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move sat_ddfw to sls, initiate sls-bv-plugin

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Nikolaj Bjorner 2024-07-06 20:14:44 -07:00
parent 833f524887
commit e7104ebb93
23 changed files with 484 additions and 141 deletions
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2
src/sat/CMakeLists.txt
View file

@ -15,7 +15,7 @@ z3_add_component(sat
sat_config.cpp
sat_cut_simplifier.cpp
sat_cutset.cpp
sat_ddfw.cpp
sat_ddfw_wrapper.cpp
sat_drat.cpp
sat_elim_eqs.cpp
sat_elim_vars.cpp

653
src/sat/sat_ddfw.cpp
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@ -1,653 +0,0 @@
/*++
Copyright (c) 2019 Microsoft Corporation
Module Name:
sat_ddfw.cpp
Abstract:
DDFW Local search module for clauses
Author:
Nikolaj Bjorner, Marijn Heule 2019-4-23
Notes:
http://www.ict.griffith.edu.au/~johnt/publications/CP2006raouf.pdf
Todo:
- rephase strategy
- experiment with backoff schemes for restarts
- parallel sync
--*/
#include "util/luby.h"
#include "sat/sat_ddfw.h"
#include "sat/sat_solver.h"
#include "params/sat_params.hpp"
namespace sat {
ddfw::~ddfw() {
}
lbool ddfw::check(unsigned sz, literal const* assumptions, parallel* p) {
init(sz, assumptions);
flet<parallel*> _p(m_par, p);
if (m_plugin)
check_with_plugin();
else
check_without_plugin();
remove_assumptions();
log();
return m_min_sz == 0 ? l_true : l_undef;
}
void ddfw::check_without_plugin() {
while (m_limit.inc() && m_min_sz > 0) {
if (should_reinit_weights()) do_reinit_weights();
else if (do_flip<false>());
else if (should_restart()) do_restart();
else if (should_parallel_sync()) do_parallel_sync();
else shift_weights();
}
}
void ddfw::check_with_plugin() {
m_plugin->init_search();
m_steps_since_progress = 0;
unsigned steps = 0;
save_best_values();
while (m_min_sz != 0 && m_steps_since_progress++ <= 1500000) {
if (should_reinit_weights()) do_reinit_weights();
else if (steps % 5000 == 0) shift_weights(), m_plugin->on_rescale();
else if (should_restart()) do_restart(), m_plugin->on_restart();
else if (do_flip<true>());
else shift_weights(), m_plugin->on_rescale();
++steps;
}
m_plugin->finish_search();
}
void ddfw::log() {
double sec = m_stopwatch.get_current_seconds();
double kflips_per_sec = sec > 0 ? (m_flips - m_last_flips) / (1000.0 * sec) : 0.0;
if (m_last_flips == 0) {
IF_VERBOSE(1, verbose_stream() << "(sat.ddfw :unsat :models :kflips/sec :flips :restarts :reinits :unsat_vars :shifts";
if (m_par) verbose_stream() << " :par";
verbose_stream() << ")\n");
}
IF_VERBOSE(1, verbose_stream() << "(sat.ddfw "
<< std::setw(07) << m_min_sz
<< std::setw(07) << m_models.size()
<< std::setw(10) << kflips_per_sec
<< std::setw(10) << m_flips
<< std::setw(10) << m_restart_count
<< std::setw(11) << m_reinit_count
<< std::setw(13) << m_unsat_vars.size()
<< std::setw(9) << m_shifts;
if (m_par) verbose_stream() << std::setw(10) << m_parsync_count;
verbose_stream() << ")\n");
m_stopwatch.start();
m_last_flips = m_flips;
}
template<bool uses_plugin>
bool ddfw::do_flip() {
double reward = 0;
bool_var v = pick_var<uses_plugin>(reward);
return apply_flip<uses_plugin>(v, reward);
}
template<bool uses_plugin>
