agjn4.jl

leakyrelu(x;α=Float32(0.2)) = max(0,x) + α*min(0,x) # LeakyRelu activation
# A generic MLP forward prop function, original code: https://github.com/ekinakyurek/GAN-70-Lines-of-Julia/blob/66a60a6ea4532841ee647f08759ae9b1ace0c892/gan.jl#L6
function forward_prop(W,X;dropout_p=0.0)
    for i=1:2:length(W)
        X = W[i]*dropout(mat(X),dropout_p) .+ W[i+1] # mat(X) flattens X to an
        i < length(W)-1 && (X = leakyrelu.(X))
    end
    sigm.(X)
end
# Forward prop for the discriminator and generator respectively
D(w,x;dropout_p=0.0) = forward_prop(w,x;dropout_p=dropout_p)  #  Discriminator
G(w,z;dropout_p=0.0) = forward_prop(w,z;dropout_p=dropout_p)  #  Generator