tensorflow generate "fake" random variables for the model
<pre><code>tf.set_random_seed(1)
R = tf.Variable(tf.random_normal((2,2)), name="random_weights")
with tf.Session() as sess:
   tf.set_random_seed(1)
   sess.run(tf.initialize_all_variables())
   print(sess.run(R))
</code></pre>

<p>for this piece of code, everytime I run it, it generates different variables, is that any way I make it the same random number initialization, so that I could reoccur the exprinment result and analyze? </p>

<p>Fix operation-level seed as <code>tf.Variable(tf.random_normal((2,2), seed=1)</code></p>

python tensorflow