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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 |
|---|
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. Under TensorFlow and NumPy this means:
- If the
seedargument is anintorNone, we usetf.random.uniformto statefully draw a pair of unboundedint32s and wrap them into a Tensor. - If the
seedargument is a stateless-compatible seed already, we just cast it to anint32[2]Tensor.
Under JAX, this function only accepts outputs from jax.random.PRNGKey, being
a no-op except for the salting behavior described below.
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.
Returns | |
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seed
|
An int32[2] Tensor suitable for use as a stateless PRNG
seed.
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View source on GitHub