using Flux
using CSV
using DataFrames
using Flux: throttle, @epochs

hidden = 4

m = Chain(
  Dense(6, hidden, σ),
  Dense(hidden, 2))

loss(x, y) = Flux.mse(m(x), y) # fonction de coût = mean squared error
ps = Flux.params(m)
opt = Descent(0.01)


d = CSV.read("dataset.csv", delim = ',')
deletecols!(d, :timestamp)

in = [ (convert(Vector,d[i,4:9])) for i in 1:size(d,1) ]
out = [ (convert(Vector,d[i,2:3])) for i in 1:size(d,1) ]
in = convert(Array{Array{Float64,1},1},in)
out = convert(Array{Array{Float64,1},1},out)

evalcb = () -> @show(loss(in, out))

train_data = zip(in,out)

print(first(train_data))

@epochs 3 Flux.train!(loss, ps, train_data, opt, cb = throttle(evalcb, 5))