alpaqa matlab
Nonconvex constrained optimization
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alpaqa-driver.cpp
Go to the documentation of this file.
1#ifdef _WIN32
2#define NOMINMAX
3#include <Windows.h>
4#endif
5
11#include <alpaqa-version.h>
12
13#include "fista-driver.hpp"
14#include "ipopt-driver.hpp"
15#include "lbfgsb-driver.hpp"
16#include "options.hpp"
17#include "panoc-driver.hpp"
18#include "pantr-driver.hpp"
19#include "qpalm-driver.hpp"
20#include "results.hpp"
21#include "solver-driver.hpp"
22
23#ifdef ALPAQA_HAVE_CASADI
24#include <casadi/config.h>
25#endif
26#ifdef ALPAQA_WITH_JSON
27#include <nlohmann/json_fwd.hpp>
28#endif
29#ifdef WITH_IPOPT
30#include <IpoptConfig.h>
31#endif
32
33#include <algorithm>
34#include <filesystem>
35#include <fstream>
36#include <iostream>
37#include <random>
38#include <span>
39#include <stdexcept>
40#include <string>
41#include <string_view>
42#include <tuple>
43#include <type_traits>
44namespace fs = std::filesystem;
45using namespace std::string_view_literals;
46
48
49const auto *docs = R"==(
50problem types:
51 dl: Dynamically loaded problem using the DLProblem class.
52 Specify the name of the registration function using the
53 problem.register option, e.g. problem.register=register_alpaqa_problem.
54 Further options can be passed to the problem using
55 problem.<key>[=<value>].
56 cs: Load a CasADi problem using the CasADiProblem class.
57 If a .tsv file with the same name as the shared library file exists,
58 the bounds and parameters will be loaded from that file. See
59 CasADiProblem::load_numerical_data for more details.
60 The problem parameter can be set using the problem.param option.
61 cu: Load a CUTEst problem using the CUTEstProblem class.
62
63methods:
64 panoc[.<direction>]:
65 PANOC solver with the given direction.
66 Directions include: lbfgs, struclbfgs, anderson.
67 zerofpr[.<direction>]:
68 ZeroFPR solver, supports the same directions as PANOC.
69 pantr:
70 PANTR solver. Requires products with the Hessian of the augmented
71 Lagrangian (unless dir.finite_diff=true).
72 fista:
73 FISTA (fast iterative shrinkage-thresholding algorithm). Only for
74 convex problems.
75 ipopt:
76 Ipopt interior point solver. Requires Jacobian of the constraints
77 and Hessian of the Lagrangian (unless finite memory is enabled).
78 qpalm:
79 QPALM proximal ALM QP solver. Assumes that the problem is a QP.
80 Requires Jacobian of the constraints and Hessian of the Lagrangian.
81
82options:
83 Solver-specific options can be specified as key-value pairs, where the
84 keys use periods to access struct members. For example,
85 solver.Lipschitz.L_0=1e3.
86
87 solver: Parameters for the main (inner) solver.
88 alm: Parameters for the outer ALM solver (if applicable).
89 dir: Parameters for solver's direction provider (if applicable).
90 accel: Parameters for direction's accelerator (if applicable).
91 out: File to write output to (default: -, i.e. standard output).
92 sol: Folder to write the solutions (and optional statistics) to.
93 x0: Initial guess for the solution.
94 mul_g0: Initial guess for the multipliers of the general constraints.
95 mul_x0: Initial guess for the multipliers of the bound constraints on x.
96 num_exp: Repeat the experiment this many times for more accurate timings.
97 extra_stats: Log more per-iteration solver statistics, such as step sizes,
98 Newton step acceptance, and residuals. Requires `sol' to be set.
99
100 The prefix @ can be added to the values of x0, mul_g0 and mul_x0 to read
101 the values from the given CSV file.
102
103 Options can be loaded from a JSON file by using an @ prefix. For example,
104 an argument @options.json loads the options from a file options.json in the
105 current directory. Multiple JSON files are processed in the order they
106 appear in the command line arguments. Options specified on the command line
107 always have precedence over options in a JSON file, regardless of order.
