code: def setUpClass(cls):
      def get_network_3d(inputs, reuse=False):
          with tf.variable_scope("3D_network", reuse=reuse):
              net = tl.layers.InputLayer(inputs)
  
              net1 = tl.layers.Conv3dLayer(
                  net,
                  shape=(2, 2, 2, 3, 32),
                  strides=(1, 2, 2, 2, 1),
                  name="Conv3dLayer",
              )  # 2 params
              net2 = tl.layers.DeConv3d(
                  net1, name="DeConv3d"
              )  # 2 params
              net3 = tl.layers.MaxPool3d(
                  net2, (1, 1, 1), name="MaxPool3d"
              )  # 0 params
              net4 = tl.layers.MeanPool3d(
                  net3, (1, 1, 1), name="MeanPool3d"
              )  # 0 params
  
              # HAO Test
              net5 = tl.layers.DeConv3d(
                  net4, name="DeConv3d1"
              )  # 2 params
  
              return [net, net1, net2, net3, net4, net5]
  
      input_pl_train = tf.placeholder(tf.float32, [None, 32, 32, 32, 3])
      input_plh_test = tf.placeholder(tf.float32, [None, 32, 32, 32, 3])
  
      cls.network_1 = get_network_3d(input_pl_train, reuse=False)
      cls.network_2 = get_network_3d(input_plh_test, reuse=True)
  
imports: import os
  import unittest
  import tensorflow
  import tensorlayer
  from tests.utils import CustomTestCase
label_desc: Use image node_id 1 for calling the Layer_Convolution_3D_Test obj's underlying member method code with example usage: obj.setUpClass(cls) and returns: list