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Remove allocations in callbacks (#230)
* update interface between sparse KKT systems and callbacks * add PrimalVector type to store primal information - split slack from variable explicitly - remove all allocations in callbacks * fix tests * fix tests on GPU * address comments * typo fix * typo fix Co-authored-by: Sungho Shin <sshin@anl.gov>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,128 +1,137 @@ | ||
| function eval_f_wrapper(solver::MadNLPSolver, x::Vector{T}) where T | ||
| function eval_f_wrapper(solver::MadNLPSolver, x::PrimalVector{T}) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| @trace(solver.logger,"Evaluating objective.") | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| cnt.eval_function_time += @elapsed obj_val = (get_minimize(nlp) ? 1. : -1.) * obj(nlp,x_nlpmodel) | ||
| cnt.obj_cnt+=1 | ||
| cnt.obj_cnt==1 && (is_valid(obj_val) || throw(InvalidNumberException(:obj))) | ||
| return obj_val*solver.obj_scale[] | ||
| cnt.eval_function_time += @elapsed begin | ||
| sense = (get_minimize(nlp) ? one(T) : -one(T)) | ||
| obj_val = sense * obj(nlp, variable(x)) | ||
| end | ||
| cnt.obj_cnt += 1 | ||
| if cnt.obj_cnt == 1 && !is_valid(obj_val) | ||
| throw(InvalidNumberException(:obj)) | ||
| end | ||
| return obj_val * solver.obj_scale[] | ||
| end | ||
|
|
||
| function eval_grad_f_wrapper!(solver::MadNLPSolver, f::Vector{T},x::Vector{T}) where T | ||
| function eval_grad_f_wrapper!(solver::MadNLPSolver, f::PrimalVector{T}, x::PrimalVector{T}) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| @trace(solver.logger,"Evaluating objective gradient.") | ||
| obj_scaling = solver.obj_scale[] * (get_minimize(nlp) ? one(T) : -one(T)) | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| f_nlpmodel = _madnlp_unsafe_wrap(f, get_nvar(nlp)) | ||
| cnt.eval_function_time += @elapsed grad!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| f_nlpmodel | ||
| variable(x), | ||
| variable(f), | ||
| ) | ||
| _scal!(obj_scaling, f) | ||
| _scal!(obj_scaling, full(f)) | ||
| cnt.obj_grad_cnt+=1 | ||
| cnt.obj_grad_cnt==1 && (is_valid(f) || throw(InvalidNumberException(:grad))) | ||
| if cnt.obj_grad_cnt == 1 && !is_valid(full(f)) | ||
| throw(InvalidNumberException(:grad)) | ||
| end | ||
| return f | ||
| end | ||
|
|
||
| function eval_cons_wrapper!(solver::MadNLPSolver, c::Vector{T},x::Vector{T}) where T | ||
| function eval_cons_wrapper!(solver::MadNLPSolver, c::Vector{T}, x::PrimalVector{T}) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| @trace(solver.logger, "Evaluating constraints.") | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| c_nlpmodel = _madnlp_unsafe_wrap(c, get_ncon(nlp)) | ||
| cnt.eval_function_time += @elapsed cons!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| c_nlpmodel | ||
| variable(x), | ||
| c, | ||
| ) | ||
| view(c,solver.ind_ineq).-=view(x,get_nvar(nlp)+1:solver.n) | ||
| view(c,solver.ind_ineq) .-= slack(x) | ||
| c .-= solver.rhs | ||
| c .*= solver.con_scale | ||
| cnt.con_cnt+=1 | ||
| cnt.con_cnt==2 && (is_valid(c) || throw(InvalidNumberException(:cons))) | ||
| if cnt.con_cnt == 1 && !is_valid(c) | ||
| throw(InvalidNumberException(:cons)) | ||
| end | ||
| return c | ||
| end | ||
|
|
||
| function eval_jac_wrapper!(solver::MadNLPSolver, kkt::AbstractKKTSystem, x::Vector{T}) where T | ||
| function eval_jac_wrapper!(solver::MadNLPSolver, kkt::AbstractKKTSystem, x::PrimalVector{T}) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| ns = length(solver.ind_ineq) | ||
| @trace(solver.logger, "Evaluating constraint Jacobian.") | ||
| jac = get_jacobian(kkt) | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| jac_nlpmodel = _madnlp_unsafe_wrap(jac, get_nnzj(nlp.meta)) | ||
| cnt.eval_function_time += @elapsed jac_coord!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| jac_nlpmodel | ||
| variable(x), | ||
| jac, | ||
| ) | ||
