code: def setUpClass(cls):
      x = tf.placeholder(tf.float32, shape=(None, 784), name="x")
  
      # define the network
      net_in = tl.layers.InputLayer(x, name="in")
      net_in = tl.layers.DropoutLayer(net_in, keep=0.8, name="in/drop")
      # net 0
      net_0 = tl.layers.DenseLayer(
          net_in, n_units=800, act=tf.nn.relu, name="net0/relu1"
      )
      net_0 = tl.layers.DropoutLayer(net_0, keep=0.5, name="net0/drop1")
      net_0 = tl.layers.DenseLayer(
          net_0, n_units=800, act=tf.nn.relu, name="net0/relu2"
      )
      # net 1
      net_1 = tl.layers.DenseLayer(
          net_in, n_units=800, act=tf.nn.relu, name="net1/relu1"
      )
      net_1 = tl.layers.DropoutLayer(net_1, keep=0.8, name="net1/drop1")
      net_1 = tl.layers.DenseLayer(
          net_1, n_units=800, act=tf.nn.relu, name="net1/relu2"
      )
      net_1 = tl.layers.DropoutLayer(net_1, keep=0.8, name="net1/drop2")
      net_1 = tl.layers.DenseLayer(
          net_1, n_units=800, act=tf.nn.relu, name="net1/relu3"
      )
      # multiplexer
      net_mux = tl.layers.MultiplexerLayer(
          layers=[net_0, net_1], name="mux"
      )
      network = tl.layers.ReshapeLayer(
          net_mux, shape=(-1, 800), name="reshape"
      )
      network = tl.layers.DropoutLayer(network, keep=0.5, name="drop3")
      # output layer
      network = tl.layers.DenseLayer(network, n_units=10, name="output")
  
      network.print_layers()
      network.print_params(False)
  
      cls.net_shape = network.outputs.get_shape().as_list()
      cls.net_layers = network.all_layers
      cls.net_params = network.all_params
      cls.net_all_drop = network.all_drop
      cls.net_n_params = network.count_params()
  
file_path: TensorLayer/tests/pending/test_layers_flow_control.py
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_Flow_Control_Test obj's underlying member method code with example usage: obj.setUpClass(cls) without return types