bool ddfw::apply_flip(bool_var v, double reward) {
if (v == null_bool_var)
return false;
if (reward > 0 || (reward == 0 && m_rand(100) <= m_config.m_use_reward_zero_pct)) {
flip(v);
if (m_unsat.size() <= m_min_sz)
save_best_values();
return true;
}
return false;
}
template<bool uses_plugin>
bool_var ddfw::pick_var(double& r) {
double sum_pos = 0;
unsigned n = 1;
bool_var v0 = null_bool_var;
for (bool_var v : m_unsat_vars) {
r = uses_plugin ? plugin_reward(v) : reward(v);
if (r > 0.0)
sum_pos += score(r);
else if (r == 0.0 && sum_pos == 0 && (m_rand() % (n++)) == 0)
v0 = v;
}
if (sum_pos > 0) {
double lim_pos = ((double) m_rand() / (1.0 + m_rand.max_value())) * sum_pos;
for (bool_var v : m_unsat_vars) {
r = uses_plugin && is_external(v) ? m_vars[v].m_last_reward : reward(v);
if (r > 0) {
lim_pos -= score(r);
if (lim_pos <= 0)
return v;
}
}
}
r = 0;
if (v0 != null_bool_var)
return v0;
if (m_unsat_vars.empty())
return null_bool_var;
return m_unsat_vars.elem_at(m_rand(m_unsat_vars.size()));
}
void ddfw::add(unsigned n, literal const* c) {
unsigned idx = m_clauses.size();
m_clauses.push_back(clause_info(n, c, m_config.m_init_clause_weight));
for (literal lit : m_clauses.back().m_clause) {
m_use_list.reserve(2*(lit.var()+1));
m_vars.reserve(lit.var()+1);
m_use_list[lit.index()].push_back(idx);
}
}
sat::bool_var ddfw::add_var(bool is_internal) {
auto v = m_vars.size();
m_vars.reserve(v + 1);
m_vars[v].m_internal = is_internal;
return v;
}
/**
* Remove the last clause that was added
*/
void ddfw::del() {
auto& info = m_clauses.back();
for (literal lit : info.m_clause)
m_use_list[lit.index()].pop_back();
m_clauses.pop_back();
if (m_unsat.contains(m_clauses.size()))
m_unsat.remove(m_clauses.size());
}
void ddfw::add(solver const& s) {
m_clauses.reset();
m_use_list.reset();
m_num_non_binary_clauses = 0;
unsigned trail_sz = s.init_trail_size();
for (unsigned i = 0; i < trail_sz; ++i) {
add(1, s.m_trail.data() + i);
}
unsigned sz = s.m_watches.size();
for (unsigned l_idx = 0; l_idx < sz; ++l_idx) {
literal l1 = ~to_literal(l_idx);
watch_list const & wlist = s.m_watches[l_idx];
for (watched const& w : wlist) {
if (!w.is_binary_non_learned_clause())
continue;
literal l2 = w.get_literal();
if (l1.index() > l2.index())
continue;
literal ls[2] = { l1, l2 };
add(2, ls);
}
}
for (clause* c : s.m_clauses) {
add(c->size(), c->begin());
}
m_num_non_binary_clauses = s.m_clauses.size();
}
void ddfw::add_assumptions() {
for (unsigned i = 0; i < m_assumptions.size(); ++i)
add(1, m_assumptions.data() + i);
}
void ddfw::remove_assumptions() {
if (m_assumptions.empty())
return;
for (unsigned i = 0; i < m_assumptions.size(); ++i)
del();
init(0, nullptr);
}
void ddfw::init(unsigned sz, literal const* assumptions) {
m_assumptions.reset();
m_assumptions.append(sz, assumptions);
add_assumptions();
for (unsigned v = 0; v < num_vars(); ++v) {
literal lit(v, false), nlit(v, true);
value(v) = (m_rand() % 2) == 0; // m_use_list[lit.index()].size() >= m_use_list[nlit.index()].size();
}
init_clause_data();
flatten_use_list();
m_reinit_count = 0;
m_reinit_next = m_config.m_reinit_base;
m_restart_count = 0;
m_restart_next = m_config.m_restart_base*2;
m_parsync_count = 0;
