code: def tower_func(image):
      # img: 227x227x3
      with argscope([Conv2D, FullyConnected], activation=tf.nn.relu):
          l = Conv2D(
              "conv1",
              image,
              filters=96,
              kernel_size=11,
              strides=4,
              padding="VALID",
          )
          l = tf.nn.lrn(
              l, 2, bias=1.0, alpha=2e-5, beta=0.75, name="norm1"
          )
          l = MaxPooling("pool1", l, 3, strides=2, padding="VALID")
  
          l = Conv2D("conv2", l, filters=256, kernel_size=5, split=2)
          l = tf.nn.lrn(
              l, 2, bias=1.0, alpha=2e-5, beta=0.75, name="norm2"
          )
          l = MaxPooling("pool2", l, 3, strides=2, padding="VALID")
  
          l = Conv2D("conv3", l, filters=384, kernel_size=3)
          l = Conv2D("conv4", l, filters=384, kernel_size=3, split=2)
          l = Conv2D("conv5", l, filters=256, kernel_size=3, split=2)
          l = MaxPooling("pool3", l, 3, strides=2, padding="VALID")
  
          # This is just a script to load model, so we ignore the dropout layer
          l = FullyConnected("fc6", l, 4096)
          l = FullyConnected("fc7", l, 4096)
      logits = FullyConnected("fc8", l, 1000)
      tf.nn.softmax(logits, name="prob")
  
file_path: tensorpack/examples/CaffeModels/load-alexnet.py
imports: from __future__ import print_function
  import argparse
  import os
  import cv2
  import tensorflow
  from tensorpack import *
  from tensorpack.dataflow.dataset import ILSVRCMeta
  from tensorpack.tfutils.summary import *
label_desc: Use image node_id 1 for calling a global function with example usage: tower_func(image) without return types