108
109examples:
110 alpaqa-driver problem.so \
111 problem.register=register_alpaqa_problem \
112 problem.custom_arg=foo \
113 method=panoc.struclbfgs \
114 accel.memory=50 \
115 alm.{tolerance,dual_tolerance}=1e-8 \
116 solver.print_interval=50 \
117 x0=@/some/file.csv
118
119 alpaqa-driver cs:build/casadi_problem.so \
120 @options/default.json \
121 problem.param=1,2,3 \
122 method=ipopt \
123 solver.tol=1e-8 solver.constr_viol_tol=1e-8 \
124 solver.warm_start_init_point=yes \
125 x0=@/some/file.csv \
126 mul_g0=@/some/other/file.csv \
127 mul_x0=@/yet/another/file.csv
128)==";
129
130void print_usage(const char *a0) {
131 const auto *opts = " [<problem-type>:][<path>/]<name> [method=<solver>] "
132 "[<key>=<value>...]\n";
133 std::cout << "alpaqa-driver " ALPAQA_VERSION_FULL " (" << alpaqa_build_time
134 << ")\n\n"
135 " Command-line interface to the alpaqa solvers.\n"
136 " alpaqa is published under the LGPL-3.0.\n"
137 " https://github.com/kul-optec/alpaqa"
138 "\n\n"
139 " Usage: "
140 << a0 << opts << docs << std::endl;
141 std::cout << "Third-party libraries:\n"
142 << " * Eigen " << EIGEN_WORLD_VERSION << '.'
143 << EIGEN_MAJOR_VERSION << '.' << EIGEN_MINOR_VERSION
144 << " (https://gitlab.com/libeigen/eigen) - MPL-2.0\n"
145#ifdef ALPAQA_HAVE_CASADI
146 << " * CasADi " CASADI_VERSION_STRING
147 " (https://github.com/casadi/casadi) - LGPL-3.0-or-later\n"
148#endif
149#ifdef ALPAQA_HAVE_CUTEST
150 << " * CUTEst"
151 " (https://github.com/ralna/CUTEst) - BSD-3-Clause\n"
152#endif
153#ifdef WITH_LBFGSB
154 << " * L-BFGS-B 3.0 "
155 "(http://users.iems.northwestern.edu/~nocedal/lbfgsb.html) - "
156 "BSD-3-Clause\n"
157#endif
158#ifdef WITH_IPOPT
159 << " * Ipopt " IPOPT_VERSION
160 " (https://github.com/coin-or/Ipopt) - EPL-2.0\n"
161 << " * MUMPS (https://mumps-solver.org) - CECILL-C\n"
162 << " * OpenBLAS (https://github.com/OpenMathLib/OpenBLAS) - "
163 "BSD-3-Clause\n"
164#endif
165#ifdef WITH_QPALM
166 << " * QPALM " QPALM_VERSION_STR
167 " (https://github.com/kul-optec/QPALM) - LGPL-3.0\n"
168#endif
169#ifdef ALPAQA_WITH_JSON
170 << " * nlohmann/json " << NLOHMANN_JSON_VERSION_MAJOR << '.'
171 << NLOHMANN_JSON_VERSION_MINOR << '.'
172 << NLOHMANN_JSON_VERSION_PATCH
173 << " (https://github.com/nlohmann/json) - MIT\n"
174#endif
175 << std::endl;
176}
177
179 std::cout << ALPAQA_VERSION_FULL " (" << ALPAQA_BUILD_TIME << ")\n";
180}
181
182/// Split the string @p s on the first occurrence of @p tok.
183/// Returns ("", s) if tok was not found.
184auto split_once(std::string_view s, char tok = '.') {
185 auto tok_pos = s.find(tok);
186 if (tok_pos == s.npos)
187 return std::make_tuple(std::string_view{}, s);
188 std::string_view key{s.begin(), s.begin() + tok_pos};
189 std::string_view rem{s.begin() + tok_pos + 1, s.end()};
190 return std::make_tuple(key, rem);
191}
192
193std::ostream &get_output_stream(Options &opts, std::ofstream &out_fstream) {
194 std::string out_path = "-";
195 set_params(out_path, "out", opts);
196 if (out_path != "-")
197 if (out_fstream.open(out_path); !out_fstream)
198 throw std::runtime_error("Unable to open '" + out_path + "'");
199 return out_fstream.is_open() ? out_fstream : std::cout;
200}
201
202std::string get_output_paths(Options &opts) {
203 std::string sol_path;
204 set_params(sol_path, "sol", opts);
205 return sol_path;
206}
207
208auto get_problem_path(const char *const *argv) {
209 bool rel_to_exe = argv[1][0] == '^';
210 std::string_view prob_path_s = argv[1] + static_cast<ptrdiff_t>(rel_to_exe);
211 std::string_view prob_type;
212 std::tie(prob_type, prob_path_s) = split_once(prob_path_s, ':');
213 fs::path prob_path{prob_path_s};
214 if (rel_to_exe)
215 prob_path = fs::canonical(fs::path(argv[0])).parent_path() / prob_path;
216 return std::make_tuple(std::move(prob_path), prob_type);
217}
218
219void print_problem_description(std::ostream &os, LoadedProblem &problem) {
220 os << "Loaded problem \"" << problem.name << "\"\n"
221 << "Number of variables: " << problem.problem.get_n() << "\n"
222 << "Number of constraints: " << problem.problem.get_m() << "\n";
223 if (problem.box_constr_count)
224 os << "Box constraints:"
225 << "\n Fixed variables: " << problem.box_constr_count->eq
226 << "\n Bilateral: " << problem.box_constr_count->lbub
