code: def mlp(x, is_train=True, reuse=False):
      with tf.variable_scope("MLP", reuse=reuse):
          tl.layers.set_name_reuse(reuse)  # print warning
          network = tl.layers.InputLayer(x, name="input")
          network = tl.layers.DropoutLayer(
              network,
              keep=0.8,
              is_fix=True,
              is_train=is_train,
              name="drop1",
          )
          network = tl.layers.DenseLayer(
              network, n_units=800, act=tf.nn.relu, name="relu1"
          )
          network = tl.layers.DropoutLayer(
              network,
              keep=0.5,
              is_fix=True,
              is_train=is_train,
              name="drop2",
          )
          network = tl.layers.DenseLayer(
              network, n_units=800, act=tf.nn.relu, name="relu2"
          )
          network = tl.layers.DropoutLayer(
              network,
              keep=0.5,
              is_fix=True,
              is_train=is_train,
              name="drop3",
          )
          network = tl.layers.DenseLayer(
              network, n_units=10, name="output"
          )
      return network
  
file_path: TensorLayer/tests/pending/test_reuse_mlp.py
imports: import os
  import unittest
  import tensorflow
  import tensorlayer
  from tests.utils import CustomTestCase
label_desc: Use image node_id 1 for calling a global function with example usage: mlp(x, is_train, reuse) and returns: network