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https://github.com/Z3Prover/z3
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fixes to maxres/mss
Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner
parent
b5bbf83847
commit
18b491eee0
10 changed files with 76 additions and 114 deletions
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@ -37,6 +37,7 @@ class inc_sat_solver : public solver {
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sat::solver m_solver;
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goal2sat m_goal2sat;
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params_ref m_params;
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bool m_optimize_model; // parameter
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expr_ref_vector m_fmls;
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expr_ref_vector m_current_fmls;
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unsigned_vector m_fmls_lim;
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@ -54,10 +55,12 @@ class inc_sat_solver : public solver {
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expr_ref_vector m_soft;
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vector<rational> m_weights;
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typedef obj_map<expr, sat::literal> dep2asm_t;
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public:
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inc_sat_solver(ast_manager& m, params_ref const& p):
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m(m), m_solver(p,0), m_params(p),
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m(m), m_solver(p,0),
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m_params(p), m_optimize_model(false),
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m_fmls(m), m_current_fmls(m), m_core(m), m_map(m),
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m_num_scopes(0),
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m_dep_core(m),
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@ -165,6 +168,7 @@ public:
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m_params = p;
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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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m_optimize_model = m_params.get_bool("optimize_model", false);
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}
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virtual void collect_statistics(statistics & st) const {
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m_preprocess->collect_statistics(st);
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@ -226,32 +230,26 @@ private:
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lbool r = internalize_formulas();
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if (r != l_true) return r;
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r = internalize_assumptions(soft.size(), soft.c_ptr(), dep2asm);
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if (r != l_true) return r;
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sat::literal_vector lits;
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svector<double> weights;
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sat::literal lit;
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if (r == l_true) {
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for (unsigned i = 0; i < soft.size(); ++i) {
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weights.push_back(m_weights[i].get_double());
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expr* s = soft[i].get();
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bool is_neg = m.is_not(s, s);
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if (!dep2asm.find(s, lit)) {
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std::cout << "not found: " << mk_pp(s, m) << "\n";
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dep2asm_t::iterator it = dep2asm.begin(), end = dep2asm.end();
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for (; it != end; ++it) {
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std::cout << mk_pp(it->m_key, m) << " " << it->m_value << "\n";
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}
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UNREACHABLE();
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}
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if (is_neg) {
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lit.neg();
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}
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lits.push_back(lit);
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for (unsigned i = 0; i < soft.size(); ++i) {
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weights.push_back(m_weights[i].get_double());
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expr* s = soft[i].get();
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if (!dep2asm.find(s, lit)) {
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IF_VERBOSE(0,
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verbose_stream() << "not found: " << mk_pp(s, m) << "\n";
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dep2asm_t::iterator it = dep2asm.begin();
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dep2asm_t::iterator end = dep2asm.end();
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for (; it != end; ++it) {
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verbose_stream() << mk_pp(it->m_key, m) << " " << it->m_value << "\n";
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}
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UNREACHABLE(););
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}
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m_solver.initialize_soft(lits.size(), lits.c_ptr(), weights.c_ptr());
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m_params.set_bool("optimize_model", true);
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m_solver.updt_params(m_params);
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lits.push_back(lit);
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}
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m_solver.initialize_soft(lits.size(), lits.c_ptr(), weights.c_ptr());
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return r;
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}
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@ -324,12 +322,8 @@ private:
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m_core.reset();
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for (unsigned i = 0; i < core.size(); ++i) {
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expr* e;
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if (asm2dep.find(core[i].index(), e)) {
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if (core[i].sign()) {
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e = m.mk_not(e);
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}
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m_core.push_back(e);
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}
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VERIFY (asm2dep.find(core[i].index(), e));
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m_core.push_back(e);
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}
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TRACE("opt",
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dep2asm_t::iterator it = dep2asm.begin();
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@ -72,14 +72,12 @@ public:
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enum strategy_t {
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s_mus,
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s_mus_mss,
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s_mus_mss2,
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s_mss
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};
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private:
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expr_ref_vector m_B;
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expr_ref_vector m_asms;
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obj_map<expr, rational> m_asm2weight;
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obj_map<expr, bool> m_asm2value;
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ptr_vector<expr> m_new_core;
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mus m_mus;
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mss m_mss;
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@ -186,44 +184,6 @@ public:
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return l_true;
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}
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lbool mus_mss_solver() {
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init();
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init_local();
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sls();
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exprs mcs;
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vector<exprs> cores;
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while (m_lower < m_upper) {
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TRACE("opt",
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display_vec(tout, m_asms.size(), m_asms.c_ptr());
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s().display(tout);
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tout << "\n";
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display(tout);
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);
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lbool is_sat = try_improve_bound(cores, mcs);
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if (m_cancel) {
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return l_undef;
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}
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switch (is_sat) {
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case l_undef:
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return l_undef;
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case l_false:
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SASSERT(cores.empty() && mcs.empty());
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m_lower = m_upper;
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return l_true;
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case l_true:
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SASSERT(cores.empty() || mcs.empty());
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for (unsigned i = 0; i < cores.size(); ++i) {
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process_unsat(cores[i]);
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}
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if (cores.empty()) {
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process_sat(mcs);
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}
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break;
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}
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}
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m_lower = m_upper;
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return l_true;
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}
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lbool mss_solver() {
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init();
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@ -234,6 +194,9 @@ public:
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lbool is_sat = l_true;
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while (m_lower < m_upper && is_sat == l_true) {
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IF_VERBOSE(1, verbose_stream() << "(opt.maxres [" << m_lower << ":" << m_upper << "])\n";);
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if (m_cancel) {
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return l_undef;
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}
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vector<exprs> cores;
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exprs mss;
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model_ref mdl;
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@ -241,6 +204,12 @@ public:
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mcs.reset();
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s().get_model(mdl);
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update_assignment(mdl.get());
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exprs cs;
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get_current_correction_set(mdl.get(), cs);
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process_sat(cs);
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#if 0
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is_sat = get_mss(mdl.get(), cores, mss, mcs);
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switch (is_sat) {
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@ -249,15 +218,12 @@ public:
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case l_false:
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m_lower = m_upper;
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return l_true;
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case l_true: {
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case l_true:
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process_sat(mcs);
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get_mss_model();
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break;
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}
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}
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if (m_cancel) {
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return l_undef;
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break;
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}
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#endif
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if (m_lower < m_upper) {
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is_sat = s().check_sat(0, 0);
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}
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@ -294,7 +260,7 @@ public:
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Suppose correction set is huge. Do we really need it?
