mirror of
https://github.com/Z3Prover/z3
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1594 lines
53 KiB
C++
1594 lines
53 KiB
C++
/*++
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Copyright (c) 2013 Microsoft Corporation
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Module Name:
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opt_context.cpp
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Abstract:
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Facility for running optimization problem.
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Author:
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Anh-Dung Phan (t-anphan) 2013-10-16
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Notes:
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--*/
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#include "opt_context.h"
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#include "ast_pp.h"
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#include "opt_solver.h"
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#include "opt_params.hpp"
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#include "for_each_expr.h"
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#include "goal.h"
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#include "tactic.h"
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#include "lia2card_tactic.h"
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#include "elim01_tactic.h"
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#include "solve_eqs_tactic.h"
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#include "simplify_tactic.h"
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#include "propagate_values_tactic.h"
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#include "solve_eqs_tactic.h"
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#include "elim_uncnstr_tactic.h"
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#include "tactical.h"
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#include "model_smt2_pp.h"
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#include "card2bv_tactic.h"
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#include "eq2bv_tactic.h"
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#include "dt2bv_tactic.h"
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#include "inc_sat_solver.h"
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#include "bv_decl_plugin.h"
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#include "pb_decl_plugin.h"
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#include "ast_smt_pp.h"
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#include "filter_model_converter.h"
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#include "ast_pp_util.h"
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#include "qsat.h"
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namespace opt {
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void context::scoped_state::push() {
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m_hard_lim.push_back(m_hard.size());
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m_objectives_lim.push_back(m_objectives.size());
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m_objectives_term_trail_lim.push_back(m_objectives_term_trail.size());
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}
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void context::scoped_state::pop() {
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m_hard.resize(m_hard_lim.back());
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unsigned k = m_objectives_term_trail_lim.back();
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while (m_objectives_term_trail.size() > k) {
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unsigned idx = m_objectives_term_trail.back();
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m_objectives[idx].m_terms.pop_back();
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m_objectives[idx].m_weights.pop_back();
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m_objectives_term_trail.pop_back();
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}
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m_objectives_term_trail_lim.pop_back();
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k = m_objectives_lim.back();
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while (m_objectives.size() > k) {
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objective& obj = m_objectives.back();
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if (obj.m_type == O_MAXSMT) {
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m_indices.erase(obj.m_id);
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}
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m_objectives.pop_back();
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}
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m_objectives_lim.pop_back();
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m_hard_lim.pop_back();
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}
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void context::scoped_state::add(expr* hard) {
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m_hard.push_back(hard);
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}
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bool context::scoped_state::set(ptr_vector<expr> & hard) {
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bool eq = hard.size() == m_hard.size();
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for (unsigned i = 0; eq && i < hard.size(); ++i) {
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eq = hard[i] == m_hard[i].get();
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}
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m_hard.reset();
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m_hard.append(hard.size(), hard.c_ptr());
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return !eq;
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}
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unsigned context::scoped_state::add(expr* f, rational const& w, symbol const& id) {
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if (!m.is_bool(f)) {
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throw default_exception("Soft constraint should be Boolean");
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}
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if (!m_indices.contains(id)) {
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m_objectives.push_back(objective(m, id));
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m_indices.insert(id, m_objectives.size() - 1);
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}
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SASSERT(m_indices.contains(id));
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unsigned idx = m_indices[id];
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if (!w.is_zero()) {
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m_objectives[idx].m_terms.push_back(f);
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m_objectives[idx].m_weights.push_back(w);
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m_objectives_term_trail.push_back(idx);
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}
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return idx;
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}
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unsigned context::scoped_state::add(app* t, bool is_max) {
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app_ref tr(t, m);
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if (!m_bv.is_bv(t) && !m_arith.is_int_real(t)) {
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throw default_exception("Objective must be bit-vector, integer or real");
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}
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unsigned index = m_objectives.size();
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m_objectives.push_back(objective(is_max, tr, index));
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return index;
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}
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context::context(ast_manager& m):
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m(m),
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m_arith(m),
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m_bv(m),
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m_hard_constraints(m),
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m_solver(0),
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m_box_index(UINT_MAX),
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m_optsmt(m),
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m_scoped_state(m),
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m_fm(m),
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m_objective_refs(m),
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m_enable_sat(false),
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m_is_clausal(false),
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m_pp_neat(false),
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m_unknown("unknown")
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{
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params_ref p;
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p.set_bool("model", true);
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p.set_bool("unsat_core", true);
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p.set_bool("elim_to_real", true);
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updt_params(p);
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}
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context::~context() {
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reset_maxsmts();
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}
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void context::reset_maxsmts() {
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map_t::iterator it = m_maxsmts.begin(), end = m_maxsmts.end();
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for (; it != end; ++it) {
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dealloc(it->m_value);
