code: def convolutional_neural_network(img, label):
      conv_pool_1 = fluid.nets.simple_img_conv_pool(
          input=img,
          filter_size=5,
          num_filters=20,
          pool_size=2,
          pool_stride=2,
          act="relu",
      )
      conv_pool_1 = fluid.layers.batch_norm(conv_pool_1)
      conv_pool_2 = fluid.nets.simple_img_conv_pool(
          input=conv_pool_1,
          filter_size=5,
          num_filters=50,
          pool_size=2,
          pool_stride=2,
          act="relu",
      )
      return loss_net(conv_pool_2, label)
  
file_path: AdvBox/DataPoison/poison_mnist_paddle.py
imports: from __future__ import print_function
  from builtins import range
  import os
  import argparse
  from PIL import Image
  import numpy
  import paddle
  import paddle.fluid
label_desc: Use image node_id 5 for calling a global function with example usage: convolutional_neural_network(img, label) and returns: loss_net