mirror of
https://github.com/Z3Prover/z3
synced 2025-04-08 10:25:18 +00:00
reworking pd-maxres
Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
parent
980e74b4ff
commit
e3cb0e2d8b
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@ -206,16 +206,10 @@ public:
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init_local();
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set_soft_assumptions();
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lbool is_sat = l_true;
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trace_bounds("max_res");
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trace_bounds("maxres");
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exprs cs;
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while (m_lower < m_upper) {
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#if 0
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expr_ref_vector asms(m_asms);
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sort_assumptions(asms);
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is_sat = s().check_sat(asms.size(), asms.c_ptr());
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#else
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is_sat = check_sat_hill_climb(m_asms);
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#endif
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if (m_cancel) {
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return l_undef;
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}
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@ -268,33 +262,45 @@ public:
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first = false;
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IF_VERBOSE(3, verbose_stream() << "weight: " << get_weight(asms[0].get()) << " " << get_weight(asms[index-1].get()) << " num soft: " << index << "\n";);
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m_last_index = index;
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is_sat = s().check_sat(index, asms.c_ptr());
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is_sat = check_sat(index, asms.c_ptr());
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}
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}
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else {
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is_sat = s().check_sat(asms.size(), asms.c_ptr());
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is_sat = check_sat(asms.size(), asms.c_ptr());
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}
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return is_sat;
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}
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lbool check_sat(unsigned sz, expr* const* asms) {
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if (m_st == s_primal_dual && m_c.sat_enabled()) {
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rational max_weight = m_upper;
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vector<rational> weights;
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for (unsigned i = 0; i < sz; ++i) {
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weights.push_back(get_weight(asms[i]));
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}
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return inc_sat_check_sat(s(), sz, asms, weights.c_ptr(), max_weight);
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}
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else {
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return s().check_sat(sz, asms);
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}
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}
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void found_optimum() {
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IF_VERBOSE(1, verbose_stream() << "found optimum\n";);
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s().get_model(m_model);
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DEBUG_CODE(
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for (unsigned i = 0; i < m_asms.size(); ++i) {
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SASSERT(is_true(m_asms[i].get()));
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});
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SASSERT(is_true(m_asms));
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rational upper(0);
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for (unsigned i = 0; i < m_soft.size(); ++i) {
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m_assignment[i] = is_true(m_soft[i]);
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if (!m_assignment[i]) upper += m_weights[i];
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if (!m_assignment[i]) {
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upper += m_weights[i];
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}
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}
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SASSERT(upper == m_lower);
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m_upper = m_lower;
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m_found_feasible_optimum = true;
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}
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virtual lbool operator()() {
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m_defs.reset();
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switch(m_st) {
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@ -496,14 +502,6 @@ public:
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return m_asm2weight.find(e);
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}
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void sls() {
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vector<rational> ws;
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for (unsigned i = 0; i < m_asms.size(); ++i) {
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ws.push_back(get_weight(m_asms[i].get()));
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}
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enable_sls(m_asms, ws);
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}
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rational split_core(exprs const& core) {
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if (core.empty()) return rational(0);
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// find the minimal weight:
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@ -687,6 +685,13 @@ public:
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return is_true(m_model.get(), e);
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}
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bool is_true(expr_ref_vector const& es) {
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for (unsigned i = 0; i < es.size(); ++i) {
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if (!is_true(es[i])) return false;
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}
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return true;
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}
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void remove_soft(exprs const& core, expr_ref_vector& asms) {
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for (unsigned i = 0; i < asms.size(); ++i) {
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if (core.contains(asms[i].get())) {
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@ -33,8 +33,7 @@ namespace opt {
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lbool operator()() {
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IF_VERBOSE(1, verbose_stream() << "(opt.sls)\n";);
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init();
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set_enable_sls(true);
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enable_sls(m_soft, m_weights);
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enable_sls(true);
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lbool is_sat = s().check_sat(0, 0);
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if (is_sat == l_true) {
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s().get_model(m_model);
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@ -97,12 +97,8 @@ namespace opt {
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s().updt_params(p);
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}
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void maxsmt_solver_base::enable_sls(expr_ref_vector const& soft, vector<rational> const& ws) {
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m_c.enable_sls(soft, ws);
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}
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void maxsmt_solver_base::set_enable_sls(bool f) {