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}
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m_maxsmts.reset();
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}
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void context::push() {
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m_scoped_state.push();
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}
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void context::pop(unsigned n) {
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for (unsigned i = 0; i < n; ++i) {
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m_scoped_state.pop();
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}
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clear_state();
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reset_maxsmts();
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m_optsmt.reset();
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m_hard_constraints.reset();
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}
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void context::get_labels(svector<symbol> & r) {
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r.append(m_labels);
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}
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void context::get_unsat_core(ptr_vector<expr> & r) {
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throw default_exception("Unsat cores are not supported with optimization");
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}
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void context::set_hard_constraints(ptr_vector<expr>& fmls) {
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if (m_scoped_state.set(fmls)) {
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clear_state();
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}
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}
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void context::add_hard_constraint(expr* f) {
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m_scoped_state.add(f);
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clear_state();
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}
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void context::get_hard_constraints(expr_ref_vector& hard) {
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hard.append(m_scoped_state.m_hard);
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}
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expr_ref context::get_objective(unsigned i) {
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SASSERT(i < num_objectives());
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objective const& o = m_scoped_state.m_objectives[i];
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expr_ref result(m), zero(m);
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expr_ref_vector args(m);
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switch (o.m_type) {
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case O_MAXSMT:
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zero = m_arith.mk_numeral(rational(0), false);
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for (unsigned i = 0; i < o.m_terms.size(); ++i) {
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args.push_back(m.mk_ite(o.m_terms[i], zero, m_arith.mk_numeral(o.m_weights[i], false)));
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}
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result = m_arith.mk_add(args.size(), args.c_ptr());
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break;
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case O_MAXIMIZE:
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result = o.m_term;
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if (m_arith.is_arith_expr(result)) {
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result = m_arith.mk_uminus(result);
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}
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else if (m_bv.is_bv(result)) {
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result = m_bv.mk_bv_neg(result);
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}
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else {
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UNREACHABLE();
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}
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break;
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case O_MINIMIZE:
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result = o.m_term;
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break;
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}
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return result;
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}
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unsigned context::add_soft_constraint(expr* f, rational const& w, symbol const& id) {
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clear_state();
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return m_scoped_state.add(f, w, id);
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}
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unsigned context::add_objective(app* t, bool is_max) {
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clear_state();
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return m_scoped_state.add(t, is_max);
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}
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void context::import_scoped_state() {
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m_optsmt.reset();
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reset_maxsmts();
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m_objectives.reset();
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m_hard_constraints.reset();
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scoped_state& s = m_scoped_state;
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for (unsigned i = 0; i < s.m_objectives.size(); ++i) {
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objective& obj = s.m_objectives[i];
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m_objectives.push_back(obj);
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if (obj.m_type == O_MAXSMT) {
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add_maxsmt(obj.m_id, i);
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}
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}
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m_hard_constraints.append(s.m_hard);
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}
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lbool context::optimize() {
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if (m_pareto) {
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return execute_pareto();
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}
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if (m_box_index != UINT_MAX) {
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return execute_box();
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}
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clear_state();
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init_solver();
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import_scoped_state();
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normalize();
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internalize();
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update_solver();
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#if 0
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if (is_qsat_opt()) {
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return run_qsat_opt();
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}
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#endif
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solver& s = get_solver();
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s.assert_expr(m_hard_constraints);
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display_benchmark();
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IF_VERBOSE(1, verbose_stream() << "(optimize:check-sat)\n";);
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lbool is_sat = s.check_sat(0,0);
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TRACE("opt", tout << "initial search result: " << is_sat << "\n";
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s.display(tout););
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if (is_sat != l_false) {
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s.get_model(m_model);
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s.get_labels(m_labels);
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}
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if (is_sat != l_true) {
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TRACE("opt", tout << m_hard_constraints << "\n";);
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return is_sat;
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}
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IF_VERBOSE(1, verbose_stream() << "(optimize:sat)\n";);
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TRACE("opt", model_smt2_pp(tout, m, *m_model, 0););
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m_optsmt.setup(*m_opt_solver.get());
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update_lower();
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switch (m_objectives.size()) {
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case 0:
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break;
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case 1:
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is_sat = execute(m_objectives[0], true, false);
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break;
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default: {
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opt_params optp(m_params);
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symbol pri = optp.priority();
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if (pri == symbol("pareto")) {
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is_sat = execute_pareto();
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}
