Re: Add softplus implementation in scipy.special

+1 on adding `softplus()`.

I would not worry about reading StackOverflow in this case. Our general
rule of thumb is that the minimum copyrightable segment of code is about 10
lines. Everything about softplus is smaller than that. And we would not be
copying the code straight in, in any case. We'll want a ufunc, I think.

On Thu, Apr 13, 2023 at 5:17 AM Pamphile Roy <[email protected]> wrote:

> Hi Aadya,
>
> Thank you for sending the email. This is in reference to the issue:
> https://github.com/scipy/scipy/issues/17905
>
> Note that we cannot use code from StackOverflow due to licensing
> incompatibilities. See here for more details
> https://scipy.github.io/devdocs/dev/hacking.html#license-considerations
>
> Cheers,
> Pamphile
>
>
> On 13.04.2023, at 10:28, [email protected] wrote:
>
> Hello Everyone,
> It might be nice to have a numerically stable softplus implementation, ie
> np.log1p(np.exp(x))
>
> This implementation can be based on the following stackoverflow answers :
>
> https://cs.stackexchange.com/questions/110798/numerically-stable-log1pexp-calculation
>
> https://stackoverflow.com/questions/44230635/avoid-overflow-with-softplus-function-in-python
>
> It can have a good place in the scipy module as it has other applications
> apart from ML/AI like it's a quite natural penalty function in optimization
> if one desires a smooth penalty in some optimization problems.
>
> All opinions are welcome. Let's discuss this?
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-- 
Robert Kern

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