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
)
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)>
Args |
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).
|
Returns |
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 ).
|
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Last updated 2021-02-18 UTC.
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