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else if (pri == symbol("box")) {
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is_sat = execute_box();
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}
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else {
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is_sat = execute_lex();
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}
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break;
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}
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}
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return adjust_unknown(is_sat);
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}
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lbool context::adjust_unknown(lbool r) {
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if (r == l_true && m_opt_solver.get() && m_opt_solver->was_unknown()) {
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r = l_undef;
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}
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return r;
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}
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bool context::print_model() const {
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opt_params optp(m_params);
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return optp.print_model();
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}
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void context::get_base_model(model_ref& mdl) {
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mdl = m_model;
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}
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void context::fix_model(model_ref& mdl) {
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if (mdl) {
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if (m_model_converter) {
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(*m_model_converter)(mdl, 0);
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}
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m_fm(mdl, 0);
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}
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}
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void context::get_model(model_ref& mdl) {
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mdl = m_model;
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fix_model(mdl);
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}
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void context::get_box_model(model_ref& mdl, unsigned index) {
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if (index >= m_box_models.size()) {
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throw default_exception("index into models is out of bounds");
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}
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mdl = m_box_models[index];
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fix_model(mdl);
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}
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lbool context::execute_min_max(unsigned index, bool committed, bool scoped, bool is_max) {
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if (scoped) get_solver().push();
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lbool result = m_optsmt.lex(index, is_max);
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if (result == l_true) m_optsmt.get_model(m_model, m_labels);
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if (scoped) get_solver().pop(1);
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if (result == l_true && committed) m_optsmt.commit_assignment(index);
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return result;
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}
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lbool context::execute_maxsat(symbol const& id, bool committed, bool scoped) {
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model_ref tmp;
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maxsmt& ms = *m_maxsmts.find(id);
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if (scoped) get_solver().push();
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lbool result = ms();
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if (result != l_false && (ms.get_model(tmp, m_labels), tmp.get())) {
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ms.get_model(m_model, m_labels);
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}
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if (scoped) get_solver().pop(1);
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if (result == l_true && committed) ms.commit_assignment();
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DEBUG_CODE(if (result == l_true) validate_maxsat(id););
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return result;
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}
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lbool context::execute(objective const& obj, bool committed, bool scoped) {
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switch(obj.m_type) {
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case O_MAXIMIZE: return execute_min_max(obj.m_index, committed, scoped, true);
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case O_MINIMIZE: return execute_min_max(obj.m_index, committed, scoped, false);
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case O_MAXSMT: return execute_maxsat(obj.m_id, committed, scoped);
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default: UNREACHABLE(); return l_undef;
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}
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}
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/**
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\brief there is no need to use push/pop when all objectives are maxsat and engine
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is maxres.
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*/
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bool context::scoped_lex() {
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if (m_maxsat_engine == symbol("maxres")) {
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for (unsigned i = 0; i < m_objectives.size(); ++i) {
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if (m_objectives[i].m_type != O_MAXSMT) return true;
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}
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return false;
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}
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return true;
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}
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lbool context::execute_lex() {
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lbool r = l_true;
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bool sc = scoped_lex();
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IF_VERBOSE(1, verbose_stream() << "(optsmt:lex)\n";);
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for (unsigned i = 0; r == l_true && i < m_objectives.size(); ++i) {
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bool is_last = i + 1 == m_objectives.size();
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r = execute(m_objectives[i], i + 1 < m_objectives.size(), sc && !is_last);
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if (r == l_true && !get_lower_as_num(i).is_finite()) {
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return r;
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}
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if (r == l_true && i + 1 < m_objectives.size()) {
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update_lower();
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}
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}
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DEBUG_CODE(if (r == l_true) validate_lex(););
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return r;
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}
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lbool context::execute_box() {
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if (m_box_index < m_box_models.size()) {
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m_model = m_box_models[m_box_index];
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++m_box_index;
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return l_true;
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}
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if (m_box_index < m_objectives.size()) {
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m_model = 0;
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++m_box_index;
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return l_undef;
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}
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if (m_box_index != UINT_MAX && m_box_index >= m_objectives.size()) {
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m_box_index = UINT_MAX;
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return l_false;
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}
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m_box_index = 1;
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m_box_models.reset();
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lbool r = m_optsmt.box();
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for (unsigned i = 0, j = 0; r == l_true && i < m_objectives.size(); ++i) {
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objective const& obj = m_objectives[i];
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if (obj.m_type == O_MAXSMT) {
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solver::scoped_push _sp(get_solver());
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r = execute(obj, false, false);
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m_box_models.push_back(m_model.get());
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}
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else {
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m_box_models.push_back(m_optsmt.get_model(j));
