Tensorflow basic example - Variables initialization

Question

I am having this code:

import tensorflow as tf
import numpy as np

data = np.random.randint(1000, size=10000)
x = tf.Variable(data, name='x')
y = tf.Variable(5*x*x-3*x+15, name='y')

model = tf.initialize_all_variables();

with tf.Session() as s:
    s.run(model)
    print (s.run(y))

I am trying to implement an exercise related to tensorflow variables but it fails with the following error:

Attempting to use uninitialized value x_20 [[Node: x_20/read = IdentityT=DT_INT64, _class=["loc:@x_20"], _device="/job:localhost/replica:0/task:0/cpu:0"]]

I also tried to initialize x with a constant but it still fails. What am I missing here ?

mdaoust · Accepted Answer · 2016-10-20 20:29:25Z

2

I think it's your definition of y that's a bit funny.

Your code currently makes a variable y and initializes it to 5*x*x-3*x+15

Maybe you just mean that the value of y is calculated from the value of x:

y=5*x*x-3*x+15

If you actually want to initialize a new variable y with the initial value of that expression over x, then you need to use x.initialized_value():

x = tf.Variable(data, name='x')
x0 = x.initialized_value()
y = tf.Variable(5*x0*x0-3*x0+15, name='y')

The traceback you're getting is coming from the fact that the initialize operation is trying to initialize y, before initializing x.

The .initialized_value() method enforces the order.

See: https://www.tensorflow.org/versions/r0.11/how_tos/variables/index.html#initialization-from-another-variable

edited Oct 20, 2016 at 20:29

answered Oct 20, 2016 at 18:50

mdaoust

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Kasparov92 · Accepted Answer · 2016-10-20 17:46:24Z

0

To solve this issue, I had to provide a constant value to the variable x. So I changed this line:

x = tf.Variable(data, name='x')

to the following line:

x = tf.constant(data, name='x')

It seems that a variable must be given a constant value.

answered Oct 20, 2016 at 17:46

Kasparov92

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