AlphaDropout(p; [rng, active])

A dropout layer. Used in Self-Normalizing Neural Networks . The AlphaDropout layer ensures that mean and variance of activations remain the same as before.

Does nothing to the input once testmode! is true.

Examples

			julia> using Statistics

julia> x = randn32(1000,1);

julia> m = Chain(Dense(1000 => 1000, selu), AlphaDropout(0.2));

julia> Flux.trainmode!(m);

julia> y = m(x);

julia> isapprox(std(x), std(y), atol=0.2)
true