Description
Hello,
I would like to discuss the possibility of adding the option of passing a numpy RandomState or Generator as 'seed', in order to seed via a client maintained rng state machine.
SciPy allows the seed to be used like this:
seed{None, int, RandomState, Generator}, optional
This parameter defines the object to use for drawing random variates. If seed is None the RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a RandomState or Generator instance, then that object is used. Default is None.
as is mentioned here.
This would have the following advantages:
- Thread-safe seeding
- Non-interference by other code (setting the seed via np.random.seed(seed) is vulnerable to outside manipulation and prone to create hard to detect bugs)
- Client decided RNG source if needed, but especially client maintained and manipulated if desired.
I am unfamiliar with the pymc3 code base and have only seen the 'seed' parameter used via np.random.seed in the few files I have searched, but it seemed like it could be generally made to support generators.
What are your thoughts on this?
Cheers,
Michael