1、分类的loss损失函数:可设为交叉熵
cross_entropy = tf.reduce_mean( -tf.reduce_sum ( ys * tf.log ( prediction) ,
reduction_indices = [1] ))
cross_entropy = tf.reduce_mean( -tf.reduce_sum ( ys * tf.log ( prediction) ,
reduction_indices = [1] ))