cutest-loader.hpp

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#pragma once
 
#include <alpaqa/config/config.hpp>
#include <alpaqa/cutest-interface-export.h>
#include <alpaqa/problem/box-constr-problem.hpp>
#include <alpaqa/problem/sparsity.hpp>
#include <guanaqo/copyable-unique_ptr.hpp>
#include <guanaqo/dl-flags.hpp>
 
#include <iosfwd>
#include <string>
 
namespace alpaqa {
 
using guanaqo::DynamicLoadFlags;
 
/// Wrapper for CUTEst problems loaded from an external shared library.
///
/// @ingroup  grp_Problems
class CUTEST_INTERFACE_EXPORT CUTEstProblem
    : public BoxConstrProblem<alpaqa::EigenConfigd> {
  public:
    USING_ALPAQA_CONFIG(alpaqa::EigenConfigd);
 
    /// Load a CUTEst problem from the given shared library and OUTSDIF.d file.
    /// If @p so_fname points to a directory, `"PROBLEM.so"` is appended
    /// automatically. If @p outsdif_fname is `nullptr`, the same directory as
    /// @p so_fname is used.
    CUTEstProblem(const char *so_fname, const char *outsdif_fname = nullptr,
                  bool sparse = false, DynamicLoadFlags dl_flags = {});
    CUTEstProblem(const CUTEstProblem &);
    CUTEstProblem &operator=(const CUTEstProblem &);
    CUTEstProblem(CUTEstProblem &&) noexcept;
    CUTEstProblem &operator=(CUTEstProblem &&) noexcept;
    ~CUTEstProblem();
 
  public:
    /// The report generated by CUTEst.
    ///
    /// @see `man CUTEST_creport` and `man CUTEST_ureport`
    struct Report {
        /// Function call counters.
        ///
        /// @note   Note that hessian_times_vector, constraints and constraints_grad
        ///         may account for codes which allow the evaluation of a
        ///         selection of constraints only and may thus be much smaller
        ///         than the number of constraints times the number of
        ///         iterations.
        struct Calls {
            /// Number of calls to the objective function.
            unsigned objective = 0;
            /// Number of calls to the objective gradient.
            unsigned objective_grad = 0;
            /// Number of calls to the objective Hessian.
            unsigned objective_hess = 0;
            /// Number of Hessian times vector products.
            unsigned hessian_times_vector = 0;
            /// Number of calls to the constraint functions.
            unsigned constraints = 0;
            /// Number of calls to the constraint gradients.
            unsigned constraints_grad = 0;
            /// Number of calls to the constraint Hessians.
            unsigned constraints_hess = 0;
        };
        Calls calls; ///< Function call counters.
 
        /// CPU time (in seconds) for CUTEST_csetup.
        double time_setup = 0;
        /// CPU time (in seconds) since the end of CUTEST_csetup.
        double time = 0;
    };
 
    [[nodiscard]] Report get_report() const;
    std::ostream &format_report(std::ostream &os, const Report &r) const;
    std::ostream &format_report(std::ostream &os) const {
        return format_report(os, get_report());
    }
 
  public:
    std::string name = "<UNKNOWN>"; ///< Problem name
    vec x0;                         ///< Initial value of decision variables
    vec y0;                         ///< Initial value of Lagrange multipliers
 
  private:
    guanaqo::copyable_unique_ptr<class CUTEstLoader> impl;
    bool sparse       = false;
    mutable int nnz_H = -1;
    mutable int nnz_J = -1;
    struct SparseStorage {
        Eigen::VectorX<int> rows, cols;
    } mutable storage_jac_g, storage_hess_L;
 
  public:
    [[nodiscard]] real_t eval_objective(crvec x) const;
    void eval_objective_gradient(crvec x, rvec grad_fx) const;
    void eval_constraints(crvec x, rvec gx) const;
    void eval_constraints_gradient_product(crvec x, crvec y,
                                           rvec grad_gxy) const;
 
    void eval_constraints_jacobian(crvec x, rvec J_values) const;
    [[nodiscard]] Sparsity get_constraints_jacobian_sparsity() const;
    void eval_grad_gi(crvec x, index_t i, rvec grad_gi) const;
    void eval_lagrangian_hessian_product(crvec x, crvec y, real_t scale,
                                         crvec v, rvec Hv) const;
    void eval_lagrangian_hessian(crvec x, crvec y, real_t scale,
                                 rvec H_values) const;
    [[nodiscard]] Sparsity get_lagrangian_hessian_sparsity() const;
    void eval_augmented_lagrangian_hessian_product(crvec x, crvec y, crvec Σ,
                                                   real_t scale, crvec v,
                                                   rvec Hv) const;
    [[nodiscard]] real_t eval_objective_and_gradient(crvec x,
                                                     rvec grad_fx) const;
    [[nodiscard]] real_t eval_objective_and_constraints(crvec x, rvec g) const;
    void eval_lagrangian_gradient(crvec x, crvec y, rvec grad_L,
                                  rvec work_n) const;
    [[nodiscard]] std::string get_name() const { return name; }
};
 
} // namespace alpaqa