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m_c.set_enable_sls(f);
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void maxsmt_solver_base::enable_sls(bool force) {
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m_c.enable_sls(force);
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}
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void maxsmt_solver_base::set_soft_assumptions() {
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@ -100,8 +100,7 @@ namespace opt {
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protected:
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void enable_sls(expr_ref_vector const& soft, weights_t& ws);
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void set_enable_sls(bool f);
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void enable_sls(bool force);
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void set_soft_assumptions();
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void trace_bounds(char const* solver);
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@ -130,7 +130,6 @@ namespace opt {
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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_enable_sls(false),
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m_is_clausal(false),
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m_pp_neat(false)
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{
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@ -532,18 +531,11 @@ namespace opt {
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}
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void context::set_soft_assumptions() {
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if (m_sat_solver.get()) {
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m_params.set_bool("soft_assumptions", true);
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m_sat_solver->updt_params(m_params);
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}
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// TBD no-op
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}
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void context::enable_sls(expr_ref_vector const& soft, vector<rational> const& weights) {
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SASSERT(soft.size() == weights.size());
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if (m_sat_solver.get()) {
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set_soft_inc_sat(m_sat_solver.get(), soft.size(), soft.c_ptr(), weights.c_ptr());
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}
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if (m_enable_sls && m_sat_solver.get()) {
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void context::enable_sls(bool force) {
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if ((force || m_enable_sls) && m_sat_solver.get()) {
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m_params.set_bool("optimize_model", true);
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m_sat_solver->updt_params(m_params);
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}
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@ -50,8 +50,7 @@ namespace opt {
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virtual solver& get_solver() = 0; // retrieve solver object (SAT or SMT solver)
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virtual ast_manager& get_manager() = 0;
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virtual params_ref& params() = 0;
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virtual void enable_sls(expr_ref_vector const& soft, weights_t& weights) = 0; // stochastic local search
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virtual void set_enable_sls(bool f) = 0; // overwrite whether SLS is enabled.
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virtual void enable_sls(bool force) = 0; // stochastic local search
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virtual void set_soft_assumptions() = 0; // configure SAT solver to skip assumptions assigned by unit-propagation
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virtual symbol const& maxsat_engine() const = 0; // retrieve maxsat engine configuration parameter.
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virtual void get_base_model(model_ref& _m) = 0; // retrieve model from initial satisfiability call.
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@ -216,8 +215,7 @@ namespace opt {
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virtual solver& get_solver();
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virtual ast_manager& get_manager() { return this->m; }
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virtual params_ref& params() { return m_params; }
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virtual void enable_sls(expr_ref_vector const& soft, weights_t& weights);
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virtual void set_enable_sls(bool f) { m_enable_sls = f; }
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virtual void enable_sls(bool force);
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virtual void set_soft_assumptions();
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virtual symbol const& maxsat_engine() const { return m_maxsat_engine; }
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virtual void get_base_model(model_ref& _m);
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@ -110,7 +110,6 @@ namespace sat {
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m_minimize_core = p.minimize_core();
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m_minimize_core_partial = p.minimize_core_partial();
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m_optimize_model = p.optimize_model();
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m_soft_assumptions = p.soft_assumptions();
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m_bcd = p.bcd();
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m_dyn_sub_res = p.dyn_sub_res();
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}
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@ -72,7 +72,6 @@ namespace sat {
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bool m_minimize_core;
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bool m_minimize_core_partial;
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bool m_optimize_model;
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bool m_soft_assumptions;
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bool m_bcd;
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@ -22,6 +22,5 @@ def_module_params('sat',
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('minimize_core', BOOL, False, 'minimize computed core'),
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('minimize_core_partial', BOOL, False, 'apply partial (cheap) core minimization'),
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('optimize_model', BOOL, False, 'enable optimization of soft constraints'),
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('soft_assumptions', BOOL, False, 'disable assumptions that are forced during unit propagation'),
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('bcd', BOOL, False, 'enable blocked clause decomposition for equality extraction'),
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('dimacs.core', BOOL, False, 'extract core from DIMACS benchmarks')))
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@ -534,10 +534,6 @@ namespace sat {
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return found_undef ? l_undef : l_false;
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}
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void solver::initialize_soft(unsigned sz, literal const* lits, double const* weights) {
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m_wsls.set_soft(sz, lits, weights);
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}
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// -----------------------
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//
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// Propagation
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@ -714,7 +710,7 @@ namespace sat {
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// Search
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//
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// -----------------------
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lbool solver::check(unsigned num_lits, literal const* lits) {
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lbool solver::check(unsigned num_lits, literal const* lits, double const* weights, double max_weight) {
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pop_to_base_level();
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IF_VERBOSE(2, verbose_stream() << "(sat.sat-solver)\n";);
