#-*- coding:utf-8 -*-
import tensorflow as tf
import numpy as np

value1 = tf.placeholder(dtype=tf.float32)
value2 = tf.placeholder(dtype=tf.float32)
value3 = value1 + value2

#定義的dataset有引數，只能使用引數化迭代器
dataset = tf.data.Dataset.range(10)
# 定義引數化迭代器
dataset = dataset.shuffle(100)
dataset = dataset.apply(tf.contrib.data.batch_and_drop_remainder(3))  #每個batch3個數據，不足3個捨棄
 

iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()

with tf.Session() as sess:
    # 需要用引數初始化迭代器
    for i in range(2):
        sess.run(iterator.initializer)
        while True:
            try:
                value = sess.run(next_element)
                result = sess.run(value3,feed_dict={value1:value,value2:value})
                print(result)
            except tf.errors.OutOfRangeError:
                print("End of epoch %d" % i)
                break