code: def setUpClass(cls):
      def get_network_1d(inputs, reuse=False):
          with tf.variable_scope("1D_network", reuse=reuse):
              net = tl.layers.InputLayer(inputs)
  
              net1 = tl.layers.Conv1d(net, name="Conv1d")  # 2 params
              net2 = tl.layers.SeparableConv1d(
                  net1, name="SeparableConv1d"
              )  # 3 params
              net3 = tl.layers.MaxPool1d(
                  net2, (1,), name="MaxPool1d"
              )  # 0 params
              net4 = tl.layers.MeanPool1d(
                  net3, (1,), name="MeanPool1d"
              )  # 0 params
  
              # HAO Test
              net5 = tl.layers.Conv1d(net4, name="Conv1d1")  # 2 params
              net6 = tl.layers.SeparableConv1d(
                  net5, name="SeparableConv1d1"
              )  # 3 params
              net7 = tl.layers.SeparableConv1d(
                  net6, name="SeparableConv1d2"
              )  # 3 params
  
          return [net, net1, net2, net3, net4, net5, net6, net7]
  
      input_pl_train = tf.placeholder(tf.float32, [None, 32, 3])
      input_plh_test = tf.placeholder(tf.float32, [None, 32, 3])
  
      cls.network_1 = get_network_1d(input_pl_train, reuse=False)
      cls.network_2 = get_network_1d(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_1D_Test obj's underlying member method code with example usage: obj.setUpClass(cls) and returns: list