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++j;
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}
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}
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if (r == l_true && m_box_models.size() > 0) {
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m_model = m_box_models[0];
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}
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return r;
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}
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expr_ref context::mk_le(unsigned i, model_ref& mdl) {
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objective const& obj = m_objectives[i];
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return mk_cmp(false, mdl, obj);
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}
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expr_ref context::mk_ge(unsigned i, model_ref& mdl) {
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objective const& obj = m_objectives[i];
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return mk_cmp(true, mdl, obj);
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}
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expr_ref context::mk_gt(unsigned i, model_ref& mdl) {
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expr_ref result = mk_le(i, mdl);
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result = mk_not(m, result);
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return result;
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}
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expr_ref context::mk_cmp(bool is_ge, model_ref& mdl, objective const& obj) {
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rational k(0);
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expr_ref val(m), result(m);
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switch (obj.m_type) {
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case O_MINIMIZE:
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is_ge = !is_ge;
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case O_MAXIMIZE:
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if (mdl->eval(obj.m_term, val) && is_numeral(val, k)) {
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if (is_ge) {
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result = mk_ge(obj.m_term, val);
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}
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else {
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result = mk_ge(val, obj.m_term);
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}
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}
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else {
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result = m.mk_true();
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}
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break;
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case O_MAXSMT: {
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pb_util pb(m);
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unsigned sz = obj.m_terms.size();
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ptr_vector<expr> terms;
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vector<rational> coeffs;
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for (unsigned i = 0; i < sz; ++i) {
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terms.push_back(obj.m_terms[i]);
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coeffs.push_back(obj.m_weights[i]);
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if (mdl->eval(obj.m_terms[i], val) && m.is_true(val)) {
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k += obj.m_weights[i];
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}
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}
|
|
if (is_ge) {
|
|
result = pb.mk_ge(sz, coeffs.c_ptr(), terms.c_ptr(), k);
|
|
}
|
|
else {
|
|
result = pb.mk_le(sz, coeffs.c_ptr(), terms.c_ptr(), k);
|
|
}
|
|
break;
|
|
}
|
|
}
|
|
TRACE("opt",
|
|
tout << (is_ge?">= ":"<= ") << k << "\n";
|
|
display_objective(tout, obj);
|
|
tout << "\n";
|
|
tout << result << "\n";);
|
|
return result;
|
|
}
|
|
|
|
expr_ref context::mk_ge(expr* t, expr* s) {
|
|
expr_ref result(m);
|
|
if (m_bv.is_bv(t)) {
|
|
result = m_bv.mk_ule(s, t);
|
|
}
|
|
else {
|
|
result = m_arith.mk_ge(t, s);
|
|
}
|
|
return result;
|
|
}
|
|
|
|
void context::yield() {
|
|
m_pareto->get_model(m_model, m_labels);
|
|
update_bound(true);
|
|
update_bound(false);
|
|
}
|
|
|
|
lbool context::execute_pareto() {
|
|
if (!m_pareto) {
|
|
set_pareto(alloc(gia_pareto, m, *this, m_solver.get(), m_params));
|
|
}
|
|
lbool is_sat = (*(m_pareto.get()))();
|
|
if (is_sat != l_true) {
|
|
set_pareto(0);
|
|
}
|
|
if (is_sat == l_true) {
|
|
yield();
|
|
}
|
|
return is_sat;
|
|
}
|
|
|
|
std::string context::reason_unknown() const {
|
|
if (m.canceled()) {
|
|
return Z3_CANCELED_MSG;
|
|
}
|
|
if (m_solver.get()) {
|
|
return m_solver->reason_unknown();
|
|
}
|
|
return m_unknown;
|
|
}
|
|
|
|
void context::display_bounds(std::ostream& out, bounds_t const& b) const {
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective const& obj = m_objectives[i];
|
|
display_objective(out, obj);
|
|
if (obj.m_type == O_MAXIMIZE) {
|
|
out << " |-> [" << b[i].first << ":" << b[i].second << "]\n";
|
|
}
|
|
else {
|
|
out << " |-> [" << -b[i].second << ":" << -b[i].first << "]\n";
|
|
}
|
|
}
|
|
}
|
|
|
|
solver& context::get_solver() {
|
|
return *m_solver.get();
|
|
}
|
|
|
|
void context::init_solver() {
|
|
setup_arith_solver();
|
|
m_opt_solver = alloc(opt_solver, m, m_params, m_fm);
|
|
m_opt_solver->set_logic(m_logic);
|
|
m_solver = m_opt_solver.get();
|
|
m_opt_solver->ensure_pb();
|
|
|
|
//if (opt_params(m_params).priority() == symbol("pareto") ||
|
|
// (opt_params(m_params).priority() == symbol("lex") && m_objectives.size() > 1)) {
|
|
//}
|
|
}
|
|
|
|
void context::setup_arith_solver() {
|
|
opt_params p(m_params);
|
|
if (p.optsmt_engine() == symbol("symba") ||
|
|
p.optsmt_engine() == symbol("farkas")) {
|
|
std::stringstream strm;
|
|
strm << AS_OPTINF;
|
|
gparams::set("smt.arith.solver", strm.str().c_str());
|
|
}
|
|
}
|
|
|
|
void context::update_solver() {
|
|
if (!m_enable_sat || !probe_bv()) {
|
|
return;
|
|
}
|
|
if (m_maxsat_engine != symbol("maxres") &&
|
|
m_maxsat_engine != symbol("pd-maxres") &&
|
|
m_maxsat_engine != symbol("bcd2") &&
|
|
m_maxsat_engine != symbol("sls")) {
|
|
return;
|
|
}
|
|
if (opt_params(m_params).priority() == symbol("pareto")) {
|
|
return;
|
|
}
|
|
if (m.proofs_enabled()) {
|
|
return;
|
|
}
|
|
m_params.set_bool("minimize_core_partial", true);
|
|
m_params.set_bool("minimize_core", true);
|
|
m_sat_solver = mk_inc_sat_solver(m, m_params);
|
|
expr_ref_vector fmls(m);
|
|
get_solver().get_assertions(fmls);
|
|
m_sat_solver->assert_expr(fmls);
|
|
m_solver = m_sat_solver.get();
|
|
}
|
|
|
|
void context::enable_sls(bool force) {
|
|
if ((force || m_enable_sls) && m_sat_solver.get()) {
|
|
m_params.set_bool("optimize_model", true);
|
|
m_sat_solver->updt_params(m_params);
|
|
}
|
|
}
|
|
|
|
struct context::is_bv {
|
|
struct found {};
|
|
ast_manager& m;
|
|
pb_util pb;
|
|
bv_util bv;
|
|
is_bv(ast_manager& m): m(m), pb(m), bv(m) {}
|
|
void operator()(var *) { throw found(); }
|
|
void operator()(quantifier *) { throw found(); }
|
|
void operator()(app *n) {
|
|
family_id fid = n->get_family_id();
|
|
if (fid != m.get_basic_family_id() &&
|
|
fid != pb.get_family_id() &&
|
|
fid != bv.get_family_id() &&
|
|
!is_uninterp_const(n)) {
|
|
throw found();
|
|
}
|
|
}
|
|
};
|
|
|
|
bool context::probe_bv() {
|
|
expr_fast_mark1 visited;
|
|
is_bv proc(m);
|
|
try {
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective & obj = m_objectives[i];
|
|
if (obj.m_type != O_MAXSMT) return false;
|
|
maxsmt& ms = *m_maxsmts.find(obj.m_id);
|
|
for (unsigned j = 0; j < ms.size(); ++j) {
|
|
quick_for_each_expr(proc, visited, ms[j]);
|
|
}
|
|
}
|
|
unsigned sz = get_solver().get_num_assertions();
|
|
for (unsigned i = 0; i < sz; i++) {
|
|
quick_for_each_expr(proc, visited, get_solver().get_assertion(i));
|
|
}
|
|
for (unsigned i = 0; i < m_hard_constraints.size(); ++i) {
|
|
quick_for_each_expr(proc, visited, m_hard_constraints[i].get());
|
|
}
|
|
}
|
|
catch (is_bv::found) {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
struct context::is_propositional_fn {
|
|
struct found {};
|
|
ast_manager& m;
|
|
is_propositional_fn(ast_manager& m): m(m) {}
|
|
void operator()(var *) { throw found(); }
|
|
void operator()(quantifier *) { throw found(); }
|
|
void operator()(app *n) {
|
|
family_id fid = n->get_family_id();
|
|
if (fid != m.get_basic_family_id() &&
|
|
!is_uninterp_const(n)) {
|
|
throw found();
|
|
}
|
|
}
|
|
};
|
|
|
|
bool context::is_propositional(expr* p) {
|
|
expr* np;
|
|
if (is_uninterp_const(p) || (m.is_not(p, np) && is_uninterp_const(np))) {
|
|
return true;
|
|
}
|
|
is_propositional_fn proc(m);
|
|
expr_fast_mark1 visited;
|
|
try {
|
|
quick_for_each_expr(proc, visited, p);
|
|
}
|
|
catch (is_propositional_fn::found) {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
|
|
void context::add_maxsmt(symbol const& id, unsigned index) {
|
|
maxsmt* ms = alloc(maxsmt, *this, index);
|
|
ms->updt_params(m_params);
|
|
m_maxsmts.insert(id, ms);
|
|
}
|
|
|
|
bool context::is_numeral(expr* e, rational & n) const {
|
|
unsigned sz;
|
|
return m_arith.is_numeral(e, n) || m_bv.is_numeral(e, n, sz);
|
|
}
|
|
|
|
void context::normalize() {
|
|
expr_ref_vector fmls(m);
|
|
to_fmls(fmls);
|
|
simplify_fmls(fmls);
|
|
from_fmls(fmls);
|
|
}
|
|
|
|
void context::simplify_fmls(expr_ref_vector& fmls) {
|
|
if (m_is_clausal) {
|
|
return;
|
|
}
|
|
|
|
goal_ref g(alloc(goal, m, true, false));
|
|
for (unsigned i = 0; i < fmls.size(); ++i) {
|
|
g->assert_expr(fmls[i].get());
|
|
}
|
|
tactic_ref tac0 =
|
|
and_then(mk_simplify_tactic(m, m_params),
|
|
mk_propagate_values_tactic(m),
|
|
mk_solve_eqs_tactic(m),
|
|
// NB: mk_elim_uncstr_tactic(m) is not sound with soft constraints
|
|
mk_simplify_tactic(m));
|
|
opt_params optp(m_params);
|
|
tactic_ref tac1, tac2, tac3, tac4;
|
|
if (optp.elim_01()) {
|
|
tac1 = mk_dt2bv_tactic(m);
|
|
tac2 = mk_elim01_tactic(m);
|
|