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SASSERT(scope_lvl() == 0);
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@ -729,7 +725,7 @@ namespace sat {
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init_search();
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propagate(false);
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if (inconsistent()) return l_false;
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init_assumptions(num_lits, lits);
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init_assumptions(num_lits, lits, weights, max_weight);
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propagate(false);
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if (check_inconsistent()) return l_false;
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cleanup();
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}
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}
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void solver::init_assumptions(unsigned num_lits, literal const* lits) {
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void solver::init_assumptions(unsigned num_lits, literal const* lits, double const* weights, double max_weight) {
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if (num_lits == 0 && m_user_scope_literals.empty()) {
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return;
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}
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retry_init_assumptions:
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m_assumptions.reset();
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m_assumption_set.reset();
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push();
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@ -920,45 +918,75 @@ namespace sat {
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assign(nlit, justification());
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}
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for (unsigned i = 0; !inconsistent() && i < num_lits; ++i) {
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literal lit = lits[i];
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SASSERT(is_external((lit).var()));
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m_assumption_set.insert(lit);
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if (m_config.m_soft_assumptions) {
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switch(value(lit)) {
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case l_undef:
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m_assumptions.push_back(lit);
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assign(lit, justification());
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break;
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case l_false: {
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set_conflict(lit);
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flet<bool> _min1(m_config.m_minimize_core, false);
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flet<bool> _min2(m_config.m_minimize_core_partial, false);
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resolve_conflict_for_unsat_core();
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SASSERT(m_core.size() <= m_assumptions.size());
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if (m_core.size() <= 3 ||
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m_core.size() <= i - m_assumptions.size() + 1) {
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return;
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}
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else {
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m_inconsistent = false;
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}
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break;
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}
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case l_true:
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break;
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}
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propagate(false);
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if (weights) {
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if (m_config.m_optimize_model) {
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m_wsls.set_soft(num_lits, lits, weights);
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}
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else {
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m_assumptions.push_back(lit);
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assign(lit, justification());
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// propagate(false);
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svector<literal> blocker;
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if (!init_weighted_assumptions(num_lits, lits, weights, max_weight, blocker)) {
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pop_to_base_level();
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mk_clause(blocker.size(), blocker.c_ptr());
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goto retry_init_assumptions;
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}
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}
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return;
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}
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for (unsigned i = 0; !inconsistent() && i < num_lits; ++i) {
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literal lit = lits[i];
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SASSERT(is_external(lit.var()));
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m_assumption_set.insert(lit);
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m_assumptions.push_back(lit);
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assign(lit, justification());
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// propagate(false);
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}
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}
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bool solver::init_weighted_assumptions(unsigned num_lits, literal const* lits, double const* weights, double max_weight,
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svector<literal>& blocker) {
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double weight = 0;
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blocker.reset();
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for (unsigned i = 0; !inconsistent() && i < num_lits; ++i) {
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literal lit = lits[i];
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SASSERT(is_external(lit.var()));
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m_assumption_set.insert(lit);
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switch(value(lit)) {
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case l_undef:
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m_assumptions.push_back(lit);
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assign(lit, justification());
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break;
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case l_false: {
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set_conflict(lit);
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flet<bool> _min1(m_config.m_minimize_core, false);
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flet<bool> _min2(m_config.m_minimize_core_partial, false);
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resolve_conflict_for_unsat_core();
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weight += weights[i];
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blocker.push_back(~lit);
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SASSERT(m_core.size() <= m_assumptions.size());
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SASSERT(m_assumptions.size() <= i);
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if (m_core.size() <= 3 || m_core.size() < blocker.size()) {
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TRACE("opt", tout << "found small core: " << m_core.size() << "\n";);
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return true;
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}
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m_inconsistent = false;
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if (weight >= max_weight) {
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TRACE("opt", tout << "blocking soft correction set: " << blocker.size() << "\n";);
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// block the current correction set candidate.
