Hi, Is there a way to uniquely spawn child seeds? I`m doing monte carlo analysis, where I have n random processes, each with their own generator. All process models instantiate a generator with default_rng(). I.e ss=SeedSequence() cs=ss.Spawn(n), and using cs[i] for process i. Now, the problem I`m facing, is that results using individual process depends on the order of the process initialization ,and the number of processes used. However, if I could spawn children with a unique identifier, I would be able to reproduce my individual results without having to pickle/log states. For example, all my models have an id (tuple) field which is hashable. If I had the ability to SeedSequence(x).Spawn([objects]) where objects support hash(object), I would have reproducibility for all my processes. I could do without the spawning, but then I would probably loose independence when I do multiproc? Is there a way to achieve my goal in the current version 1.21 of numpy?
Best Stig
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