code: def test_conv_with_custom_int_padding(self):
      network = layers.join(
          layers.Input((5, 5, 1)),
          layers.Convolution((3, 3, 1), bias=0, weight=1, padding=2),
      )
  
      x = asfloat(np.ones((1, 5, 5, 1)))
      expected_output = np.array(
          [
              [1, 2, 3, 3, 3, 2, 1],
              [2, 4, 6, 6, 6, 4, 2],
              [3, 6, 9, 9, 9, 6, 3],
              [3, 6, 9, 9, 9, 6, 3],
              [3, 6, 9, 9, 9, 6, 3],
              [2, 4, 6, 6, 6, 4, 2],
              [1, 2, 3, 3, 3, 2, 1],
          ]
      ).reshape((1, 7, 7, 1))
  
      actual_output = self.eval(network.output(x))
      np.testing.assert_array_almost_equal(
          expected_output, actual_output
      )
  
imports: import random
  from itertools import product
  from collections import namedtuple
  import numpy
  import tensorflow
  from neupy import layers
  from neupy.utils import asfloat, shape_to_tuple
  from neupy.layers.convolutions import conv_output_shape, deconv_output_shape
  from neupy.exceptions import LayerConnectionError
  from base import BaseTestCase
label_desc: Use image node_id 13 for calling the ConvLayersTestCase obj's underlying member method code with example usage: obj.test_conv_with_custom_int_padding() without return types