m_parsync_next = m_config.m_parsync_base;
m_min_sz = m_unsat.size();
m_flips = 0;
m_last_flips = 0;
m_shifts = 0;
m_stopwatch.start();
}
void ddfw::reinit(solver& s, bool_vector const& phase) {
add(s);
add_assumptions();
for (unsigned v = 0; v < phase.size(); ++v) {
value(v) = phase[v];
reward(v) = 0;
make_count(v) = 0;
}
init_clause_data();
flatten_use_list();
}
void ddfw::reinit() {
add_assumptions();
init_clause_data();
flatten_use_list();
}
void ddfw::flatten_use_list() {
m_use_list_index.reset();
m_flat_use_list.reset();
for (auto const& ul : m_use_list) {
m_use_list_index.push_back(m_flat_use_list.size());
m_flat_use_list.append(ul);
}
m_use_list_index.push_back(m_flat_use_list.size());
}
void ddfw::flip(bool_var v) {
++m_flips;
literal lit = literal(v, !value(v));
literal nlit = ~lit;
SASSERT(is_true(lit));
for (unsigned cls_idx : use_list(lit)) {
clause_info& ci = m_clauses[cls_idx];
ci.del(lit);
double w = ci.m_weight;
// cls becomes false: flip any variable in clause to receive reward w
switch (ci.m_num_trues) {
case 0: {
m_unsat.insert_fresh(cls_idx);
auto const& c = get_clause(cls_idx);
for (literal l : c) {
inc_reward(l, w);
inc_make(l);
}
inc_reward(lit, w);
break;
}
case 1:
dec_reward(to_literal(ci.m_trues), w);
break;
default:
break;
}
}
for (unsigned cls_idx : use_list(nlit)) {
clause_info& ci = m_clauses[cls_idx];
double w = ci.m_weight;
// the clause used to have a single true (pivot) literal, now it has two.
// Then the previous pivot is no longer penalized for flipping.
switch (ci.m_num_trues) {
case 0: {
m_unsat.remove(cls_idx);
auto const& c = get_clause(cls_idx);
for (literal l : c) {
dec_reward(l, w);
dec_make(l);
}
dec_reward(nlit, w);
break;
}
case 1:
inc_reward(to_literal(ci.m_trues), w);
break;
default:
break;
}
ci.add(nlit);
}
value(v) = !value(v);
update_reward_avg(v);
}
bool ddfw::should_reinit_weights() {
return m_flips >= m_reinit_next;
}
void ddfw::do_reinit_weights() {
log();
if (m_reinit_count % 2 == 0) {
for (auto& ci : m_clauses)
ci.m_weight += 1;
}
else {
for (auto& ci : m_clauses)
if (ci.is_true())
ci.m_weight = m_config.m_init_clause_weight;
else
ci.m_weight = m_config.m_init_clause_weight + 1;
}
init_clause_data();
++m_reinit_count;
m_reinit_next += m_reinit_count * m_config.m_reinit_base;
}
void ddfw::init_clause_data() {
for (unsigned v = 0; v < num_vars(); ++v) {
make_count(v) = 0;
reward(v) = 0;
}
m_unsat_vars.reset();
m_unsat.reset();
unsigned sz = m_clauses.size();
for (unsigned i = 0; i < sz; ++i) {
auto& ci = m_clauses[i];
auto const& c = get_clause(i);
ci.m_trues = 0;
ci.m_num_trues = 0;
for (literal lit : c)
if (is_true(lit))
ci.add(lit);
switch (ci.m_num_trues) {
case 0:
for (literal lit : c) {
inc_reward(lit, ci.m_weight);
inc_make(lit);
}
m_unsat.insert_fresh(i);
break;
case 1:
dec_reward(to_literal(ci.m_trues), ci.m_weight);
break;
default:
break;
}
}
}
bool ddfw::should_restart() {
return m_flips >= m_restart_next;
}
void ddfw::do_restart() {
reinit_values();
init_clause_data();
m_restart_next += m_config.m_restart_base*get_luby(++m_restart_count);
}
/**
\brief the higher the bias, the lower the probability to deviate from the value of the bias
during a restart.