227 << "\n Lower bound only: " << problem.box_constr_count->lb
228 << "\n Upper bound only: " << problem.box_constr_count->ub
229 << "\n";
230 if (problem.general_constr_count)
231 os << "General constraints:"
232 << "\n Equality: " << problem.general_constr_count->eq
233 << "\n Bilateral: " << problem.general_constr_count->lbub
234 << "\n Lower bound only: " << problem.general_constr_count->lb
235 << "\n Upper bound only: " << problem.general_constr_count->ub
236 << "\n";
237 os << "Provided functions:\n";
239}
240
242 std::string method = "panoc", direction;
243 set_params(method, "method", opts);
244 std::tie(method, direction) = alpaqa::params::split_key(method, '.');
245 // Dictionary of available solver builders
246 std::map<std::string_view, solver_builder_func> solvers{
247 {"panoc", make_panoc_driver}, {"zerofpr", make_zerofpr_driver},
248 {"pantr", make_pantr_driver}, {"lbfgsb", make_lbfgsb_driver},
249 {"fista", make_fista_driver}, {"ipopt", make_ipopt_driver},
250 {"qpalm", make_qpalm_driver},
251 };
252 // Find the selected solver builder
253 auto solver_it = solvers.find(method);
254 if (solver_it == solvers.end())
255 throw std::invalid_argument(
256 "Unknown solver '" + std::string(method) + "'\n" +
257 " Available solvers: " +
258 alpaqa::util::join(std::views::keys(solvers)));
259 ;
260 return std::make_tuple(std::move(solver_it->second), direction);
261}
262
263void store_solution(const fs::path &sol_output_dir, std::ostream &os,
264 BenchmarkResults &results, auto &solver,
265 std::span<const char *> argv) {
266 const auto &sol_res = results.solver_results;
267 auto timestamp_str = std::to_string(results.timestamp);
268 auto rnd_str = random_hex_string(std::random_device());
269 auto name = results.problem.path.stem().string();
270 if (name == "PROBLEM")
271 name = results.problem.name;
272 auto suffix = '_' + name + '_' + timestamp_str + '_' + rnd_str;
273 fs::create_directories(sol_output_dir);
274 std::array solutions{
275 std::tuple{"solution", "sol_x", &sol_res.solution},
276 std::tuple{"multipliers for g", "mul_g", &sol_res.multipliers},
277 std::tuple{"multipliers for x", "mul_x", &sol_res.multipliers_bounds},
278 };
279 for (auto [name, fname, value] : solutions) {
280 if (value->size() == 0)
281 continue;
282 auto pth = sol_output_dir / (std::string(fname) + suffix + ".csv");
283 os << "Writing " << name << " to " << pth << std::endl;
284 std::ofstream output_file(pth);
285 alpaqa::print_csv(output_file, *value);
286 }
287 {
288 auto pth = sol_output_dir / ("cmdline" + suffix + ".txt");
289 os << "Writing arguments to " << pth << std::endl;
290 std::ofstream output_file(pth);
291 for (const char *arg : argv)
292 output_file << std::quoted(arg, '\'') << ' ';
293 output_file << '\n';
294 }
295 if (solver->has_statistics()) {
296 auto pth = sol_output_dir / ("stats" + suffix + ".csv");
297 os << "Writing statistics to " << pth << std::endl;
298 std::ofstream output_file(pth);
299 solver->write_statistics_to_stream(output_file);
300 }
301}
302
303int main(int argc, const char *argv[]) try {
304#ifdef _WIN32
305 SetConsoleOutputCP(CP_UTF8);
306#endif
307 // Check command line options
308 if (argc < 1)
309 return -1;
310 if (argc == 1)
311 return print_usage(argv[0]), 0;
312 if (argc < 2)
313 return print_usage(argv[0]), -1;
314 if (argv[1] == "-h"sv || argv[1] == "--help"sv || argv[1] == "?"sv)
315 return print_usage(argv[0]), 0;
316 if (argv[1] == "-v"sv || argv[1] == "--version"sv)
317 return print_version(), 0;
318
319 std::span args{argv, static_cast<size_t>(argc)};
320 Options opts{argc - 2, argv + 2};
321
322 // Check where to write the output to
323 std::ofstream out_fstream;
324 std::ostream &os = get_output_stream(opts, out_fstream);
325
326 // Check which problem to load
327 auto [prob_path, prob_type] = get_problem_path(argv);
328
329 // Check which solver to use
330 auto [solver_builder, direction] = get_solver_builder(opts);
331
332 // Check output paths
333 fs::path sol_output_dir = get_output_paths(opts);
334
335 // Build solver
336 auto solver = solver_builder(direction, opts);
337
338 // Load problem
339 os << "Loading " << prob_path << " ..." << std::endl;
340 auto problem = load_problem(prob_type, prob_path.parent_path(),
341 prob_path.filename(), opts);
