This script causes a segfault, sometimes it as to be run twice to cause it. Julia v0.6.1

flux_juno_segfault.jl

using Flux
using Flux: back!, truncate!, treelike, train!, mse
N      = 200
n      = 2

function generate_data()
    A      = randn(n,n)
    A      = expm(A - A')
    A      = 0.999A
    A = [0.999 1; 0 0.8]
    x0     = randn(n)
    x      = zeros(n,N)
    x[:,1] = x0
    for i = 1:N-1
        if false #sum(x[:,i]) < 0
            x[:,i+1] = -A*x[:,i] + 0.01randn(n)
        else
            x[:,i+1] = A*x[:,i] + 0.01randn(n)
        end
    end

    y = x[:,2:end]
    x = x[:,1:end-1]
    x,y,A
end

function fit_model(m, loss, x, y, cb = () -> ())
    dataset = Iterators.repeated((x, y), 2000)
    function evalcallback()
        # @show(loss(x, y))
        # plot(y', ls = :dash, show=false, layout=n, size=(1500,600))
        # plot!(m(x).data', ls = :solid, show=true)
    end
    opt = ADAM(params(m), 0.01)
    train!(loss, dataset, opt, cb = cb)
    loss(x,y).data[1]
end

x,y,A = generate_data()
# x = param(x)
np = 17
m = Chain(
Dense(n,np,swish),
Dense(np,np,swish),
Dense(np,np,swish),
Dense(np,n)
)
loss = (x,y) -> Flux.mse(m(x), y)
# dataset = Iterators.repeated((x, y), 2000)
using IterTools
x = 0*x; y = sign.(y)
batch_size = 3
epochs = 5
# dataset = repeated(zip(partition(x,batch_size),partition(y,batch_size)), epochs)
dataset = zip(collect(partition(x,batch_size)),collect(partition(y,batch_size)))
for xi in dataset
    @show xi
end
opt = ADAM(params(m), 0.01)
train!(loss, dataset, opt)