bias = 0 -> flip truth value with 50%
|bias| = 1 -> toss coin with 25% probability
|bias| = 2 -> toss coin with 12.5% probability
etc
*/
void ddfw::reinit_values() {
for (unsigned i = 0; i < num_vars(); ++i) {
int b = bias(i);
if (0 == (m_rand() % (1 + abs(b))))
value(i) = (m_rand() % 2) == 0;
else
value(i) = bias(i) > 0;
}
}
bool ddfw::should_parallel_sync() {
return m_par != nullptr && m_flips >= m_parsync_next;
}
void ddfw::save_priorities() {
m_probs.reset();
for (unsigned v = 0; v < num_vars(); ++v)
m_probs.push_back(-m_vars[v].m_reward_avg);
}
void ddfw::do_parallel_sync() {
if (m_par->from_solver(*this))
m_par->to_solver(*this);
++m_parsync_count;
m_parsync_next *= 3;
m_parsync_next /= 2;
}
void ddfw::save_model() {
m_model.reserve(num_vars());
for (unsigned i = 0; i < num_vars(); ++i)
m_model[i] = to_lbool(value(i));
save_priorities();
if (m_plugin)
m_plugin->on_save_model();
}
void ddfw::save_best_values() {
if (m_unsat.size() < m_min_sz || m_unsat.empty()) {
m_steps_since_progress = 0;
if (m_unsat.size() < 50 || m_min_sz * 10 > m_unsat.size() * 11)
save_model();
}
if (m_unsat.size() < m_min_sz) {
m_models.reset();
// skip saving the first model.
for (unsigned v = 0; v < num_vars(); ++v) {
int& b = bias(v);
if (abs(b) > 3) {
b = b > 0 ? 3 : -3;
}
}
}
unsigned h = value_hash();
unsigned occs = 0;
bool contains = m_models.find(h, occs);
if (!contains) {
for (unsigned v = 0; v < num_vars(); ++v)
bias(v) += value(v) ? 1 : -1;
if (m_models.size() > m_config.m_max_num_models)
m_models.erase(m_models.begin()->m_key);
}
m_models.insert(h, occs + 1);
if (occs > 100) {
m_restart_next = m_flips;
m_models.erase(h);
}
m_min_sz = m_unsat.size();
}
unsigned ddfw::value_hash() const {
unsigned s0 = 0, s1 = 0;
for (auto const& vi : m_vars) {
s0 += vi.m_value;
s1 += s0;
}
return s1;
}
/**
\brief Filter on whether to select a satisfied clause
1. with some probability prefer higher weight to lesser weight.
2. take into account number of trues ?
3. select multiple clauses instead of just one per clause in unsat.
*/
bool ddfw::select_clause(double max_weight, clause_info const& cn, unsigned& n) {
if (cn.m_num_trues == 0 || cn.m_weight + 1e-5 < max_weight)
return false;
if (cn.m_weight > max_weight) {
n = 2;
return true;
}
return (m_rand() % (n++)) == 0;
}
unsigned ddfw::select_max_same_sign(unsigned cf_idx) {
auto& ci = m_clauses[cf_idx];
unsigned cl = UINT_MAX; // clause pointer to same sign, max weight satisfied clause.