tac3 = mk_lia2card_tactic(m);
|
|
tac4 = mk_eq2bv_tactic(m);
|
|
params_ref lia_p;
|
|
lia_p.set_bool("compile_equality", optp.pb_compile_equality());
|
|
tac3->updt_params(lia_p);
|
|
set_simplify(and_then(tac0.get(), tac1.get(), tac2.get(), tac3.get(), tac4.get(), mk_simplify_tactic(m)));
|
|
}
|
|
else {
|
|
set_simplify(tac0.get());
|
|
}
|
|
proof_converter_ref pc;
|
|
expr_dependency_ref core(m);
|
|
goal_ref_buffer result;
|
|
(*m_simplify)(g, result, m_model_converter, pc, core);
|
|
SASSERT(result.size() == 1);
|
|
goal* r = result[0];
|
|
fmls.reset();
|
|
expr_ref tmp(m);
|
|
for (unsigned i = 0; i < r->size(); ++i) {
|
|
fmls.push_back(r->form(i));
|
|
}
|
|
}
|
|
|
|
bool context::is_maximize(expr* fml, app_ref& term, expr_ref& orig_term, unsigned& index) {
|
|
if (is_app(fml) && m_objective_fns.find(to_app(fml)->get_decl(), index) &&
|
|
m_objectives[index].m_type == O_MAXIMIZE) {
|
|
term = to_app(to_app(fml)->get_arg(0));
|
|
orig_term = m_objective_orig.find(to_app(fml)->get_decl());
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
bool context::is_minimize(expr* fml, app_ref& term, expr_ref& orig_term, unsigned& index) {
|
|
if (is_app(fml) && m_objective_fns.find(to_app(fml)->get_decl(), index) &&
|
|
m_objectives[index].m_type == O_MINIMIZE) {
|
|
term = to_app(to_app(fml)->get_arg(0));
|
|
orig_term = m_objective_orig.find(to_app(fml)->get_decl());
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
bool context::is_maxsat(expr* fml, expr_ref_vector& terms,
|
|
vector<rational>& weights, rational& offset,
|
|
bool& neg, symbol& id, expr_ref& orig_term, unsigned& index) {
|
|
if (!is_app(fml)) return false;
|
|
neg = false;
|
|
app* a = to_app(fml);
|
|
if (m_objective_fns.find(a->get_decl(), index) && m_objectives[index].m_type == O_MAXSMT) {
|
|
for (unsigned i = 0; i < a->get_num_args(); ++i) {
|
|
expr_ref arg(a->get_arg(i), m);
|
|
rational weight = m_objectives[index].m_weights[i];
|
|
if (weight.is_neg()) {
|
|
weight.neg();
|
|
arg = mk_not(m, arg);
|
|
offset -= weight;
|
|
}
|
|
if (m.is_true(arg)) {
|
|
IF_VERBOSE(1, verbose_stream() << weight << ": " << mk_pp(m_objectives[index].m_terms[i].get(), m) << " |-> true\n";);
|
|
}
|
|
else if (weight.is_zero()) {
|
|
// skip
|
|
}
|
|
else if (m.is_false(arg)) {
|
|
IF_VERBOSE(1, verbose_stream() << weight << ": " << mk_pp(m_objectives[index].m_terms[i].get(), m) << " |-> false\n";);
|
|
offset += weight;
|
|
}
|
|
else {
|
|
terms.push_back(arg);
|
|
weights.push_back(weight);
|
|
}
|
|
}
|
|
id = m_objectives[index].m_id;
|
|
return true;
|
|
}
|
|
app_ref term(m);
|
|
offset = rational::zero();
|
|
bool is_max = is_maximize(fml, term, orig_term, index);
|
|
bool is_min = !is_max && is_minimize(fml, term, orig_term, index);
|
|
if (is_min && get_pb_sum(term, terms, weights, offset)) {
|
|
TRACE("opt", tout << "try to convert minimization" << mk_pp(term, m) << "\n";);
|
|
// minimize 2*x + 3*y
|
|
// <=>
|
|
// (assert-soft (not x) 2)
|
|
// (assert-soft (not y) 3)
|
|
//
|
|
for (unsigned i = 0; i < weights.size(); ++i) {
|
|
if (weights[i].is_neg()) {
|
|
offset += weights[i];
|
|
weights[i].neg();
|
|
}
|
|
else {
|
|
terms[i] = mk_not(m, terms[i].get());
|
|
}
|
|
}
|
|
TRACE("opt",
|
|
tout << "Convert minimization " << orig_term << "\n";
|
|
tout << "to maxsat: " << term << "\n";
|
|
for (unsigned i = 0; i < weights.size(); ++i) {
|
|
tout << mk_pp(terms[i].get(), m) << ": " << weights[i] << "\n";
|
|
}
|
|
tout << "offset: " << offset << "\n";
|
|
);
|
|
std::ostringstream out;
|
|
out << orig_term << ":" << index;
|
|
id = symbol(out.str().c_str());
|
|
return true;
|
|
}
|
|
if (is_max && get_pb_sum(term, terms, weights, offset)) {
|
|
TRACE("opt", tout << "try to convert maximization" << mk_pp(term, m) << "\n";);
|
|
// maximize 2*x + 3*y - z
|
|
// <=>
|
|
// (assert-soft x 2)
|
|
// (assert-soft y 3)
|
|
// (assert-soft (not z) 1)
|
|
// offset := 6
|
|
// maximize = offset - penalty
|
|
//
|
|
for (unsigned i = 0; i < weights.size(); ++i) {
|
|
if (weights[i].is_neg()) {
|
|
weights[i].neg();
|
|
terms[i] = mk_not(m, terms[i].get());
|
|
}
|
|
offset += weights[i];
|
|
}
|
|
neg = true;
|
|
std::ostringstream out;
|
|
out << orig_term << ":" << index;
|
|
id = symbol(out.str().c_str());
|
|
return true;
|
|
}
|
|
if ((is_max || is_min) && m_bv.is_bv(term)) {
|
|
offset.reset();
|
|
unsigned bv_size = m_bv.get_bv_size(term);
|
|
expr_ref val(m);
|
|
val = m_bv.mk_numeral(is_max, 1);
|
|
for (unsigned i = 0; i < bv_size; ++i) {
|
|
rational w = power(rational(2),i);
|
|
weights.push_back(w);
|
|
terms.push_back(m.mk_eq(val, m_bv.mk_extract(i, i, term)));
|
|
if (is_max) {
|
|
offset += w;
|
|
}
|
|
}
|
|
neg = is_max;
|
|
std::ostringstream out;
|
|
out << orig_term << ":" << index;
|
|
id = symbol(out.str().c_str());
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
expr* context::mk_objective_fn(unsigned index, objective_t ty, unsigned sz, expr*const* args) {
|
|
ptr_vector<sort> domain;
|
|
for (unsigned i = 0; i < sz; ++i) {
|
|
domain.push_back(m.get_sort(args[i]));
|
|
}
|
|
char const* name = "";
|
|
switch(ty) {
|
|
case O_MAXIMIZE: name = "maximize"; break;
|
|
case O_MINIMIZE: name = "minimize"; break;
|
|
case O_MAXSMT: name = "maxsat"; break;
|
|
default: break;
|
|
}
|
|
func_decl* f = m.mk_fresh_func_decl(name,"", domain.size(), domain.c_ptr(), m.mk_bool_sort());
|
|
m_objective_fns.insert(f, index);
|
|
m_objective_refs.push_back(f);
|
|
m_objective_orig.insert(f, sz > 0 ? args[0] : 0);
|
|
return m.mk_app(f, sz, args);
|
|
}
|
|
|
|
expr* context::mk_maximize(unsigned index, app* t) {
|
|
expr* t_ = t;
|
|
return mk_objective_fn(index, O_MAXIMIZE, 1, &t_);
|
|
}
|
|
|
|
expr* context::mk_minimize(unsigned index, app* t) {
|
|
expr* t_ = t;
|
|
return mk_objective_fn(index, O_MINIMIZE, 1, &t_);
|
|
}
|
|
|
|
expr* context::mk_maxsat(unsigned index, unsigned num_fmls, expr* const* fmls) {
|
|
return mk_objective_fn(index, O_MAXSMT, num_fmls, fmls);
|
|
}
|
|
|
|
void context::from_fmls(expr_ref_vector const& fmls) {
|
|
TRACE("opt", tout << fmls << "\n";);
|
|
m_hard_constraints.reset();
|
|
expr_ref orig_term(m);
|
|
for (unsigned i = 0; i < fmls.size(); ++i) {
|
|
expr* fml = fmls[i];
|
|
app_ref tr(m);
|
|
expr_ref_vector terms(m);
|
|
vector<rational> weights;
|
|
rational offset(0);
|
|
unsigned index;
|
|
symbol id;
|
|
bool neg;
|
|
if (is_maxsat(fml, terms, weights, offset, neg, id, orig_term, index)) {
|
|
objective& obj = m_objectives[index];
|
|
|
|
if (obj.m_type != O_MAXSMT) {
|
|
// change from maximize/minimize.
|
|
obj.m_id = id;
|
|
obj.m_type = O_MAXSMT;
|
|
SASSERT(!m_maxsmts.contains(id));
|
|
add_maxsmt(id, index);
|
|
}
|
|
mk_atomic(terms);
|
|
SASSERT(obj.m_id == id);
|
|
obj.m_term = orig_term?to_app(orig_term):0;
|
|
obj.m_terms.reset();
|
|
obj.m_terms.append(terms);
|
|
obj.m_weights.reset();
|
|
obj.m_weights.append(weights);
|
|
obj.m_adjust_value.set_offset(offset);
|
|
obj.m_adjust_value.set_negate(neg);
|
|
m_maxsmts.find(id)->set_adjust_value(obj.m_adjust_value);
|
|
TRACE("opt", tout << "maxsat: " << id << " offset:" << offset << "\n";
|
|
tout << terms << "\n";);
|
|
}
|
|
else if (is_maximize(fml, tr, orig_term, index)) {
|
|
purify(tr);
|
|
m_objectives[index].m_term = tr;
|
|
}
|
|
else if (is_minimize(fml, tr, orig_term, index)) {
|
|
purify(tr);
|
|
m_objectives[index].m_term = tr;
|
|
m_objectives[index].m_adjust_value.set_negate(true);
|
|
}
|
|
else {
|
|
m_hard_constraints.push_back(fml);
|
|
}
|
|
}
|
|
// fix types of objectives:
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective & obj = m_objectives[i];
|
|
expr* t = obj.m_term;
|
|
switch(obj.m_type) {
|
|
case O_MINIMIZE:
|
|
case O_MAXIMIZE:
|
|
if (!m_arith.is_int(t) && !m_arith.is_real(t)) {
|
|
obj.m_term = m_arith.mk_numeral(rational(0), true);
|
|
}
|
|
break;
|
|
default:
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
bool context::verify_model(unsigned index, model* md, rational const& _v) {
|
|
rational r;
|
|
app_ref term = m_objectives[index].m_term;
|
|
if (!term) {
|
|
return true;
|
|
}
|
|
rational v = m_objectives[index].m_adjust_value(_v);
|
|
expr_ref val(m);
|
|
model_ref mdl = md;
|
|
fix_model(mdl);
|
|
|
|
if (!mdl->eval(term, val)) {
|
|
TRACE("opt", tout << "Term does not evaluate " << term << "\n";);
|
|
return false;
|
|
}
|
|
unsigned bvsz;
|
|
if (!m_arith.is_numeral(val, r) && !m_bv.is_numeral(val, r, bvsz)) {
|
|
TRACE("opt", tout << "model does not evaluate objective to a value\n";);
|
|
return false;
|
|
}
|
|
if (r != v) {
|
|
TRACE("opt", tout << "Out of bounds: " << term << " " << val << " != " << v << "\n";);
|
|
return false;
|
|
}
|
|
else {
|
|
TRACE("opt", tout << "validated: " << term << " = " << val << "\n";);
|
|
}
|
|
return true;
|
|
}
|
|
|
|
void context::purify(app_ref& term) {
|
|
filter_model_converter_ref fm;
|
|
if (m_arith.is_add(term)) {
|
|
expr_ref_vector args(m);
|
|
unsigned sz = term->get_num_args();
|
|
for (unsigned i = 0; i < sz; ++i) {
|
|
expr* arg = term->get_arg(i);
|
|
if (is_mul_const(arg)) {
|
|
args.push_back(arg);
|
|
}
|
|
else {
|
|
args.push_back(purify(fm, arg));
|
|
}
|
|
}
|
|
term = m_arith.mk_add(args.size(), args.c_ptr());
|
|
}
|
|
else if (m_arith.is_arith_expr(term) && !is_mul_const(term)) {
|
|
TRACE("opt", tout << "Purifying " << term << "\n";);
|
|
term = purify(fm, term);
|
|
}
|
|
else if (m.is_ite(term)) {
|
|
TRACE("opt", tout << "Purifying " << term << "\n";);
|
|
term = purify(fm, term);
|
|
}
|
|
if (fm) {
|
|
m_model_converter = concat(m_model_converter.get(), fm.get());
|
|
}
|
|
}
|
|
|
|
bool context::is_mul_const(expr* e) {
|
|
expr* e1, *e2;
|
|
return
|
|
is_uninterp_const(e) ||
|
|
m_arith.is_numeral(e) ||
|
|
(m_arith.is_mul(e, e1, e2) && m_arith.is_numeral(e1) && is_uninterp_const(e2)) ||
|
|
(m_arith.is_mul(e, e2, e1) && m_arith.is_numeral(e1) && is_uninterp_const(e2));
|
|
}
|
|
|
|
app* context::purify(filter_model_converter_ref& fm, expr* term) {
|
|
std::ostringstream out;
|
|
out << mk_pp(term, m);
|
|
app* q = m.mk_fresh_const(out.str().c_str(), m.get_sort(term));
|
|
if (!fm) fm = alloc(filter_model_converter, m);
|
|
m_hard_constraints.push_back(m.mk_eq(q, term));
|
|
fm->insert(q->get_decl());
|
|
return q;
|
|
}
|
|
|
|
/**
|
|
To select the proper theory solver we have to ensure that all theory
|
|
symbols from soft constraints are reflected in the hard constraints.
