars(),
          ],
          self.input_layer.get_mxts(),
      )
      np.testing.assert_almost_equal(
          func([self.inp, np.zeros_like(self.inp)]),
          np.array(
              [
                  [
                      [
                          [0, 2, 2, 2],
                          [4, 12, 12, 8],
                          [4, 12, 12, 8],
                          [4, 10, 10, 6],
                      ],
                      [
                          [8, 18, 18, 10],
                          [20, 44, 44, 24],
                          [20, 44, 44, 24],
                          [12, 26, 26, 14],
                      ],
                  ],
                  [
                      [
                          [0, 2, 2, 2],
                          [4, 12, 12, 8],
                          [4, 12, 12, 8],
                          [4, 10, 10, 6],
                      ],
                      [
                          [8, 18, 18, 10],
                          [20, 44, 44, 24],
                          [20, 44, 44, 24],
                          [12, 26, 26, 14],
                      ],
                  ],
              ]
          ).transpose(0, 2, 3, 1),
      )
  
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.layers.convolutional import PoolMode, PaddingMode
  from deeplift.util import compile_func
  import itertools
label_desc: Use image node_id 4 for calling the TestConv obj's underlying member method code with example usage: obj.test_dense_backprop() without return types