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*/
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lbool mus_mss2_solver() {
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lbool mus_mss_solver() {
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init();
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init_local();
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sls();
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@ -356,14 +322,8 @@ public:
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// obtained from the current best model.
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//
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//
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// TBD: throttle blocking on correction sets if they are too big.
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// likewise, if the cores are too big, don't block the cores.
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//
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exprs cs;
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get_current_correction_set(cs);
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get_current_correction_set(mdl.get(), cs);
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unsigned max_core = max_core_size(cores);
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if (!cs.empty() && cs.size() < max_core) {
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process_sat(cs);
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@ -379,7 +339,6 @@ public:
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void found_optimum() {
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s().get_model(m_model);
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m_asm2value.reset();
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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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@ -397,8 +356,6 @@ public:
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return mus_solver();
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case s_mus_mss:
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return mus_mss_solver();
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case s_mus_mss2:
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return mus_mss2_solver();
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case s_mss:
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return mss_solver();
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}
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@ -462,14 +419,14 @@ public:
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return is_sat;
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}
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void get_current_correction_set(exprs& cs) {
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void get_current_correction_set(model* mdl, exprs& cs) {
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cs.reset();
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if (!mdl) return;
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for (unsigned i = 0; i < m_asms.size(); ++i) {
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if (!is_true(m_asms[i].get())) {
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if (!is_true(mdl, m_asms[i].get())) {
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cs.push_back(m_asms[i].get());
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}
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}
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IF_VERBOSE(2, verbose_stream() << "(opt.maxres correction set size: " << cs.size() << ")\n";);
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TRACE("opt", display_vec(tout << "new correction set: ", cs.size(), cs.c_ptr()););
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}
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@ -554,7 +511,7 @@ public:
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IF_VERBOSE(1, verbose_stream() << "(opt.maxres [" << m_lower << ":" << m_upper << "])\n";);
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}
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void get_mus_model(model_ref& mdl) {
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bool get_mus_model(model_ref& mdl) {
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rational w(0);
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if (m_c.sat_enabled()) {
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// SAT solver core extracts some model
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@ -567,6 +524,7 @@ public:
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if (mdl.get() && w < m_upper) {
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update_assignment(mdl.get());
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}
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return 0 != mdl.get();
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}
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void get_mss_model() {
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@ -682,17 +640,13 @@ public:
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s().assert_expr(fml);
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fml = m.mk_implies(dd, b_i);
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s().assert_expr(fml);
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m_asm2value.insert(dd, is_true(d) && is_true(b_i));
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d = dd;
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}
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else {
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dd = m.mk_and(b_i, d);
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m_asm2value.insert(dd, is_true(d) && is_true(b_i));
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m_trail.push_back(dd);
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d = dd;
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d = m.mk_and(b_i, d);
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m_trail.push_back(d);
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}
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asum = mk_fresh_bool("a");
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m_asm2value.insert(asum, is_true(b_i1) || is_true(d));
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cls = m.mk_or(b_i1, d);
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fml = m.mk_implies(asum, cls);
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new_assumption(asum, w);
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@ -809,7 +763,6 @@ public:
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return l_undef;
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}
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void update_assignment(model* mdl) {
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rational upper(0);
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expr_ref tmp(m);
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@ -826,7 +779,6 @@ public:
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return;
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}
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m_model = mdl;
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m_asm2value.reset();
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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].get());
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@ -851,16 +803,16 @@ public:
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s().assert_expr(fml);
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}
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bool is_true(expr* e) {
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bool truth_value;
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if (m_asm2value.find(e, truth_value)) {
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return truth_value;
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}
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bool is_true(model* mdl, expr* e) {
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expr_ref tmp(m);
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VERIFY(m_model->eval(e, tmp));
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VERIFY(mdl->eval(e, tmp));
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return m.is_true(tmp);
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}
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bool is_true(expr* e) {
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return is_true(m_model.get(), e);
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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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@ -933,7 +885,7 @@ opt::maxsmt_solver_base* opt::mk_maxres(
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opt::maxsmt_solver_base* opt::mk_mus_mss_maxres(
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context& c, weights_t& ws, expr_ref_vector const& soft) {
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return alloc(maxres, c, ws, soft, maxres::s_mus_mss2);
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return alloc(maxres, c, ws, soft, maxres::s_mus_mss);
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}
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opt::maxsmt_solver_base* opt::mk_mss_maxres(
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@ -70,6 +70,7 @@ struct mus::imp {
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lbool get_mus(unsigned_vector& mus) {
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// SASSERT: mus does not have duplicates.
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m_model.reset();
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unsigned_vector core;
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for (unsigned i = 0; i < m_cls2expr.size(); ++i) {
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core.push_back(i);
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@ -465,9 +465,13 @@ namespace opt {
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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_enable_sls && m_sat_solver.get()) {
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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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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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}
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struct context::is_bv {
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