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return false;
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}
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break;
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}
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case l_true:
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break;
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}
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propagate(false);
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}
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return true;
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}
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void solver::reinit_assumptions() {
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if (tracking_assumptions() && scope_lvl() == 0) {
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TRACE("sat", tout << m_assumptions << "\n";);
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@ -239,7 +239,6 @@ namespace sat {
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if (memory::get_allocation_size() > m_config.m_max_memory) throw solver_exception(Z3_MAX_MEMORY_MSG);
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}
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typedef std::pair<literal, literal> bin_clause;
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void initialize_soft(unsigned sz, literal const* lits, double const* weights);
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protected:
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watch_list & get_wlist(literal l) { return m_watches[l.index()]; }
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watch_list const & get_wlist(literal l) const { return m_watches[l.index()]; }
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@ -271,7 +270,11 @@ namespace sat {
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//
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// -----------------------
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public:
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lbool check(unsigned num_lits = 0, literal const* lits = 0);
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lbool check(unsigned num_lits = 0, literal const* lits = 0) {
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return check(num_lits, lits, 0, 0);
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}
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lbool check(unsigned num_lits, literal const* lits, double const* weights, double max_weight);
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model const & get_model() const { return m_model; }
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bool model_is_current() const { return m_model_is_current; }
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literal_vector const& get_core() const { return m_core; }
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@ -291,7 +294,8 @@ namespace sat {
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bool_var next_var();
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lbool bounded_search();
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void init_search();
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void init_assumptions(unsigned num_lits, literal const* lits);
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void init_assumptions(unsigned num_lits, literal const* lits, double const* weights, double max_weight);
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bool init_weighted_assumptions(unsigned num_lits, literal const* lits, double const* weights, double max_weight, svector<literal>& blocker);
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void reinit_assumptions();
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bool tracking_assumptions() const;
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bool is_assumption(literal l) const;
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@ -30,6 +30,7 @@ Notes:
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#include "goal2sat.h"
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#include "ast_pp.h"
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#include "model_smt2_pp.h"
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#include "filter_model_converter.h"
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// incremental SAT solver.