| compress_jacobian!(kkt) | ||
| cnt.con_jac_cnt+=1 | ||
| cnt.con_jac_cnt==1 && (is_valid(jac) || throw(InvalidNumberException(:jac))) | ||
| cnt.con_jac_cnt += 1 | ||
| if cnt.con_jac_cnt == 1 && !is_valid(jac) | ||
| throw(InvalidNumberException(:jac)) | ||
| end | ||
| @trace(solver.logger,"Constraint jacobian evaluation started.") | ||
| return jac | ||
| end | ||
|
|
||
| function eval_lag_hess_wrapper!(solver::MadNLPSolver, kkt::AbstractKKTSystem, x::Vector{T},l::Vector{T};is_resto=false) where T | ||
| function eval_lag_hess_wrapper!(solver::MadNLPSolver, kkt::AbstractKKTSystem, x::PrimalVector{T},l::Vector{T};is_resto=false) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| @trace(solver.logger,"Evaluating Lagrangian Hessian.") | ||
| dual(solver._w1) .= l.*solver.con_scale | ||
| dual(solver._w1) .= l .* solver.con_scale | ||
| hess = get_hessian(kkt) | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| hess_nlpmodel = _madnlp_unsafe_wrap(hess, get_nnzh(nlp.meta)) | ||
| scale = (get_minimize(nlp) ? one(T) : -one(T)) | ||
| scale *= (is_resto ? zero(T) : solver.obj_scale[]) | ||
| cnt.eval_function_time += @elapsed hess_coord!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| variable(x), | ||
| dual(solver._w1), | ||
| hess_nlpmodel; | ||
| obj_weight = (get_minimize(nlp) ? 1. : -1.) * (is_resto ? 0.0 : solver.obj_scale[]) | ||
| hess; | ||
| obj_weight = scale, | ||
| ) | ||
| compress_hessian!(kkt) | ||
| cnt.lag_hess_cnt+=1 | ||
| cnt.lag_hess_cnt==1 && (is_valid(hess) || throw(InvalidNumberException(:hess))) | ||
| cnt.lag_hess_cnt += 1 | ||
| if cnt.lag_hess_cnt == 1 && !is_valid(hess) | ||
| throw(InvalidNumberException(:hess)) | ||
| end | ||
| return hess | ||
| end | ||
|
|
||
| function eval_jac_wrapper!(solver::MadNLPSolver, kkt::AbstractDenseKKTSystem, x::Vector{T}) where T | ||
| function eval_jac_wrapper!(solver::MadNLPSolver, kkt::AbstractDenseKKTSystem, x::PrimalVector{T}) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| ns = length(solver.ind_ineq) | ||
| @trace(solver.logger, "Evaluating constraint Jacobian.") | ||
| jac = get_jacobian(kkt) | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| cnt.eval_function_time += @elapsed jac_dense!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| jac | ||
| variable(x), | ||
| jac, | ||
| ) | ||
| compress_jacobian!(kkt) | ||
| cnt.con_jac_cnt+=1 | ||
| cnt.con_jac_cnt==1 && (is_valid(jac) || throw(InvalidNumberException(:jac))) | ||
| if cnt.con_jac_cnt == 1 && !is_valid(jac) | ||
| throw(InvalidNumberException(:jac)) | ||
| end | ||
| @trace(solver.logger,"Constraint jacobian evaluation started.") | ||
| return jac | ||
| end | ||
|
|
||
| function eval_lag_hess_wrapper!(solver::MadNLPSolver, kkt::AbstractDenseKKTSystem, x::Vector{T},l::Vector{T};is_resto=false) where T | ||
| function eval_lag_hess_wrapper!(solver::MadNLPSolver, kkt::AbstractDenseKKTSystem, x::PrimalVector{T},l::Vector{T};is_resto=false) where T | ||
| nlp = solver.nlp | ||
| cnt = solver.cnt | ||
| @trace(solver.logger,"Evaluating Lagrangian Hessian.") | ||
| dual(solver._w1) .= l.*solver.con_scale | ||
| dual(solver._w1) .= l .* solver.con_scale | ||
| hess = get_hessian(kkt) | ||
| x_nlpmodel = _madnlp_unsafe_wrap(x, get_nvar(nlp)) | ||
| scale = is_resto ? zero(T) : get_minimize(nlp) ? solver.obj_scale[] : -solver.obj_scale[] | ||
| cnt.eval_function_time += @elapsed hess_dense!( | ||
| nlp, | ||
| x_nlpmodel, | ||
| variable(x), | ||
| dual(solver._w1), | ||
| hess; | ||
| obj_weight = (get_minimize(nlp) ? 1. : -1.) * (is_resto ? 0.0 : solver.obj_scale[]) | ||
| obj_weight = scale, | ||
| ) | ||
| compress_hessian!(kkt) | ||
| cnt.lag_hess_cnt+=1 | ||
| cnt.lag_hess_cnt==1 && (is_valid(hess) || throw(InvalidNumberException(:hess))) | ||
| if cnt.lag_hess_cnt == 1 && !is_valid(hess) | ||
| throw(InvalidNumberException(:hess)) | ||
| end | ||
| return hess | ||
| end | ||
|
|
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