code: def get_model(inputs_shape):
      ni = Input(inputs_shape)
      nn = Dropout(keep=0.8)(ni)
      nn = Dense(n_units=800, act=tf.nn.relu)(nn)
      nn = Dropout(keep=0.8)(nn)
      nn = Dense(n_units=800, act=tf.nn.relu)(nn)
      nn = Dropout(keep=0.8)(nn)
      nn = Dense(n_units=10, act=tf.nn.relu)(nn)
      M = Model(inputs=ni, outputs=nn, name="mlp")
      return M
  
file_path: TensorLayer/examples/basic_tutorials/tutorial_mnist_mlp_static.py
imports: import pprint
  import time
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import Dense, Dropout, Input
  from tensorlayer.models import Model
label_desc: Use image node_id 1 for calling a global function with example usage: get_model(inputs_shape) and returns: M