tensorflow的binary错误问题

[发奋图强五花肉]

在做tensorflow练习，代码如下，但是一直报错“TypeError: Expected binary or unicode string, got <function relu at 0x10fc977b8>
”
不是很理解到底那里出错了
python3.6，tensorflow 1
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 2017/5/17 下午3:35

@author: zhechengma
"""

import tensorflow as tf
import numpy as np

def add_layer(inputs,in_size,out_size,activation_function=None): #定义一个层
weights=tf.Variable(tf.random_normal([in_size,out_size]))#定义个矩阵权重
biases=tf.Variable(tf.zeros([1,out_size])+0.1) #定义偏重
wx_plu_b=tf.matmul(inputs,weights)+biases #定义函数输入*权重+偏重

if activation_function is None:
outputs=wx_plu_b
else:
outputs=activation_function
return outputs

x_data=np.linspace(-1,1,300)[:,np.newaxis] #设置输入层，np创造的一个矩阵
noise=np.random.normal(0,0.05,x_data.shape)#设置噪点层
y_data=np.square(x_data)-0.5+noise#设置目标层

# print(x_data+'first')
# print(noise+'nosis')
# print(y_data+'yceng')
xs=tf.placeholder(dtype = tf.float32,shape = None)
ys=tf.placeholder(dtype = tf.float32,shape = None)


l1=add_layer(xs,1,10,activation_function = tf.nn.relu)#添加一层，输入数据为xdata，输入大小为1，属楚大小为0，公式为relu
predition=add_layer(l1,10,1,activation_function = tf.nn.relu)#添加预测层，输入为第一层，输入大小为10（因为第一层输出大小为10），输出大小为1

loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-predition),reduction_indices = [1]))
train_step=tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init=tf.initialize_all_variables()#初始化
sess=tf.Session()#开始神经网络
sess.run(init)#开始运算

for i in range(1000):
sess.run(train_step,feed_dict = {x_data,y_data})
if i%50==0:
print(sess.run(loss,feed_dict = {x_data,y_data}))