并在session里执行graph

n_samples = xs.shape[0]
with tf.Session() as sess:
	# 记得初始化所有变量
	sess.run(tf.global_variables_initializer()) 
	
	writer = tf.summary.FileWriter('./graphs/linear_reg', sess.graph)
	
	# 训练模型
	for i in range(50):
		total_loss = 0
		for x, y in zip(xs, ys):
			# 通过feed_dic把数据灌进去
			_, l = sess.run([optimizer, loss], feed_dict={X: x, Y:y}) 
			total_loss += l
		if i%5 ==0:
			print('Epoch {0}: {1}'.format(i, total_loss/n_samples))

	# 关闭writer
	writer.close() 
	
	# 取出w和b的值
	W, b = sess.run([W, b])