[Numpy-discussion] NEP: Random Number Generator Policy (original) (raw)

Robert Kern robert.kern at gmail.com
Sun Jun 10 20:57:24 EDT 2018

On Sun, Jun 10, 2018 at 5:47 PM Ralf Gommers <ralf.gommers at gmail.com> wrote:

_On Sun, Jun 3, 2018 at 9:23 PM, Warren Weckesser <_ warren.weckesser at gmail.com> wrote:

I suspect many of the tests will be easy to update, so fixing 300 or so tests does not seem like a monumental task. It's all not monumental, but it adds up quickly. In addition to changing tests, one will also need compatibility code when supporting multiple numpy versions (e.g. scipy when get a copy of RandomStable in scipy/_lib/_numpy_compat.py). A quick count of just np.random.seed occurrences with ``$ grep -roh --include *.py np.random.seed . | wc -w`` for some packages: numpy: 77 scipy: 462 matplotlib: 204 statsmodels: 461 pymc3: 36 scikit-image: 63 scikit-learn: 69 keras: 46 pytorch: 0 tensorflow: 368 astropy: 24 And note, these are not incorrect/broken usages, this is code that works and has done so for years.

Yes, some of them are incorrect and broken. Failure can be difficult to detect. This module from keras is particularly problematic:

https://github.com/keras-team/keras-preprocessing/blob/master/keras_preprocessing/image.py

Conclusion: the current proposal will cause work for the vast majority of libraries that depends on numpy. The total amount of that work will certainly not be counted in person-days/weeks, and more likely in years than months. So I'm not convinced yet that the current proposal is the best way forward.

The mere usage of np.random.seed() doesn't imply that these packages actually require stream-compatibility. Some might, for sure, like where they are used in the unit tests, but that's not what you counted. At best, these numbers just mean that we can't eliminate np.random.seed() in a new system right away.

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