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class inc_sat_solver : public solver {
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@ -55,9 +56,6 @@ class inc_sat_solver : public solver {
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proof_converter_ref m_pc;
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model_converter_ref m_mc2;
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expr_dependency_ref m_dep_core;
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expr_ref_vector m_soft;
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vector<rational> m_weights;
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bool m_soft_assumptions;
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typedef obj_map<expr, sat::literal> dep2asm_t;
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@ -71,9 +69,7 @@ public:
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m_core(m),
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m_map(m),
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m_num_scopes(0),
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m_dep_core(m),
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m_soft(m),
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m_soft_assumptions(false) {
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m_dep_core(m) {
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m_params.set_bool("elim_vars", false);
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m_solver.updt_params(m_params);
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params_ref simp2_p = p;
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@ -99,25 +95,25 @@ public:
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|||
|
||||
virtual void set_progress_callback(progress_callback * callback) {}
|
||||
|
||||
virtual lbool check_sat(unsigned num_assumptions, expr * const * assumptions) {
|
||||
virtual lbool check_sat(unsigned num_assumptions, expr * const * assumptions) {
|
||||
return check_sat(num_assumptions, assumptions, 0, 0);
|
||||
}
|
||||
|
||||
lbool check_sat(unsigned num_assumptions, expr * const * assumptions, double const* weights, double max_weight) {
|
||||
|
||||
m_solver.pop_to_base_level();
|
||||
dep2asm_t dep2asm;
|
||||
m_model = 0;
|
||||
lbool r = internalize_formulas();
|
||||
if (r != l_true) return r;
|
||||
r = internalize_assumptions(num_assumptions, assumptions, dep2asm);
|
||||
if (r != l_true) return r;
|
||||
extract_assumptions(dep2asm, m_asms);
|
||||
|
||||
r = initialize_soft_constraints();
|
||||
r = internalize_assumptions(num_assumptions, assumptions, weights, dep2asm);
|
||||
if (r != l_true) return r;
|
||||
|
||||
//m_solver.display_dimacs(std::cout);
|
||||
r = m_solver.check(m_asms.size(), m_asms.c_ptr());
|
||||
r = m_solver.check(m_asms.size(), m_asms.c_ptr(), weights, max_weight);
|
||||
switch (r) {
|
||||
case l_true:
|
||||
if (num_assumptions > 0) {
|
||||
if (num_assumptions > 0 && !weights) {
|
||||
check_assumptions(dep2asm);
|
||||
}
|
||||
break;
|
||||
|
@ -187,7 +183,6 @@ public:
|
|||
m_params = p;
|
||||
m_params.set_bool("elim_vars", false);
|
||||
m_solver.updt_params(m_params);
|
||||
m_soft_assumptions = m_params.get_bool("soft_assumptions", false);
|
||||
m_optimize_model = m_params.get_bool("optimize_model", false);
|
||||
}
|
||||
