Sets the graph-level random seed for the default graph.
tf.compat.v1.set_random_seed( seed )
Operations that rely on a random seed actually derive it from two seeds: the graph-level and operation-level seeds. This sets the graph-level seed.
Its interactions with operation-level seeds is as follows:
To illustrate the user-visible effects, consider these examples:
To generate different sequences across sessions, set neither graph-level nor op-level seeds:
a = tf.random.uniform([1]) b = tf.random.normal([1]) print("Session 1") with tf.compat.v1.Session() as sess1: print(sess1.run(a)) # generates 'A1' print(sess1.run(a)) # generates 'A2' print(sess1.run(b)) # generates 'B1' print(sess1.run(b)) # generates 'B2' print("Session 2") with tf.compat.v1.Session() as sess2: print(sess2.run(a)) # generates 'A3' print(sess2.run(a)) # generates 'A4' print(sess2.run(b)) # generates 'B3' print(sess2.run(b)) # generates 'B4'
To generate the same repeatable sequence for an op across sessions, set the seed for the op:
a = tf.random.uniform([1], seed=1) b = tf.random.normal([1]) # Repeatedly running this block with the same graph will generate the same # sequence of values for 'a', but different sequences of values for 'b'. print("Session 1") with tf.compat.v1.Session() as sess1: print(sess1.run(a)) # generates 'A1' print(sess1.run(a)) # generates 'A2' print(sess1.run(b)) # generates 'B1' print(sess1.run(b)) # generates 'B2' print("Session 2") with tf.compat.v1.Session() as sess2: print(sess2.run(a)) # generates 'A1' print(sess2.run(a)) # generates 'A2' print(sess2.run(b)) # generates 'B3' print(sess2.run(b)) # generates 'B4'
To make the random sequences generated by all ops be repeatable across sessions, set a graph-level seed:
tf.compat.v1.random.set_random_seed(1234) a = tf.random.uniform([1]) b = tf.random.normal([1]) # Repeatedly running this block with the same graph will generate the same # sequences of 'a' and 'b'. print("Session 1") with tf.compat.v1.Session() as sess1: print(sess1.run(a)) # generates 'A1' print(sess1.run(a)) # generates 'A2' print(sess1.run(b)) # generates 'B1' print(sess1.run(b)) # generates 'B2' print("Session 2") with tf.compat.v1.Session() as sess2: print(sess2.run(a)) # generates 'A1' print(sess2.run(a)) # generates 'A2' print(sess2.run(b)) # generates 'B1' print(sess2.run(b)) # generates 'B2'
Args | |
---|---|
seed | integer. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/set_random_seed