code: def test_conv_with_custom_tuple_padding(self):
      inp = layers.Input((5, 5, 1))
      conv = layers.Convolution(
          (3, 3, 1), bias=0, weight=1, padding=(0, 2)
      )
  
      network = inp >> conv
      network.outputs
  
      x = asfloat(np.ones((1, 5, 5, 1)))
      expected_output = np.array(
          [
              [3, 6, 9, 9, 9, 6, 3],
              [3, 6, 9, 9, 9, 6, 3],
              [3, 6, 9, 9, 9, 6, 3],
          ]
      ).reshape((1, 3, 7, 1))
      actual_output = self.eval(network.output(x))
  
      np.testing.assert_array_almost_equal(
          expected_output, actual_output
      )
      self.assertShapesEqual(network.output_shape, (None, 3, 7, 1))
  
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 14 for calling the ConvLayersTestCase obj's underlying member method code with example usage: obj.test_conv_with_custom_tuple_padding() without return types