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Map various PRNG seed flavors to a seed Tensor
.
tfp.random.sanitize_seed(
seed, salt=None, name=None
)
Used in the notebooks
Used in the tutorials |
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This function implements TFP's standard PRNG seeding semantics. See https://github.com/tensorflow/probability/blob/main/PRNGS.md for details.
Operationally, sanitize_seed
maps any seed flavor to a
"stateless-compatible" seed, namely a int32[2]
Tensor. To wit:
- If the
seed
argument is anint
orNone
, we usetf.random.uniform
to statefully draw a pair of unboundedint32
s and wrap them into a Tensor. - If the
seed
argument is a stateless-compatible seed already, we just cast it to anint32[2]
Tensor.
This, any function that accepts a seed
argument can be written in
stateless-seed style internally, and acquires TFP's
seed-type-directed stateless/stateful switching behavior by just
running the input seed through sanitize_seed
on entry.
The sanitize_seed
function also allows salting the seed: if a user
accidentally passes the same stateful seed to two different calls to
sanitize_seed
with different salts, they will get independent
randomness. We may micro-optimize by removing salting from
sanitize_seed
of already-stateless seeds in the future, as using a
stateless seed already requires seed uniqueness discipline.
Args | |
---|---|
seed
|
An int32[2] Tensor or a Python list or tuple of 2 ints ,
which will be treated as stateless seeds; or a Python int or
None , which will be treated as stateful seeds.
|
salt
|
An optional Python string. |
name
|
An optional Python string, name to add to TF ops created by this function. |
Returns | |
---|---|
seed
|
An int32[2] Tensor suitable for use as a stateless PRNG
seed.
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