Change constant in tensoflow session while looping

Question

How can I change the tensorflow constant inside session for loop.
I am a learner and I am wondering how to update it in for loop

---

import tensorflow as tf
import numpy as np

looperCount = 10

data = np.random.randint(2, size=looperCount)
x = tf.constant(data, name='x')

y = tf.Variable((5 * (x * x)) - (3 * x) + 15, name="y")
model = tf.initialize_all_variables()

with tf.Session() as sess:
    for i in range(looperCount):
        sess.run(model)
        data = np.random.randint(2, size=looperCount)
        x = tf.constant(data, name='x')
        avg = np.average(sess.run(y))
        print "avg - {}, sess - {}".format(avg, sess.run(y))

---

Updated working code

import tensorflow as tf
import numpy as np

looperCount = 10

x = tf.placeholder("float", looperCount)
y = (5 * (x * x)) - (3 * x) + 15

with tf.Session() as sess:
    for i in range(looperCount):
        data = np.random.randint(10, size=looperCount)
        result_y = sess.run(y, feed_dict={x: data})
        avg = np.average(result_y)
        print "avg - {:10} valy - {:10}".format("{:.2f}".format(avg), result_y)

Answer 1

In TensorFlow, "constant" means exactly that: once you set it, you can't change it. To change the value that your TensorFlow program uses in the loop, you have two main choices: (1) using a tf.placeholder() to feed in a value, or (2) using a tf.Variable to store the value between steps, and tf.Variable.assign() to update it.

Option 1 is much easier. Here's an example of how you could use it to implement your program using a placeholder:

import tensorflow as tf
import numpy as np

looperCount = 10

data = np.random.randint(2, size=looperCount)
x = tf.placeholder(tf.float64, shape=[2], name="x")

y = tf.Variable((5 * (x * x)) - (3 * x) + 15, name="y")
init_op = tf.initialize_all_variables()

with tf.Session() as sess:
    sess.run(init_op)      
    for i in range(looperCount):
        data = np.random.randint(2, size=looperCount)
        avg = np.average(sess.run(y, feed_dict={x: data}))
        print "avg - {}, sess - {}".format(avg, sess.run(y, feed_dict={x: data}))