Reproducible results in Tensorflow with tf.set_random_seed

Question

I am trying to generate N sets of independent random numbers. I have a simple code that shows the problem for 3 sets of 10 random numbers. I notice that even though I use th

Answer 1

There is a related GitHub issue. But in your case, please refer to the documentation of tf.set_random_seed:

Sets the graph-level random seed.

You probably want to use the same graph and same operation to get the same random numbers in different sessions.

import tensorflow as tf

tf.set_random_seed(1234)
generate = tf.random_uniform((10,), 0, 10)
tf.get_default_graph().finalize() # something everybody tends to forget

for i in range(3):
    with tf.Session() as sess:
        b = sess.run(generate)
        print(b)

gives

[9.604688  5.811516  6.4159    9.621765  0.5434954 4.1893444 5.8865128
 7.9785547 8.296125  8.388672 ]
[9.604688  5.811516  6.4159    9.621765  0.5434954 4.1893444 5.8865128
 7.9785547 8.296125  8.388672 ]
[9.604688  5.811516  6.4159    9.621765  0.5434954 4.1893444 5.8865128
 7.9785547 8.296125  8.388672 ]

In your case, you created different operations within the same graph.