|
|
|
|
- filter "obj" from generated model.
|
|
*/
|
|
void context::mk_atomic(expr_ref_vector& terms) {
|
|
filter_model_converter_ref fm;
|
|
for (unsigned i = 0; i < terms.size(); ++i) {
|
|
expr_ref p(terms[i].get(), m);
|
|
app_ref q(m);
|
|
if (is_propositional(p)) {
|
|
terms[i] = p;
|
|
}
|
|
else {
|
|
terms[i] = purify(fm, p);
|
|
}
|
|
}
|
|
if (fm) {
|
|
m_model_converter = concat(m_model_converter.get(), fm.get());
|
|
}
|
|
}
|
|
|
|
void context::to_fmls(expr_ref_vector& fmls) {
|
|
m_objective_fns.reset();
|
|
fmls.append(m_hard_constraints);
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective const& obj = m_objectives[i];
|
|
switch(obj.m_type) {
|
|
case O_MINIMIZE:
|
|
fmls.push_back(mk_minimize(i, obj.m_term));
|
|
break;
|
|
case O_MAXIMIZE:
|
|
fmls.push_back(mk_maximize(i, obj.m_term));
|
|
break;
|
|
case O_MAXSMT:
|
|
fmls.push_back(mk_maxsat(i, obj.m_terms.size(), obj.m_terms.c_ptr()));
|
|
break;
|
|
}
|
|
}
|
|
TRACE("opt", tout << fmls << "\n";);
|
|
}
|
|
|
|
void context::internalize() {
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective & obj = m_objectives[i];
|
|
switch(obj.m_type) {
|
|
case O_MINIMIZE: {
|
|
app_ref tmp(m);
|
|
tmp = obj.m_term;
|
|
if (m_arith.is_int(tmp) || m_arith.is_real(tmp)) {
|
|
tmp = m_arith.mk_uminus(obj.m_term);
|
|
}
|
|
obj.m_index = m_optsmt.add(tmp);
|
|
break;
|
|
}
|
|
case O_MAXIMIZE:
|
|
obj.m_index = m_optsmt.add(obj.m_term);
|
|
break;
|
|
case O_MAXSMT: {
|
|
maxsmt& ms = *m_maxsmts.find(obj.m_id);
|
|
for (unsigned j = 0; j < obj.m_terms.size(); ++j) {
|
|
ms.add(obj.m_terms[j].get(), obj.m_weights[j]);
|
|
}
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void context::update_bound(bool is_lower) {
|
|
expr_ref val(m);
|
|
if (!m_model.get()) return;
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective const& obj = m_objectives[i];
|
|
rational r;
|
|
switch(obj.m_type) {
|
|
case O_MINIMIZE: {
|
|
bool evaluated = m_model->eval(obj.m_term, val);
|
|
TRACE("opt", tout << obj.m_term << " " << val << " " << evaluated << " " << is_numeral(val, r) << "\n";);
|
|
if (evaluated && is_numeral(val, r)) {
|
|
inf_eps val = inf_eps(obj.m_adjust_value(r));
|
|
TRACE("opt", tout << "adjusted value: " << val << "\n";);
|
|
if (is_lower) {
|
|
m_optsmt.update_lower(obj.m_index, val);
|
|
}
|
|
else {
|
|
m_optsmt.update_upper(obj.m_index, val);
|
|
}
|
|
}
|
|
break;
|
|
}
|
|
case O_MAXIMIZE: {
|
|
bool evaluated = m_model->eval(obj.m_term, val);
|
|
TRACE("opt", tout << obj.m_term << " " << val << "\n";);
|
|
if (evaluated && is_numeral(val, r)) {
|
|
inf_eps val = inf_eps(obj.m_adjust_value(r));
|
|
TRACE("opt", tout << "adjusted value: " << val << "\n";);
|
|
if (is_lower) {
|
|
m_optsmt.update_lower(obj.m_index, val);
|
|
}
|
|
else {
|
|
m_optsmt.update_upper(obj.m_index, val);
|
|
}
|
|
}
|
|
break;
|
|
}
|
|
case O_MAXSMT: {
|
|
bool ok = true;
|
|
for (unsigned j = 0; ok && j < obj.m_terms.size(); ++j) {
|
|
bool evaluated = m_model->eval(obj.m_terms[j], val);
|
|
TRACE("opt", tout << mk_pp(obj.m_terms[j], m) << " " << val << "\n";);
|
|
if (evaluated) {
|
|
if (!m.is_true(val)) {
|
|
r += obj.m_weights[j];
|
|
}
|
|
}
|
|
else {
|
|
ok = false;
|
|
}
|
|
}
|
|
if (ok) {
|
|
maxsmt& ms = *m_maxsmts.find(obj.m_id);
|
|
if (is_lower) {
|
|
ms.update_upper(r);
|
|
TRACE("opt", tout << r << " " << ms.get_upper() << "\n";);
|
|
}
|
|
else {
|
|
ms.update_lower(r);
|
|
TRACE("opt", tout << r << " " << ms.get_lower() << "\n";);
|
|
}
|
|
}
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void context::display_benchmark() {
|
|
if (opt_params(m_params).dump_benchmarks() &&
|
|
sat_enabled() &&
|
|
m_objectives.size() == 1 &&
|
|
m_objectives[0].m_type == O_MAXSMT
|
|
) {
|
|
objective& o = m_objectives[0];
|
|
unsigned sz = o.m_terms.size();
|
|
inc_sat_display(verbose_stream(), get_solver(), sz, o.m_terms.c_ptr(), o.m_weights.c_ptr());
|
|
}
|
|
}
|
|
|
|
void context::display(std::ostream& out) {
|
|
display_assignment(out);
|
|
}
|
|
|
|
void context::display_assignment(std::ostream& out) {
|
|
out << "(objectives\n";
|
|
for (unsigned i = 0; i < m_scoped_state.m_objectives.size(); ++i) {
|
|
objective const& obj = m_scoped_state.m_objectives[i];
|
|
out << " (";
|
|
display_objective(out, obj);
|
|
if (get_lower_as_num(i) != get_upper_as_num(i)) {
|
|
out << " (" << get_lower(i) << " " << get_upper(i) << ")";
|
|
}
|
|
else {
|
|
out << " " << get_lower(i);
|
|
}
|
|
out << ")\n";
|
|
}
|
|
out << ")\n";
|
|
}
|
|
|
|
void context::display_objective(std::ostream& out, objective const& obj) const {
|
|
switch(obj.m_type) {
|
|
case O_MAXSMT: {
|
|
symbol s = obj.m_id;
|
|
if (s != symbol::null) {
|
|
out << s;
|
|
}
|
|
break;
|
|
}
|
|
default:
|
|