virtual void collect_statistics(statistics & st) const {
|
||||
|
@ -226,58 +221,9 @@ public:
|
|||
virtual expr * get_assumption(unsigned idx) const {
|
||||
return m_asmsf[idx];
|
||||
}
|
||||
void set_soft(unsigned sz, expr*const* soft, rational const* weights) {
|
||||
m_soft.reset();
|
||||
m_weights.reset();
|
||||
m_soft.append(sz, soft);
|
||||
m_weights.append(sz, weights);
|
||||
}
|
||||
|
||||
private:
|
||||
|
||||
lbool initialize_soft_constraints() {
|
||||
dep2asm_t dep2asm;
|
||||
if (m_soft.empty()) {
|
||||
return l_true;
|
||||
}
|
||||
expr_ref_vector soft(m_soft);
|
||||
for (unsigned i = 0; i < soft.size(); ++i) {
|
||||
expr* e = soft[i].get(), *e1;
|
||||
if (is_uninterp_const(e) || (m.is_not(e, e1) && is_uninterp_const(e1))) {
|
||||
continue;
|
||||
}
|
||||
expr_ref asum(m), fml(m);
|
||||
asum = m.mk_fresh_const("soft", m.mk_bool_sort());
|
||||
fml = m.mk_iff(asum, e);
|
||||
m_fmls.push_back(fml);
|
||||
soft[i] = asum;
|
||||
}
|
||||
m_soft.reset();
|
||||
lbool r = internalize_formulas();
|
||||
if (r != l_true) return r;
|
||||
r = internalize_assumptions(soft.size(), soft.c_ptr(), dep2asm);
|
||||
if (r != l_true) return r;
|
||||
sat::literal_vector lits;
|
||||
svector<double> weights;
|
||||
sat::literal lit;
|
||||
for (unsigned i = 0; i < soft.size(); ++i) {
|
||||
weights.push_back(m_weights[i].get_double());
|
||||
expr* s = soft[i].get();
|
||||
if (!dep2asm.find(s, lit)) {
|
||||
IF_VERBOSE(0,
|
||||
verbose_stream() << "not found: " << mk_pp(s, m) << "\n";
|
||||
dep2asm_t::iterator it = dep2asm.begin();
|
||||
dep2asm_t::iterator end = dep2asm.end();
|
||||
for (; it != end; ++it) {
|
||||
verbose_stream() << mk_pp(it->m_key, m) << " " << it->m_value << "\n";
|
||||
}
|
||||
UNREACHABLE(););
|
||||
}
|
||||
lits.push_back(lit);
|
||||
}
|
||||
m_solver.initialize_soft(lits.size(), lits.c_ptr(), weights.c_ptr());
|
||||
return r;
|
||||
}
|
||||
|
||||
lbool internalize_goal(goal_ref& g, dep2asm_t& dep2asm) {
|
||||
m_mc2.reset();
|
||||
|
@ -305,15 +251,54 @@ private:
|
|||
return l_true;
|
||||
}
|
||||
|
||||
lbool internalize_assumptions(unsigned sz, expr* const* asms, dep2asm_t& dep2asm) {
|
||||
lbool internalize_assumptions(unsigned sz, expr* const* asms, double const* weights, dep2asm_t& dep2asm) {
|
||||
if (sz == 0) {
|
||||
return l_true;
|
||||
}
|
||||
if (weights) {
|
||||
return internalize_weighted(sz, asms, weights, dep2asm);
|
||||
}
|
||||
return internalize_unweighted(sz, asms, dep2asm);
|
||||
}
|
||||
|
||||
lbool internalize_unweighted(unsigned sz, expr* const* asms, dep2asm_t& dep2asm) {
|
||||
goal_ref g = alloc(goal, m, true, true); // models and cores are enabled.
|
||||
lbool res = l_undef;
|
||||
for (unsigned i = 0; i < sz; ++i) {
|
||||
g->assert_expr(asms[i], m.mk_leaf(asms[i]));
|
||||
}
|
||||
return internalize_goal(g, dep2asm);
|
||||
res = internalize_goal(g, dep2asm);
|
||||
if (res == l_true) {
|
||||
extract_assumptions(dep2asm);
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
/*
|
||||
\brief extract weighted assumption literals in the same order as the weights.
|
||||
For this purpose we enforce tha assumptions are literals.
|
||||
*/
|
||||
lbool internalize_weighted(unsigned sz, expr* const* asms, double const* weights, dep2asm_t& dep2asm) {
|
||||
goal_ref g = alloc(goal, m, true, true); // models and cores are enabled.