342 print_problem_description(os, problem);
343 os << std::endl;
344
345 // Check options
346 auto used = opts.used();
347 auto unused_opt = std::ranges::find(used, 0);
348 auto unused_idx = static_cast<size_t>(unused_opt - used.begin());
349 if (unused_opt != used.end())
350 throw std::invalid_argument("Unused option: " +
351 std::string(opts.options()[unused_idx]));
352
353 // Solve
354 auto solver_results = solver->run(problem, os);
355
356 // Compute more statistics
357 real_t f = problem.problem.eval_f(solver_results.solution);
358 auto kkt_err = alpaqa::compute_kkt_error(
359 problem.problem, solver_results.solution, solver_results.multipliers);
360 BenchmarkResults results{
361 .problem = problem,
362 .solver_results = solver_results,
363 .objective = f + solver_results.h,
364 .smooth_objective = f,
365 .error = kkt_err,
366 .options = opts.options(),
367 .timestamp = timestamp_ms<std::chrono::system_clock>().count(),
368 };
369
370 // Print results
371 print_results(os, results);
372
373 // Store solution
374 if (!sol_output_dir.empty())
375 store_solution(sol_output_dir, os, results, solver, args);
376
377} catch (std::exception &e) {
378 std::cerr << "Error: " << demangled_typename(typeid(e)) << ":\n "
379 << e.what() << std::endl;
380 return -1;
381}
auto get_solver_builder(Options &opts)
std::string get_output_paths(Options &opts)
const auto * docs
std::ostream & get_output_stream(Options &opts, std::ofstream &out_fstream)
void print_version()
auto get_problem_path(const char *const *argv)
void print_usage(const char *a0)
void store_solution(const fs::path &sol_output_dir, std::ostream &os, BenchmarkResults &results, auto &solver, std::span< const char * > argv)
void print_problem_description(std::ostream &os, LoadedProblem &problem)
auto split_once(std::string_view s, char tok='.')
Split the string s on the first occurrence of tok.
int main(int argc, const char *argv[])
length_t get_n() const
[Required] Number of decision variables.
length_t get_m() const
[Required] Number of constraints.
#define USING_ALPAQA_CONFIG(Conf)
Definition config.hpp:56
std::string demangled_typename(const std::type_info &t)
Get the pretty name of the given type as a string.
SharedSolverWrapper make_fista_driver(std::string_view direction, Options &opts)
void print_provided_functions(std::ostream &os, const TypeErasedProblem< Conf > &problem)
SharedSolverWrapper make_ipopt_driver(std::string_view, Options &)
SharedSolverWrapper make_lbfgsb_driver(std::string_view, Options &)
auto split_key(std::string_view full, char tok='.')
Split the string full on the first occurrence of tok.
Definition params.hpp:32
std::string join(std::ranges::input_range auto strings, join_opt opt={})
Join the list of strings into a single string, using the separator given by opt.
std::ostream & print_csv(std::ostream &os, const Eigen::DenseBase< Derived > &M, Args &&...args)
Definition print.hpp:67
KKTError< Conf > compute_kkt_error(const TypeErasedProblem< Conf > &problem, crvec< Conf > x, crvec< Conf > y)
Definition kkt-error.hpp:17
decltype(auto) set_params(T &t, std::string_view prefix, Options &opts)
Definition options.hpp:86
SharedSolverWrapper make_zerofpr_driver(std::string_view direction, Options &opts)
SharedSolverWrapper make_panoc_driver(std::string_view direction, Options &opts)
SharedSolverWrapper make_pantr_driver(std::string_view direction, Options &opts)
LoadedProblem load_problem(std::string_view type, const fs::path &dir, const fs::path &file, Options &opts)
Definition problem.cpp:183
std::optional< ConstrCount > general_constr_count
Definition problem.hpp:34
alpaqa::TypeErasedProblem< config_t > problem
Definition problem.hpp:25
std::string name
Definition problem.hpp:28
fs::path path
Definition problem.hpp:27
std::optional< ConstrCount > box_constr_count
Definition problem.hpp:33
SharedSolverWrapper make_qpalm_driver(std::string_view, Options &)
std::string random_hex_string(auto &&rng)
Definition results.hpp:53
void print_results(std::ostream &os, const BenchmarkResults &results)
Definition results.hpp:136
LoadedProblem & problem
Definition results.hpp:45
int64_t timestamp
Definition results.hpp:50
SolverResults solver_results
Definition results.hpp:46
Double-precision double configuration.
Definition config.hpp:135