How to get internal tensor value in tensorflow

Question

When tensorflow's session is runned, i need to get the same value of y. How can i get y with same value, not rerun this graph?

import tensorflow as tf
import numpy as np

x = tf.Variable(0.0)
tf.set_random_seed(10)
x_plus1 = x+tf.random_normal([1], mean=0.0, stddev=0.01,dtype=tf.float32)

y = tf.Variable([1.0])
y += x_plus1

z = y + tf.random_normal([1], mean=0.0, stddev=0.01,dtype=tf.float32)

init = tf.global_variables_initializer()

with tf.Session() as sess:
    sess.run(init)
    print(z.eval())
    for i in range(5):
        print(y.eval())

Here, i want to get y that contributes to z.

Answer 1

You can evaluate y and z simultaneously with sess.run(), that runs the needed parts of the graph only once, hence the value for y will be the one used for z.

with tf.Session() as sess:
    sess.run(init)
    z_value, y_value = sess.run([z, y])
    print(z_value)
    print(y_value)

Answer 2

Modify the with block as following, this way you only evaluate the graph once, before the for loop, then you can print it as many times as you like:

with tf.Session() as sess:
    sess.run(init)
    print(z.eval())
    yy = y.eval()
    for i in range(5):
        print(yy)