code: def test_fprop_stride(self):
      conv_layer = layers.Conv2D(
          kernel=self.conv_W,
          bias=self.conv_b,
          strides=(2, 2),
          padding=PaddingMode.valid,
          data_format="channels_last",
          conv_mxts_mode="Linear",
      )
      self.create_small_net_with_conv_layer(
          conv_layer, outputs_per_channel=4
      )
  
      func = compile_func(
          [self.input_layer.get_activation_vars()],
          self.conv_layer.get_activation_vars(),
      )
      np.testing.assert_almost_equal(
          func(self.inp),
          np.array(
              [
                  [
                      [[439, 495], [663, 719]],
                      [[-439, -495], [-663, -719]],
                  ],
                  [
                      [[1335, 1391], [1559, 1615]],
                      [[-1335, -1391], [-1559, -1615]],
                  ],
              ]
          ).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 5 for calling the TestConv obj's underlying member method code with example usage: obj.test_fprop_stride() without return types