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 import tensorflow as tf # Example 1: session keeps track of the random state c = tf.random.uniform([], -10, 10, seed=2) with tf.compat.v1.Session() as sess: print(sess.run(c)) # >> 3.574932 print(sess.run(c)) # >> -5.9731865 # Example 2: each new session will start the random state all over again. c = tf.random.uniform([], -10, 10, seed=2) with tf.compat.v1.Session() as sess: print(sess.run(c)) # >> 3.574932 with tf.compat.v1.Session() as sess: print(sess.run(c)) # >> 3.574932 # Example 3: with operation level random seed, each op keeps its own seed. c = tf.random.uniform([], -10, 10, seed=2) d = tf.random.uniform([], -10, 10, seed=2) with tf.compat.v1.Session() as sess: print(sess.run(c)) # >> 3.574932 print(sess.run(d)) # >> 3.574932 # Example 4: graph level random seed tf.compat.v1.set_random_seed(2) c = tf.random.uniform([], -10, 10) d = tf.random.uniform([], -10, 10) with tf.compat.v1.Session() as sess: print(sess.run(c)) # >> 9.123926 print(sess.run(d)) # >> -4.5340395
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