BatchExaModel

[amontoison]

cc @michel2323

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[amontoison]

@michel2323 Do you know how we can adapt the objective function to return a vector of nscenario instead of a scalar that is the sum of all objectives?
It is what we need for the new API of NLPModels.jl.

[michel2323]

Right. Forgot about the primal. How about the constraints?

I'll give it a try. Should be easy.

[amontoison]

For the constraints, we want to a strided API where the cosntraints of each scenarios are stored in the same vector.
It is like TwoStageExaModel and exactly what we do.

[michel2323]

For the objective, I've added the API below. This should be aligned with what be discussed back here.

    obj(model::TwoStageExaModel, x_global, s) → scalar

Evaluate the objective contribution of scenario s (for 1 ≤ s ≤ ns), or
the shared/design-only objective terms (for s = 0).

Per-scenario terms are Objective nodes whose iterator length is evenly divisible
by ns. Design-only terms (where length(itr) % ns != 0) are returned when s = 0.

The invariant obj(m, x) ≈ sum(obj(m, x, s) for s in 1:ns) + obj(m, x, 0) holds.

[michel2323]

We decided on a vectorized API obj(::BatchExaModel, x, result) where result is a vector of size ns.