model_func.py 文件源码

def huber_loss(infer, label, epsilon, layer_name):
    """
    Args:
        infer
        label
        epsilon
        layer_name
    """
    with tf.variable_scope(layer_name):
        abs_diff = tf.abs(tf.sub(infer, label));
        index = tf.to_int32(abs_diff <= epsilon, name = 'partition_index')
        l1_part, l2_part = tf.dynamic_partition(abs_diff, index, 2)
        #l1_loss = tf.reduce_mean(l1_part, name = 'l1_loss')
        #l2_loss = tf.reduce_mean(tf.square(l2_part), name = 'l2_loss')
        l1_part_loss = epsilon * (l1_part - 0.5 * epsilon)
        l2_part_loss = 0.5 * tf.square(l2_part)
        hloss = tf.reduce_mean(tf.concat(0, [l1_part_loss,l2_part_loss]), 
                    name = 'huber_loss_sum')
    return hloss