code: def model(x, is_train):
      with tf.variable_scope("mlp", reuse=tf.AUTO_REUSE):
          network = tl.layers.InputLayer(x, name="input")
          network = tl.layers.DropoutLayer(
              network,
              keep=0.8,
              name="drop1",
              is_fix=True,
              is_train=is_train,
          )
          network = tl.layers.DenseLayer(
              network, 800, tf.nn.relu, name="relu1"
          )
          network = tl.layers.DropoutLayer(
              network,
              keep=0.5,
              name="drop2",
              is_fix=True,
              is_train=is_train,
          )
          network = tl.layers.DenseLayer(
              network, 800, tf.nn.relu, name="relu2"
          )
          network = tl.layers.DropoutLayer(
              network,
              keep=0.5,
              name="drop3",
              is_fix=True,
              is_train=is_train,
          )
          network = tl.layers.DenseLayer(
              network, n_units=10, act=tf.identity, name="output"
          )
      return network
  
imports: import numpy
  import tensorflow
  import tensorlayer
label_desc: Use image node_id 2 for calling a global function with example usage: model(x, is_train) and returns: network