code: def _map_fn_test(img, target):
      # 1. Crop the central [height, width] of the image.
      img = tf.image.resize_with_pad(img, 24, 24)
      # 2. Subtract off the mean and divide by the variance of the pixels.
      img = tf.image.per_image_standardization(img)
      img = tf.reshape(img, (24, 24, 3))
      target = tf.reshape(target, ())
      return img, target
  
file_path: TensorLayer/examples/quantized_net/tutorial_dorefanet_cifar10_tfrecord.py
imports: import multiprocessing
  import time
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import Conv2d, Dense, DorefaConv2d, DorefaDense, Flatten, Input, LocalResponseNorm, MaxPool2d
  from tensorlayer.models import Model
label_desc: Use image node_id 5 for calling a global function with example usage: _map_fn_test(img, target) and returns: img,  target