How do I generate a random vector in TensorFlow and maintain it for further use?

Question

I am trying to generate a random variable and use it twice. However, when I use it the second time, the generator creates a second random variable that is not identical to the f

Answer 1

The current version of your code will randomly generate a new value for rand_var_1 and rand_var_2 on each call to sess.run() (although since you set the seed to 0, they will have the same value within a single call to sess.run()).

If you want to retain the value of a randomly-generated tensor for later use, you should assign it to a tf.Variable:

rand_var_1 = tf.Variable(tf.random_uniform([5], 0, 10, dtype=tf.int32, seed=0))
rand_var_2 = tf.Variable(tf.random_uniform([5], 0, 10, dtype=tf.int32, seed=0))

# Or, alternatively:
rand_var_1 = tf.Variable(tf.random_uniform([5], 0, 10, dtype=tf.int32, seed=0))
rand_var_2 = tf.Variable(rand_var_1.initialized_value())

# Or, alternatively:
rand_t = tf.random_uniform([5], 0, 10, dtype=tf.int32, seed=0)
rand_var_1 = tf.Variable(rand_t)
rand_var_2 = tf.Variable(rand_t)

...then tf.initialize_all_variables() will have the desired effect:

# Op 1
z1 = tf.add(rand_var_1, rand_var_2)

# Op 2
z2 = tf.add(rand_var_1, rand_var_2)

init = tf.initialize_all_variables()

with tf.Session() as sess:
    sess.run(init)        # Random numbers generated here and cached.
    z1_op = sess.run(z1)  # Reuses cached values for rand_var_1, rand_var_2.
    z2_op = sess.run(z2)  # Reuses cached values for rand_var_1, rand_var_2.
    print(z1_op, z2_op)   # Will print two identical vectors.