Flux.jl/src/layers/stateless.jl
2019-02-08 21:49:53 +03:00

57 lines
1.7 KiB
Julia
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

using NNlib: logsoftmax, logσ
# Cost functions
mse(, y) = sum(( .- y).^2) * 1 // length(y)
function crossentropy(::AbstractVecOrMat, y::AbstractVecOrMat; weight = 1)
-sum(y .* log.() .* weight) * 1 // size(y, 2)
end
function logitcrossentropy(logŷ::AbstractVecOrMat, y::AbstractVecOrMat; weight = 1)
return -sum(y .* logsoftmax(logŷ) .* weight) * 1 // size(y, 2)
end
"""
binarycrossentropy(ŷ, y; ϵ=eps(ŷ))
Return `-y*log(ŷ + ϵ) - (1-y)*log(1-ŷ + ϵ)`. The ϵ term provides numerical stability.
julia> binarycrossentropy.(σ.([-1.1491, 0.8619, 0.3127]), [1, 1, 0.])
3-element Array{Float64,1}:
1.4244
0.352317
0.86167
"""
binarycrossentropy(, y; ϵ=eps()) = -y*log( + ϵ) - (1 - y)*log(1 - + ϵ)
"""
logitbinarycrossentropy(logŷ, y)
`logitbinarycrossentropy(logŷ, y)` is mathematically equivalent to `binarycrossentropy(σ(logŷ), y)`
but it is more numerically stable.
julia> logitbinarycrossentropy.([-1.1491, 0.8619, 0.3127], [1, 1, 0.])
3-element Array{Float64,1}:
1.4244
0.352317
0.86167
"""
logitbinarycrossentropy(logŷ, y) = (1 - y)*logŷ - logσ(logŷ)
"""
normalise(x::AbstractArray; dims=1)
Normalises x to mean 0 and standard deviation 1, across the dimensions given by dims. Defaults to normalising over columns.
"""
function normalise(x::AbstractArray; dims=1)
μ′ = mean(x, dims = dims)
σ = std(x, dims = dims, mean = μ′, corrected=false)
return (x .- μ′) ./ σ
end
function normalise(x::AbstractArray, dims=1)
Base.depwarn("`normalise(x::AbstractArray, dims)` is deprecated, use `normalise(a, dims=dims)` instead.", :normalise)
normalise(x, dims = dims)
end