tensorflow/tf.set_random_seed()

tensorflow中设置随机种子，可分为两类，图级seed和操作级seed,
情况1：当没有设置图级seed和操作级seed时，生成的随机数是随机的
情况2：当设置操作级seed时，生成的随机数是同一组随机数，没有设置操作级seed的操作，生成的随机数是随机的
情况3：当设置图级seed, 将会生成同一组随机数，如果设置操作级seed又和情况2相同

  ```python  a = tf.random_uniform([1])  b = tf.random_normal([1])  print("Session 1")  with tf.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.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:  ```python  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.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.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:  ```python  tf.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.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.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.  """