code: def tower_func(image):
      is_training = get_current_tower_context().is_training
  
      with argscope(
          [tf.layers.conv2d],
          kernel_size=3,
          activation=tf.nn.relu,
          padding="same",
      ):
          x = image
          x = tf.layers.conv2d(x, 64, name="conv1_1")
          x = tf.layers.conv2d(x, 64, name="conv1_2")
          x = tf.layers.max_pooling2d(x, 2, 2, name="pool1")
  
          x = tf.layers.conv2d(x, 128, name="conv2_1")
          x = tf.layers.conv2d(x, 128, name="conv2_2")
          x = tf.layers.max_pooling2d(x, 2, 2, name="pool2")
  
          x = tf.layers.conv2d(x, 256, name="conv3_1")
          x = tf.layers.conv2d(x, 256, name="conv3_2")
          x = tf.layers.conv2d(x, 256, name="conv3_3")
          x = tf.layers.conv2d(x, 256, name="conv3_4")
          x = tf.layers.max_pooling2d(x, 2, 2, name="pool3")
  
          x = tf.layers.conv2d(x, 512, name="conv4_1")
          x = tf.layers.conv2d(x, 512, name="conv4_2")
          x = tf.layers.conv2d(x, 512, name="conv4_3")
          x = tf.layers.conv2d(x, 512, name="conv4_4")
          x = tf.layers.max_pooling2d(x, 2, 2, name="pool4")
  
          x = tf.layers.conv2d(x, 512, name="conv5_1")
          x = tf.layers.conv2d(x, 512, name="conv5_2")
          x = tf.layers.conv2d(x, 512, name="conv5_3")
          x = tf.layers.conv2d(x, 512, name="conv5_4")
          x = tf.layers.max_pooling2d(x, 2, 2, name="pool5")
          x = tf.layers.flatten(x, name="flatten")
  
          x = tf.layers.dense(
              x, 4096, activation=tf.nn.relu, name="fc6"
          )
          x = tf.layers.dropout(
              x, rate=0.5, name="drop0", training=is_training
          )
          x = tf.layers.dense(
              x, 4096, activation=tf.nn.relu, name="fc7"
          )
          x = tf.layers.dropout(
              x, rate=0.5, name="drop1", training=is_training
          )
          logits = tf.layers.dense(
              x, 1000, activation=tf.identity, name="fc8"
          )
  
      tf.nn.softmax(logits, name="prob")
  
file_path: tensorpack/examples/CaffeModels/load-vgg19.py
imports: from __future__ import print_function
  import argparse
  import numpy
  import os
  import cv2
  import six
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow.dataset import ILSVRCMeta
label_desc: Use image node_id 1 for calling a global function with example usage: tower_func(image) without return types