auto const& c = ci.m_clause;
double max_weight = m_init_weight;
unsigned n = 1;
for (literal lit : c) {
for (unsigned cn_idx : use_list(lit)) {
auto& cn = m_clauses[cn_idx];
if (select_clause(max_weight, cn, n)) {
cl = cn_idx;
max_weight = cn.m_weight;
}
}
}
return cl;
}
void ddfw::transfer_weight(unsigned from, unsigned to, double w) {
auto& cf = m_clauses[to];
auto& cn = m_clauses[from];
if (cn.m_weight < w)
return;
cf.m_weight += w;
cn.m_weight -= w;
for (literal lit : get_clause(to))
inc_reward(lit, w);
if (cn.m_num_trues == 1)
inc_reward(to_literal(cn.m_trues), w);
}
unsigned ddfw::select_random_true_clause() {
unsigned num_clauses = m_clauses.size();
unsigned rounds = 100 * num_clauses;
for (unsigned i = 0; i < rounds; ++i) {
unsigned idx = (m_rand() * m_rand()) % num_clauses;
auto & cn = m_clauses[idx];
if (cn.is_true() && cn.m_weight >= m_init_weight)
return idx;
}
return UINT_MAX;
}
// 1% chance to disregard neighbor
inline bool ddfw::disregard_neighbor() {
return false; // rand() % 1000 == 0;
}
double ddfw::calculate_transfer_weight(double w) {
return (w > m_init_weight) ? m_init_weight : 1;
}
void ddfw::shift_weights() {
++m_shifts;
for (unsigned to_idx : m_unsat) {
SASSERT(!m_clauses[to_idx].is_true());
unsigned from_idx = select_max_same_sign(to_idx);
if (from_idx == UINT_MAX || disregard_neighbor())
from_idx = select_random_true_clause();
if (from_idx == UINT_MAX)
continue;
auto & cn = m_clauses[from_idx];
SASSERT(cn.is_true());
double w = calculate_transfer_weight(cn.m_weight);
transfer_weight(from_idx, to_idx, w);
}
// DEBUG_CODE(invariant(););
}
std::ostream& ddfw::display(std::ostream& out) const {
unsigned num_cls = m_clauses.size();
for (unsigned i = 0; i < num_cls; ++i) {
out << get_clause(i) << " nt: ";
auto const& ci = m_clauses[i];
out << ci.m_num_trues << " w: " << ci.m_weight << "\n";
}
for (unsigned v = 0; v < num_vars(); ++v)
out << (is_true(literal(v, false)) ? "" : "-") << v << " rw: " << get_reward(v) << "\n";
out << "unsat vars: ";
for (bool_var v : m_unsat_vars)
out << v << " ";
out << "\n";
return out;
}
void ddfw::invariant() {
// every variable in unsat vars is in a false clause.
for (bool_var v : m_unsat_vars) {
bool found = false;
for (unsigned cl : m_unsat) {
for (literal lit : get_clause(cl)) {
if (lit.var() == v) { found = true; break; }
}
if (found) break;
}
if (!found) IF_VERBOSE(0, verbose_stream() << "unsat var not found: " << v << "\n"; );
VERIFY(found);
}
for (unsigned v = 0; v < num_vars(); ++v) {
double v_reward = 0;
literal lit(v, !value(v));
for (unsigned j : m_use_list[lit.index()]) {
clause_info const& ci = m_clauses[j];
if (ci.m_num_trues == 1) {
SASSERT(lit == to_literal(ci.m_trues));
v_reward -= ci.m_weight;
}
}
for (unsigned j : m_use_list[(~lit).index()]) {
clause_info const& ci = m_clauses[j];
if (ci.m_num_trues == 0) {
v_reward += ci.m_weight;
}
}
IF_VERBOSE(0, if (v_reward != reward(v)) verbose_stream() << v << " " << v_reward << " " << reward(v) << "\n");
// SASSERT(reward(v) == v_reward);
}
DEBUG_CODE(
for (auto const& ci : m_clauses) {
SASSERT(ci.m_weight > 0);
}
for (unsigned i = 0; i < m_clauses.size(); ++i) {
bool found = false;
for (literal lit : get_clause(i)) {
if (is_true(lit)) found = true;
}
SASSERT(found == !m_unsat.contains(i));
}
// every variable in a false clause is in unsat vars
for (unsigned cl : m_unsat) {
for (literal lit : get_clause(cl)) {
SASSERT(m_unsat_vars.contains(lit.var()));
}
});
}
void ddfw::updt_params(params_ref const& _p) {
sat_params p(_p);
m_config.m_init_clause_weight = p.ddfw_init_clause_weight();
m_config.m_use_reward_zero_pct = p.ddfw_use_reward_pct();
