tf.random.experimental.stateless_split

Splits an RNG seed into num new seeds by adding a leading axis.

tf.random.experimental.stateless_split(
    seed, num=2, alg='auto_select'
)

Example:

seed = [1, 2]
new_seeds = tf.random.experimental.stateless_split(seed, num=3)
print(new_seeds)
tf.Tensor(
[[1105988140 1738052849]
 [-335576002  370444179]
 [  10670227 -246211131]], shape=(3, 2), dtype=int32)
tf.random.stateless_normal(shape=[3], seed=new_seeds[0, :])
<tf.Tensor: shape=(3,), dtype=float32, numpy=array([-0.59835213, -0.9578608 ,
0.9002807 ], dtype=float32)>

seed an RNG seed (a tensor with shape [2] and dtype int32 or int64). (When using XLA, only int32 is allowed.)
num optional, a positive integer or scalar tensor indicating the number of seeds to produce (default 2).
alg The RNG algorithm used to generate the random numbers. See tf.random.stateless_uniform for a detailed explanation.

A tensor with shape [num, 2] representing num new seeds. It will have the same dtype as seed (if seed doesn't have an explict dtype, the dtype will be determined by tf.convert_to_tensor).