out << obj.m_term;
|
|
break;
|
|
}
|
|
}
|
|
|
|
inf_eps context::get_lower_as_num(unsigned idx) {
|
|
if (idx >= m_objectives.size()) {
|
|
throw default_exception("index out of bounds");
|
|
}
|
|
objective const& obj = m_objectives[idx];
|
|
switch(obj.m_type) {
|
|
case O_MAXSMT:
|
|
return inf_eps(m_maxsmts.find(obj.m_id)->get_lower());
|
|
case O_MINIMIZE:
|
|
return obj.m_adjust_value(m_optsmt.get_upper(obj.m_index));
|
|
case O_MAXIMIZE:
|
|
return obj.m_adjust_value(m_optsmt.get_lower(obj.m_index));
|
|
default:
|
|
UNREACHABLE();
|
|
return inf_eps();
|
|
}
|
|
}
|
|
|
|
inf_eps context::get_upper_as_num(unsigned idx) {
|
|
if (idx >= m_objectives.size()) {
|
|
throw default_exception("index out of bounds");
|
|
}
|
|
objective const& obj = m_objectives[idx];
|
|
switch(obj.m_type) {
|
|
case O_MAXSMT:
|
|
return inf_eps(m_maxsmts.find(obj.m_id)->get_upper());
|
|
case O_MINIMIZE:
|
|
return obj.m_adjust_value(m_optsmt.get_lower(obj.m_index));
|
|
case O_MAXIMIZE:
|
|
return obj.m_adjust_value(m_optsmt.get_upper(obj.m_index));
|
|
default:
|
|
UNREACHABLE();
|
|
return inf_eps();
|
|
}
|
|
}
|
|
|
|
expr_ref context::get_lower(unsigned idx) {
|
|
return to_expr(get_lower_as_num(idx));
|
|
}
|
|
|
|
expr_ref context::get_upper(unsigned idx) {
|
|
return to_expr(get_upper_as_num(idx));
|
|
}
|
|
|
|
void context::to_exprs(inf_eps const& n, expr_ref_vector& es) {
|
|
rational inf = n.get_infinity();
|
|
rational r = n.get_rational();
|
|
rational eps = n.get_infinitesimal();
|
|
es.push_back(m_arith.mk_numeral(inf, inf.is_int()));
|
|
es.push_back(m_arith.mk_numeral(r, r.is_int()));
|
|
es.push_back(m_arith.mk_numeral(eps, eps.is_int()));
|
|
}
|
|
|
|
expr_ref context::to_expr(inf_eps const& n) {
|
|
rational inf = n.get_infinity();
|
|
rational r = n.get_rational();
|
|
rational eps = n.get_infinitesimal();
|
|
expr_ref_vector args(m);
|
|
if (!inf.is_zero()) {
|
|
expr* oo = m.mk_const(symbol("oo"), m_arith.mk_int());
|
|
if (inf.is_one()) {
|
|
args.push_back(oo);
|
|
}
|
|
else {
|
|
args.push_back(m_arith.mk_mul(m_arith.mk_numeral(inf, inf.is_int()), oo));
|
|
}
|
|
}
|
|
if (!r.is_zero()) {
|
|
args.push_back(m_arith.mk_numeral(r, r.is_int()));
|
|
}
|
|
if (!eps.is_zero()) {
|
|
expr* ep = m.mk_const(symbol("epsilon"), m_arith.mk_real());
|
|
if (eps.is_one()) {
|
|
args.push_back(ep);
|
|
}
|
|
else {
|
|
args.push_back(m_arith.mk_mul(m_arith.mk_numeral(eps, eps.is_int()), ep));
|
|
}
|
|
}
|
|
switch(args.size()) {
|
|
case 0: return expr_ref(m_arith.mk_numeral(rational(0), true), m);
|
|
case 1: return expr_ref(args[0].get(), m);
|
|
default: return expr_ref(m_arith.mk_add(args.size(), args.c_ptr()), m);
|
|
}
|
|
}
|
|
|
|
void context::set_simplify(tactic* tac) {
|
|
m_simplify = tac;
|
|
}
|
|
|
|
void context::clear_state() {
|
|
set_pareto(0);
|
|
m_box_index = UINT_MAX;
|
|
m_model.reset();
|
|
}
|
|
|
|
void context::set_pareto(pareto_base* p) {
|
|
m_pareto = p;
|
|
}
|
|
|
|
void context::collect_statistics(statistics& stats) const {
|
|
if (m_solver) {
|
|
m_solver->collect_statistics(stats);
|
|
}
|
|
if (m_simplify) {
|
|
m_simplify->collect_statistics(stats);
|
|
}
|
|
map_t::iterator it = m_maxsmts.begin(), end = m_maxsmts.end();
|
|
for (; it != end; ++it) {
|
|
it->m_value->collect_statistics(stats);
|
|
}
|
|
get_memory_statistics(stats);
|
|
get_rlimit_statistics(m.limit(), stats);
|
|
if (m_qmax) {
|
|
m_qmax->collect_statistics(stats);
|
|
}
|
|
}
|
|
|
|
void context::collect_param_descrs(param_descrs & r) {
|
|
opt_params::collect_param_descrs(r);
|
|
}
|
|
|
|
void context::updt_params(params_ref const& p) {
|
|
m_params.append(p);
|
|
if (m_solver) {
|
|
m_solver->updt_params(m_params);
|
|
}
|
|
m_optsmt.updt_params(m_params);
|
|
map_t::iterator it = m_maxsmts.begin(), end = m_maxsmts.end();
|
|
for (; it != end; ++it) {
|
|
it->m_value->updt_params(m_params);
|
|
}
|
|
opt_params _p(p);
|
|
m_enable_sat = _p.enable_sat();
|
|
m_enable_sls = _p.enable_sls();
|
|
m_maxsat_engine = _p.maxsat_engine();
|
|
m_pp_neat = _p.pp_neat();
|
|
}
|
|
|
|
std::string context::to_string() const {
|
|
return to_string(m_scoped_state.m_hard, m_scoped_state.m_objectives);
|
|
}
|
|
|
|
std::string context::to_string_internal() const {
|
|
return to_string(m_hard_constraints, m_objectives);
|
|
}
|
|
|
|
std::string context::to_string(expr_ref_vector const& hard, vector<objective> const& objectives) const {
|
|
smt2_pp_environment_dbg env(m);
|
|
ast_pp_util visitor(m);
|
|
std::ostringstream out;
|
|
visitor.collect(hard);
|
|
|
|
for (unsigned i = 0; i < objectives.size(); ++i) {
|
|
objective const& obj = objectives[i];
|
|
switch(obj.m_type) {
|
|
case O_MAXIMIZE:
|
|
case O_MINIMIZE:
|
|
visitor.collect(obj.m_term);
|
|
break;
|
|
