code: def create_model(inputs_shape):
      W_init = tl.initializers.truncated_normal(stddev=5e-2)
      W_init2 = tl.initializers.truncated_normal(stddev=0.04)
      ni = Input(inputs_shape)
      nn = Conv2d(
          64,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          name="conv1_1",
      )(ni)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool1_1")(nn)
      nn = Conv2d(
          64,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv1_2",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool1_2")(nn)
  
      nn = Conv2d(
          128,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv2_1",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool2_1")(nn)
      nn = Conv2d(
          128,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv2_2",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool2_2")(nn)
  
      nn = Conv2d(
          256,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv3_1",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool3_1")(nn)
      nn = Conv2d(
          256,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv3_2",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool3_2")(nn)
  
      nn = Conv2d(
          512,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv4_1",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool4_1")(nn)
      nn = Conv2d(
          512,
          (3, 3),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          W_init=W_init,
          b_init=None,
          name="conv4_2",
      )(nn)
      nn = MaxPool2d((2, 2), (2, 2), padding="SAME", name="pool4_2")(nn)
  
      nn = Flatten(name="flatten")(nn)
      nn = Dense(1000, act=None, W_init=W_init2, name="output")(nn)
  
      M = Model(inputs=ni, outputs=nn, name="cnn")
      return M
  
imports: import tensorlayer
  from tensorlayer.layers import Input, Conv2d, Flatten, Dense, MaxPool2d
  from tensorlayer.models import Model
  from tensorlayer.files import maybe_download_and_extract
  import numpy
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: create_model(inputs_shape) and returns: M