Skip to content

Add keyword argument to change the quasi-Newton update in R2N #196

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Add keyword argument to change the quasi-Newton update in R2N #196

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
28 changes: 23 additions & 5 deletions src/R2N.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@ mutable struct R2NSolver{
xk::V
∇fk::V
∇fk⁻::V
y::V
mν∇fk::V
ψ::G
xkn::V
Expand Down Expand Up @@ -40,6 +41,7 @@ function R2NSolver(
xk = similar(x0)
∇fk = similar(x0)
∇fk⁻ = similar(x0)
y = similar(x0)
mν∇fk = similar(x0)
xkn = similar(x0)
s = similar(x0)
Expand Down Expand Up @@ -70,6 +72,7 @@ function R2NSolver(
xk,
∇fk,
∇fk⁻,
y,
mν∇fk,
ψ,
xkn,
Expand Down Expand Up @@ -154,6 +157,12 @@ Notably, you can access, and modify, the following:
- `stats.solver_specific[:nonsmooth_obj]`: current value of the nonsmooth part of the objective function;
- `stats.status`: current status of the algorithm. Should be `:unknown` unless the algorithm has attained a stopping criterion. Changing this to anything other than `:unknown` will stop the algorithm, but you should use `:user` to properly indicate the intention;
- `stats.elapsed_time`: elapsed time in seconds.
Similarly to the callback, when using a quasi-Newton approximation, two functions, `qn_update_y!(nlp, solver, stats)` and `qn_copy!(nlp, solver, stats)` are called at each update of the approximation.
Namely, the former computes the `y` vector for which the pair `(s, y)` is pushed into the approximation.
By default, `y := ∇fk⁻ - ∇fk`.
The latter allows the user to tell which values should be copied for the next iteration.
By default, only the gradient is copied: `∇fk⁻ .= ∇fk`.
This might be useful when using R2N in a constrained optimization context, when the gradient of the Lagrangian function is pushed at each iteration rather than the gradient of the objective function.
"""
function R2N(
nlp::AbstractNLPModel{T, V},
Expand Down Expand Up @@ -200,6 +209,8 @@ function SolverCore.solve!(
reg_nlp::AbstractRegularizedNLPModel{T, V},
stats::GenericExecutionStats{T, V};
callback = (args...) -> nothing,
qn_update_y!::Function = _qn_grad_update_y!,
qn_copy!::Function = _qn_grad_copy!,
x::V = reg_nlp.model.meta.x0,
atol::T = √eps(T),
rtol::T = √eps(T),
Expand Down Expand Up @@ -283,7 +294,7 @@ function SolverCore.solve!(

fk = obj(nlp, xk)
grad!(nlp, xk, ∇fk)
∇fk⁻ .= ∇fk
qn_copy!(nlp, solver, stats)

quasiNewtTest = isa(nlp, QuasiNewtonModel)
λmax::T = T(1)
Expand Down Expand Up @@ -414,15 +425,14 @@ function SolverCore.solve!(
grad!(nlp, xk, ∇fk)

if quasiNewtTest
@. ∇fk⁻ = ∇fk - ∇fk⁻
push!(nlp, s, ∇fk⁻)
qn_update_y!(nlp, solver, stats)
push!(nlp, s, solver.y)
qn_copy!(nlp, solver, stats)
end
solver.subpb.model.B = hess_op(nlp, xk)

λmax, found_λ = opnorm(solver.subpb.model.B)
found_λ || error("operator norm computation failed")

∇fk⁻ .= ∇fk
end

if η2 ≤ ρk < Inf
Expand Down Expand Up @@ -496,3 +506,11 @@ function SolverCore.solve!(
set_residuals!(stats, zero(eltype(xk)), sqrt_ξ1_νInv)
return stats
end

function _qn_grad_update_y!(nlp::AbstractNLPModel{T, V}, solver::R2NSolver{T, G, V}, stats::GenericExecutionStats) where{T, V, G}
@. solver.y = solver.∇fk - solver.∇fk⁻
end

function _qn_grad_copy!(nlp::AbstractNLPModel{T, V}, solver::R2NSolver{T, G, V}, stats::GenericExecutionStats) where{T, V, G}
solver.∇fk⁻ .= solver.∇fk
end
Loading