import tensorflow as tf

    return inputs, feat

# image_size = 32, img_channels = 3, class_num = 10 in cifar10
x = tf.placeholder(tf.float32, shape=[None, image_size, image_size, img_channels])
label = tf.placeholder(tf.float32, shape=[None,])
one_hot_labels = tf.one_hot(indices=tf.cast(label, tf.int32), depth=class_num)

training_flag = tf.placeholder(tf.bool)
learning_rate = tf.placeholder(tf.float32, name='learning_rate')

