code: def get_model(inputs_shape, hmodel):
      hidden = hmodel.as_layer()
      ni = Input(inputs_shape)
      nn = hidden(ni)
      nn = Dropout(keep=0.8)(nn)
      nn = Dense(n_units=10, act=tf.nn.relu)(nn)
  
      return Model(inputs=ni, outputs=nn, name="mlp")
  
file_path: TensorLayer/examples/basic_tutorials/tutorial_mnist_mlp_static_2.py
imports: 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 2 for calling a global function with example usage: get_model(inputs_shape, hmodel) and returns: Model