m_config.m_reinit_base = p.ddfw_reinit_base();
m_config.m_restart_base = p.ddfw_restart_base();
}
}

285
src/sat/sat_ddfw.h
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@ -1,285 +0,0 @@
/*++
Copyright (c) 2019 Microsoft Corporation
Module Name:
sat_ddfw.h
Abstract:
DDFW Local search module for clauses
Author:
Nikolaj Bjorner, Marijn Heule 2019-4-23
Notes:
http://www.ict.griffith.edu.au/~johnt/publications/CP2006raouf.pdf
--*/
#pragma once
#include "util/uint_set.h"
#include "util/rlimit.h"
#include "util/params.h"
#include "util/ema.h"
#include "util/sat_sls.h"
#include "util/map.h"
#include "sat/sat_types.h"
namespace sat {
class solver;
class parallel;
class local_search_plugin {
public:
virtual ~local_search_plugin() {}
virtual void init_search() = 0;
virtual void finish_search() = 0;
virtual double reward(bool_var v) = 0;
virtual void on_rescale() = 0;
virtual void on_save_model() = 0;
virtual void on_restart() = 0;
};
class ddfw : public i_local_search {
protected:
struct config {
config() { reset(); }
unsigned m_use_reward_zero_pct;
unsigned m_init_clause_weight;
unsigned m_max_num_models;
unsigned m_restart_base;
unsigned m_reinit_base;
unsigned m_parsync_base;
double m_itau;
void reset() {
m_init_clause_weight = 8;
m_use_reward_zero_pct = 15;
m_max_num_models = (1 << 10);
m_restart_base = 100333;
m_reinit_base = 10000;
m_parsync_base = 333333;
m_itau = 0.5;
}
};
struct var_info {
var_info() {}
bool m_internal = false;
bool m_value = false;
double m_reward = 0;
double m_last_reward = 0;
unsigned m_make_count = 0;
int m_bias = 0;
bool m_external = false;
ema m_reward_avg = 1e-5;
};
config m_config;
reslimit m_limit;
vector<clause_info> m_clauses;
literal_vector m_assumptions;
svector<var_info> m_vars; // var -> info
svector<double> m_probs; // var -> probability of flipping
svector<double> m_scores; // reward -> score
model m_model; // var -> best assignment
unsigned m_init_weight = 2;
vector<unsigned_vector> m_use_list;
unsigned_vector m_flat_use_list;
unsigned_vector m_use_list_index;
indexed_uint_set m_unsat;
indexed_uint_set m_unsat_vars; // set of variables that are in unsat clauses
random_gen m_rand;
unsigned m_num_non_binary_clauses = 0;
unsigned m_restart_count = 0, m_reinit_count = 0, m_parsync_count = 0;
uint64_t m_restart_next = 0, m_reinit_next = 0, m_parsync_next = 0;
uint64_t m_flips = 0, m_last_flips = 0, m_shifts = 0;
unsigned m_min_sz = 0, m_steps_since_progress = 0;
u_map<unsigned> m_models;
stopwatch m_stopwatch;
parallel* m_par;
scoped_ptr<local_search_plugin> m_plugin = nullptr;
void flatten_use_list();
/**
* TBD: map reward value to a score, possibly through an exponential function, such as
* exp(-tau/r), where tau > 0
*/
inline double score(double r) { return r; }
inline unsigned& make_count(bool_var v) { return m_vars[v].m_make_count; }
inline bool& value(bool_var v) { return m_vars[v].m_value; }
inline bool value(bool_var v) const { return m_vars[v].m_value; }
inline double& reward(bool_var v) { return m_vars[v].m_reward; }
inline double plugin_reward(bool_var v) { return is_external(v) ? (m_vars[v].m_last_reward = m_plugin->reward(v)) : reward(v); }
void set_external(bool_var v) { m_vars[v].m_external = true; }
inline bool is_external(bool_var v) const { return m_vars[v].m_external; }
inline int& bias(bool_var v) { return m_vars[v].m_bias; }
unsigned value_hash() const;
inline bool is_true(literal lit) const { return value(lit.var()) != lit.sign(); }
inline sat::literal_vector const& get_clause(unsigned idx) const { return m_clauses[idx].m_clause; }
inline double get_weight(unsigned idx) const { return m_clauses[idx].m_weight; }
