code: def loss_net(hidden, label):
      prediction = fluid.layers.fc(input=hidden, size=10, act="softmax")
      loss = fluid.layers.cross_entropy(input=prediction, label=label)
      avg_loss = fluid.layers.mean(loss)
      acc = fluid.layers.accuracy(input=prediction, label=label)
      return prediction, avg_loss, acc
  
file_path: AdvBox/DataPoison/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 2 for calling a global function with example usage: loss_net(hidden, label) and returns: prediction,  avg_loss,  acc