Default value of `Fminbox.mu0 = NaN` causing optimisation failures on v2.0.1.

[dcelisgarza]

Upgrading from v2.0.0 to v2.0.1 causes failures in previously working optimisations. I've taken to setting a finite value for mu0, but it appears the automatic tuning might be broken. I think it can be traced to PR #1232 . I've checked the initial values of the gradient and function and there's nothing egregious.

[pkofod]

Upgrading from v2.0.0 to v2.0.1 causes failures in previously working optimisations. I've taken to setting a finite value for mu0, but it appears the automatic tuning might be broken. I think it can be traced to PR #1232 . I've checked the initial values of the gradient and function and there's nothing egregious.

So are you saying that it worked prior to v2.0.0, at v2.0.0 but not in v2.0.1?

[dcelisgarza]

Correct. The optimisation is an entropy pooling problem where the problem is

Min_x f(x)
S.t.  Ax = b
      Dx <= e
      sum(x) = 1

Where matrix A and vector b have been normalised by the norm of A, matrix D and vector e normalised by the norm of D, and f is a kl divergence like function. There is nothing numerically dodgy in it.

[pkofod]

Is it possible to provide some more information? Can you for example give me x0 and the bounds?

[dcelisgarza]

Of course, though the optimisation is part of a larger system so I need a bit of time to break it down all the way to an MWE.

[pkofod]

Doesn't have to be a full MWE. If you can just print out the x0, lower, upper then I think I can figure it out

[dcelisgarza]

using LinearAlgebra, Optim

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B = [0.0314970394174356, 0.0028910475100436778]
wb = [-Inf Inf; -Inf Inf]
x0 = [0.0314970394174356, 0.0314970394174356]
w = fill(inv(size(A,2)), size(A,2))

G = similar(x0)
last_x = similar(x0)
grad = similar(G)
y = similar(w)
function common_op(x)
    if x != last_x
        copy!(last_x, x)
        y .= w .* exp.(-transpose(A) * x .- one(eltype(w)))
        grad .= B - A * y
    end
end
function f(x)
    common_op(x)
    return sum(y) + LinearAlgebra.dot(x, B)
end
function g!(G, x)
    common_op(x)
    G .= grad
    return G
end

res = Optim.optimize(f, g!, view(wb, :, 1), view(wb, :, 2), x0, Optim.Fminbox())

[pkofod]

thanks

[pkofod]

w is missing though

[dcelisgarza]

You're right it was an input parameter, it's simply

w = fill(inv(size(A,2)), size(A,2))

it's used at the end but for this it shouldn't matter

x = Optim.minimizer(result)
w .* exp.(-transpose(A) * x .- one(eltype(w)))

[pkofod]

Let me also post this

ulia> optimize(sum, [-Inf, 0.0], [Inf, 1.0], [0.5, 0.5])
┌ Warning: Terminated early due to NaN in gradient.
└ @ Optim ~/.julia/packages/Optim/mv9zc/src/multivariate/optimize/optimize.jl:136
 * Status: success

 * Candidate solution
    Final objective value:     0.000000e+00

 * Found with
    Algorithm:     Fminbox with L-BFGS

 * Convergence measures
    |x - x'|               = 0.00e+00 ≤ 0.0e+00
    |x - x'|/|x'|          = NaN ≰ 0.0e+00
    |f(x) - f(x')|         = 0.00e+00 ≤ 0.0e+00
    |f(x) - f(x')|/|f(x')| = NaN ≰ 0.0e+00
    |g(x)|                 = 1.00e+00 ≰ 1.0e-08

 * Work counters
    Seconds run:   0  (vs limit Inf)
    Iterations:    2
    f(x) calls:    47
    ∇f(x) calls:   47
    ∇f(x)ᵀv calls: 0

[pkofod]

You're right it was an input parameter, it's simply

opt is also not defined here

[dcelisgarza]

Ah shucks i should've run the mwe. I'll edit the original post, it's just a scaling constant which defaults to 1.

[dcelisgarza]

Ok i've tested it and it runs, I'm sorry and thanks for such a quick turnaround. Here's the stacktrace

ERROR: ArgumentError: Could not compute finite initial mu for Fminbox, got: NaN. Please provide a finite mu0 value.
Stacktrace:
 [1] initial_mu(box::Optim.BoxBarrier{…}, x::Vector{…}, g_x::Vector{…}, F::Fminbox{…})
   @ Optim ~/.julia/packages/Optim/DtV5C/src/multivariate/solvers/constrained/fminbox.jl:275
 [2] optimize(df::OnceDifferentiable{…}, l::SubArray{…}, u::SubArray{…}, x0::Vector{…}, F::Fminbox{…}, options::Optim.Options{…})
   @ Optim ~/.julia/packages/Optim/DtV5C/src/multivariate/solvers/constrained/fminbox.jl:494
 [3] optimize(f::Function, g::typeof(g!), l::SubArray{…}, u::SubArray{…}, x0::Vector{…}, F::Fminbox{…}, options::Optim.Options{…}; inplace::Bool)
   @ Optim ~/.julia/packages/Optim/DtV5C/src/multivariate/solvers/constrained/fminbox.jl:311
 [4] optimize(f::Function, g::Function, l::SubArray{…}, u::SubArray{…}, x0::Vector{…}, F::Fminbox{…}, options::Optim.Options{…})
   @ Optim ~/.julia/packages/Optim/DtV5C/src/multivariate/solvers/constrained/fminbox.jl:297
 [5] top-level scope
   @ /mnt/storage/dev/PortfolioOptimisers.jl/test/NOTRACK.jl:43
Some type information was truncated. Use `show(err)` to see complete types.

[pkofod]

Is this private code or a public repository I can see somewhere for the full example?

[dcelisgarza]

It's a registered package so you can dev it.

https://github.com/dcelisgarza/PortfolioOptimisers.jl/

Here are links to the failing tests:

https://github.com/dcelisgarza/PortfolioOptimisers.jl/blob/282a539784e2c409eaf7f626e34b15ed4aad2588/test/test_12_prior.jl#L378

https://github.com/dcelisgarza/PortfolioOptimisers.jl/blob/282a539784e2c409eaf7f626e34b15ed4aad2588/test/test_12_prior.jl#L700

Here are links to the erroring functions (i have two formulations, both error in the same way):

https://github.com/dcelisgarza/PortfolioOptimisers.jl/blob/282a539784e2c409eaf7f626e34b15ed4aad2588/src/13_Prior/10_EntropyPoolingPrior.jl#L1081

https://github.com/dcelisgarza/PortfolioOptimisers.jl/blob/282a539784e2c409eaf7f626e34b15ed4aad2588/src/13_Prior/10_EntropyPoolingPrior.jl#L1131