log1pexp, #52 #70
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log1pexp, #52 #70
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Closed
cossio
commented
May 21, 2019
log1pexp, use float
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Looks good to me. |
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merge? |
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bump |
nalimilan
reviewed
Jun 7, 2020
| @@ -63,8 +63,8 @@ Return `log(1+exp(x))` evaluated carefully for largish `x`. | |||
| This is also called the ["softplus"](https://en.wikipedia.org/wiki/Rectifier_(neural_networks)) | |||
| transformation, being a smooth approximation to `max(0,x)`. Its inverse is [`logexpm1`](@ref). | |||
| """ | |||
| log1pexp(x::Real) = x < 18.0 ? log1p(exp(x)) : x < 33.3 ? x + exp(-x) : oftype(exp(-x), x) | |||
| log1pexp(x::Float32) = x < 9.0f0 ? log1p(exp(x)) : x < 16.0f0 ? x + exp(-x) : oftype(exp(-x), x) | |||
| log1pexp(x::Real) = x ≤ -37. ? exp(x) : x ≤ 18. ? log1p(exp(x)) : x ≤ 33.3 ? x + exp(-x) : float(x) | |||
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Why use ≤ here but < in the Float32 method?
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This was now moved to JuliaStats/LogExpFunctions.jl#37. But to answer your question, I only copied the algorithm described in https://cran.r-project.org/web/packages/Rmpfr/vignettes/log1mexp-note.pdf, which uses ≤ here.
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Should be moved to https://github.com/JuliaStats/LogExpFunctions.jl |
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#52
(replaces #57)