case O_MAXSMT:
|
|
visitor.collect(obj.m_terms);
|
|
break;
|
|
default:
|
|
UNREACHABLE();
|
|
break;
|
|
}
|
|
}
|
|
|
|
visitor.display_decls(out);
|
|
visitor.display_asserts(out, hard, m_pp_neat);
|
|
for (unsigned i = 0; i < objectives.size(); ++i) {
|
|
objective const& obj = objectives[i];
|
|
switch(obj.m_type) {
|
|
case O_MAXIMIZE:
|
|
out << "(maximize ";
|
|
ast_smt2_pp(out, obj.m_term, env);
|
|
out << ")\n";
|
|
break;
|
|
case O_MINIMIZE:
|
|
out << "(minimize ";
|
|
ast_smt2_pp(out, obj.m_term, env);
|
|
out << ")\n";
|
|
break;
|
|
case O_MAXSMT:
|
|
for (unsigned j = 0; j < obj.m_terms.size(); ++j) {
|
|
out << "(assert-soft ";
|
|
ast_smt2_pp(out, obj.m_terms[j], env);
|
|
rational w = obj.m_weights[j];
|
|
|
|
w.display_decimal(out << " :weight ", 3, true);
|
|
if (obj.m_id != symbol::null) {
|
|
if (is_smt2_quoted_symbol(obj.m_id)) {
|
|
out << " :id " << mk_smt2_quoted_symbol(obj.m_id);
|
|
}
|
|
else {
|
|
out << " :id " << obj.m_id;
|
|
}
|
|
}
|
|
out << ")\n";
|
|
}
|
|
break;
|
|
default:
|
|
UNREACHABLE();
|
|
break;
|
|
}
|
|
}
|
|
|
|
param_descrs descrs;
|
|
collect_param_descrs(descrs);
|
|
m_params.display_smt2(out, "opt", descrs);
|
|
|
|
out << "(check-sat)\n";
|
|
return out.str();
|
|
}
|
|
|
|
void context::validate_maxsat(symbol const& id) {
|
|
maxsmt& ms = *m_maxsmts.find(id);
|
|
TRACE("opt", tout << "Validate: " << id << "\n";);
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective const& obj = m_objectives[i];
|
|
if (obj.m_id == id && obj.m_type == O_MAXSMT) {
|
|
SASSERT(obj.m_type == O_MAXSMT);
|
|
rational value(0);
|
|
expr_ref val(m);
|
|
for (unsigned i = 0; i < obj.m_terms.size(); ++i) {
|
|
bool evaluated = m_model->eval(obj.m_terms[i], val);
|
|
SASSERT(evaluated);
|
|
CTRACE("opt", evaluated && !m.is_true(val) && !m.is_false(val), tout << mk_pp(obj.m_terms[i], m) << " " << val << "\n";);
|
|
CTRACE("opt", !evaluated, tout << mk_pp(obj.m_terms[i], m) << "\n";);
|
|
if (evaluated && !m.is_true(val)) {
|
|
value += obj.m_weights[i];
|
|
}
|
|
// TBD: check that optimal was not changed.
|
|
}
|
|
value = obj.m_adjust_value(value);
|
|
rational value0 = ms.get_lower();
|
|
TRACE("opt", tout << "value " << value << " " << value0 << "\n";);
|
|
SASSERT(value == value0);
|
|
}
|
|
}
|
|
}
|
|
|
|
void context::validate_lex() {
|
|
rational r1;
|
|
expr_ref val(m);
|
|
for (unsigned i = 0; i < m_objectives.size(); ++i) {
|
|
objective const& obj = m_objectives[i];
|
|
switch(obj.m_type) {
|
|
case O_MINIMIZE:
|
|
case O_MAXIMIZE: {
|
|
inf_eps n = m_optsmt.get_lower(obj.m_index);
|
|
if (m_optsmt.objective_is_model_valid(obj.m_index) &&
|
|
n.get_infinity().is_zero() &&
|
|
n.get_infinitesimal().is_zero() &&
|
|
m_model->eval(obj.m_term, val) &&
|
|
is_numeral(val, r1)) {
|
|
rational r2 = n.get_rational();
|
|
if (obj.m_type == O_MINIMIZE) {
|
|
r1.neg();
|
|
}
|
|
CTRACE("opt", r1 != r2, tout << obj.m_term << " evaluates to " << r1 << " but has objective " << r2 << "\n";);
|
|
CTRACE("opt", r1 != r2, model_smt2_pp(tout, m, *m_model, 0););
|
|
SASSERT(r1 == r2);
|
|
}
|
|
break;
|
|
}
|
|
case O_MAXSMT: {
|
|
rational value(0);
|
|
for (unsigned i = 0; i < obj.m_terms.size(); ++i) {
|
|
bool evaluated = m_model->eval(obj.m_terms[i], val);
|
|
if (evaluated && !m.is_true(val)) {
|
|
value += obj.m_weights[i];
|
|
}
|
|
// TBD: check that optimal was not changed.
|
|
}
|
|
TRACE("opt", tout << "value " << value << "\n";);
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
bool context::is_qsat_opt() {
|
|
if (m_objectives.size() != 1) {
|
|
return false;
|
|
}
|
|
if (m_objectives[0].m_type != O_MAXIMIZE &&
|
|
m_objectives[0].m_type != O_MINIMIZE) {
|
|
return false;
|
|
}
|
|
if (!m_arith.is_real(m_objectives[0].m_term)) {
|
|
return false;
|
|
}
|
|
for (unsigned i = 0; i < m_hard_constraints.size(); ++i) {
|
|
if (has_quantifiers(m_hard_constraints[i].get())) {
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
lbool context::run_qsat_opt() {
|
|
SASSERT(is_qsat_opt());
|
|
objective const& obj = m_objectives[0];
|
|
app_ref term(obj.m_term);
|
|
if (obj.m_type == O_MINIMIZE) {
|
|
term = m_arith.mk_uminus(term);
|
|
}
|
|
inf_eps value;
|
|
m_qmax = alloc(qe::qmax, m, m_params);
|
|
lbool result = (*m_qmax)(m_hard_constraints, term, value, m_model);
|
|
if (result != l_undef && obj.m_type == O_MINIMIZE) {
|
|
value.neg();
|
|
}
|
|
m_optsmt.setup(*m_opt_solver.get());
|
|
if (result == l_undef) {
|
|
if (obj.m_type == O_MINIMIZE) {
|
|
m_optsmt.update_upper(obj.m_index, value);
|
|
}
|
|
else {
|
|
m_optsmt.update_lower(obj.m_index, value);
|
|
}
|
|
}
|
|
else {
|
|
m_optsmt.update_lower(obj.m_index, value);
|
|
m_optsmt.update_upper(obj.m_index, value);
|
|
}
|
|
return result;
|
|
}
|
|
}
|