Julia flux simple multilayer perceptron to solve xor problem

xor_flux.jl

using Flux
using Plots

x = [0f0 0 1 1; 0 1 0 1]
y = [0f0 1 1 0]

xornn_model = Chain(
    Dense(2, 2, σ),
    Dense(2, 1, σ)
)


params(xornn_model)
params(xornn_model)[1]
params(xornn_model)[3]

loss_fn(x, y) = Flux.mse(xornn_model(x), y)
opt = ADAM(0.1)
n =  500

loss = zeros(500)
for i in 1:500
    Flux.train!(loss_fn, params(xornn_model), [(x, y)], opt)
    loss[i] = loss_fn(x, y)
    if i % 10 == 0
        println(loss[i])
    end
end

loss_fn(x, y)
xornn_model(x)

plot(1:n, loss, title="MSE vs Epochs of xor network")