|
||||
lbool res = l_undef;
|
||||
m_asms.reset();
|
||||
expr_ref_vector lits(m);
|
||||
filter_model_converter_ref fmc = alloc(filter_model_converter, m);
|
||||
for (unsigned i = 0; i < sz; ++i) {
|
||||
expr_ref lit = ensure_literal(g, asms[i], fmc.get());
|
||||
lits.push_back(lit);
|
||||
g->assert_expr(lit, m.mk_leaf(lit));
|
||||
}
|
||||
m_mc = concat(m_mc.get(), fmc.get());
|
||||
res = internalize_goal(g, dep2asm);
|
||||
if (res == l_true) {
|
||||
for (unsigned i = 0; i < lits.size(); ++i) {
|
||||
sat::literal l;
|
||||
VERIFY (dep2asm.find(lits[i].get(), l));
|
||||
m_asms.push_back(l);
|
||||
}
|
||||
}
|
||||
return res;
|
||||
}
|
||||
|
||||
lbool internalize_formulas() {
|
||||
|
@ -328,11 +313,27 @@ private:
|
|||
return internalize_goal(g, dep2asm);
|
||||
}
|
||||
|
||||
void extract_assumptions(dep2asm_t& dep2asm, sat::literal_vector& asms) {
|
||||
asms.reset();
|
||||
expr_ref ensure_literal(goal_ref& g, expr* e, filter_model_converter* fmc) {
|
||||
expr_ref result(m), fml(m);
|
||||
expr* e1;
|
||||
if (is_uninterp_const(e) || (m.is_not(e, e1) && is_uninterp_const(e1))) {
|
||||
result = e;
|
||||
}
|
||||
else {
|
||||
// TBD: need a filter_model_converter to remove
|
||||
result = m.mk_fresh_const("soft", m.mk_bool_sort());
|
||||
fmc->insert(to_app(result)->get_decl());
|
||||
fml = m.mk_implies(result, e);
|
||||
g->assert_expr(fml);
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
void extract_assumptions(dep2asm_t& dep2asm) {
|
||||
m_asms.reset();
|
||||
dep2asm_t::iterator it = dep2asm.begin(), end = dep2asm.end();
|
||||
for (; it != end; ++it) {
|
||||
asms.push_back(it->m_value);
|
||||
m_asms.push_back(it->m_value);
|
||||
}
|
||||
//IF_VERBOSE(0, verbose_stream() << asms << "\n";);
|
||||
}
|
||||
|
@ -363,8 +364,6 @@ private:
|
|||
VERIFY(asm2dep.find(core[i].index(), e));
|
||||
m_core.push_back(e);
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
||||
void check_assumptions(dep2asm_t& dep2asm) {
|
||||
|
@ -372,7 +371,7 @@ private:
|
|||
dep2asm_t::iterator it = dep2asm.begin(), end = dep2asm.end();
|
||||
for (; it != end; ++it) {
|
||||
sat::literal lit = it->m_value;
|
||||
if (!m_soft_assumptions && sat::value_at(lit, ll_m) != l_true) {
|
||||
if (sat::value_at(lit, ll_m) != l_true) {
|
||||
IF_VERBOSE(0, verbose_stream() << mk_pp(it->m_key, m) << " does not evaluate to true\n";
|
||||
verbose_stream() << m_asms << "\n";
|
||||
m_solver.display_assignment(verbose_stream());
|
||||
|
@ -433,7 +432,12 @@ solver* mk_inc_sat_solver(ast_manager& m, params_ref const& p) {
|
|||
return alloc(inc_sat_solver, m, p);
|
||||
}
|
||||
|
||||
void set_soft_inc_sat(solver* _s, unsigned sz, expr*const* soft, rational const* weights) {
|
||||
inc_sat_solver* s = dynamic_cast<inc_sat_solver*>(_s);
|
||||
s->set_soft(sz, soft, weights);
|
||||
|
||||
lbool inc_sat_check_sat(solver& _s, unsigned sz, expr*const* soft, rational const* _weights, rational const& max_weight) {
|
||||
inc_sat_solver& s = dynamic_cast<inc_sat_solver&>(_s);
|
||||
vector<double> weights;
|
||||
for (unsigned i = 0; _weights && i < sz; ++i) {
|
||||
weights.push_back(_weights[i].get_double());
|
||||
}
|
||||
return s.check_sat(sz, soft, weights.c_ptr(), max_weight.get_double());
|
||||
}
|
||||
|
|
|
@ -24,6 +24,6 @@ Notes:
|
|||
|
||||
solver* mk_inc_sat_solver(ast_manager& m, params_ref const& p);
|
||||
|
||||
void set_soft_inc_sat(solver* s, unsigned sz, expr*const* soft, rational const* weights);
|
||||
lbool inc_sat_check_sat(solver& s, unsigned sz, expr*const* soft, rational const* weights, rational const& max_weight);
|
||||
|
||||
#endif
|
||||
|
|
Loading…
Reference in a new issue