logitbinarycrossentropy
function
defined in module
Flux.Losses
logitbinarycrossentropy(ŷ, y; agg = mean)
Mathematically equivalent to
binarycrossentropy(σ(ŷ), y)
but is more numerically stable.
See also:
crossentropy
,
logitcrossentropy
.
julia> y_bin = Bool[1,0,1];
julia> y_model = Float32[2, -1, pi]
3-element Vector{Float32}:
2.0
-1.0
3.1415927
julia> Flux.logitbinarycrossentropy(y_model, y_bin)
0.160832f0
julia> Flux.binarycrossentropy(sigmoid.(y_model), y_bin)
0.16083185f0
There is
1
method for Flux.Losses.logitbinarycrossentropy
:
The following pages link back here: