code: def data_aug_valid(img, ann):
      # 1. Crop the central [height, width] of the image.
      img = tf.image.resize_image_with_crop_or_pad(img, 24, 24)
      # 2. Subtract off the mean and divide by the variance of the pixels.
      img = tf.image.per_image_standardization(img)
      return img, ann
  
file_path: TensorLayer/examples/distributed_training/tutorial_cifar10_distributed_trainer.py
imports: import multiprocessing
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import BatchNormLayer, Conv2d, DenseLayer, FlattenLayer, InputLayer, MaxPool2d
label_desc: Use image node_id 3 for calling a global function with example usage: data_aug_valid(img, ann) and returns: img,  ann