inline bool is_true(unsigned idx) const { return m_clauses[idx].is_true(); }
void update_reward_avg(bool_var v) { m_vars[v].m_reward_avg.update(reward(v)); }
unsigned select_max_same_sign(unsigned cf_idx);
inline void inc_make(literal lit) {
bool_var v = lit.var();
if (make_count(v)++ == 0) m_unsat_vars.insert_fresh(v);
}
inline void dec_make(literal lit) {
bool_var v = lit.var();
if (--make_count(v) == 0) m_unsat_vars.remove(v);
}
inline void inc_reward(literal lit, double w) { reward(lit.var()) += w; }
inline void dec_reward(literal lit, double w) { reward(lit.var()) -= w; }
void check_with_plugin();
void check_without_plugin();
// flip activity
template<bool uses_plugin>
bool do_flip();
template<bool uses_plugin>
bool_var pick_var(double& reward);
template<bool uses_plugin>
bool apply_flip(bool_var v, double reward);
void save_best_values();
void save_model();
void save_priorities();
// shift activity
void shift_weights();
inline double calculate_transfer_weight(double w);
// reinitialize weights activity
bool should_reinit_weights();
void do_reinit_weights();
inline bool select_clause(double max_weight, clause_info const& cn, unsigned& n);
// restart activity
bool should_restart();
void do_restart();
void reinit_values();
unsigned select_random_true_clause();
// parallel integration
bool should_parallel_sync();
void do_parallel_sync();
void log();
void init(unsigned sz, literal const* assumptions);
void init_clause_data();
void invariant();
void del();
void add_assumptions();
inline void transfer_weight(unsigned from, unsigned to, double w);
inline bool disregard_neighbor();
public:
ddfw(): m_par(nullptr) {}
~ddfw() override;
void set_plugin(local_search_plugin* p) { m_plugin = p; }
lbool check(unsigned sz, literal const* assumptions, parallel* p) override;
void updt_params(params_ref const& p) override;
model const& get_model() const override { return m_model; }
reslimit& rlimit() override { return m_limit; }
void set_seed(unsigned n) override { m_rand.set_seed(n); }
void add(solver const& s) override;
bool get_value(bool_var v) const override { return value(v); }
std::ostream& display(std::ostream& out) const;
// for parallel integration
unsigned num_non_binary_clauses() const override { return m_num_non_binary_clauses; }
void reinit(solver& s, bool_vector const& phase) override;
void collect_statistics(statistics& st) const override {}
double get_priority(bool_var v) const override { return m_probs[v]; }
// access clause information and state of Boolean search
indexed_uint_set& unsat_set() { return m_unsat; }
vector<clause_info> const& clauses() const { return m_clauses; }
clause_info& get_clause_info(unsigned idx) { return m_clauses[idx]; }
void remove_assumptions();
void flip(bool_var v);
inline double get_reward(bool_var v) const { return m_vars[v].m_reward; }
void add(unsigned sz, literal const* c);
sat::bool_var add_var(bool is_internal = true);
// is this a variable that was added during initialization?
bool is_initial_var(sat::bool_var v) const {
return m_vars.size() > v && !m_vars[v].m_internal;
}
void reinit();
inline unsigned num_vars() const { return m_vars.size(); }
std::initializer_list<unsigned> use_list(literal lit) {
unsigned i = lit.index();
auto const* b = m_flat_use_list.data() + m_use_list_index[i];
auto const* e = m_flat_use_list.data() + m_use_list_index[i + 1];
return std::initializer_list(b, e);
}
};
}

90
src/sat/sat_ddfw_wrapper.cpp Normal file
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@ -0,0 +1,90 @@
/*++
Copyright (c) 2019 Microsoft Corporation
Module Name:
sat_ddfw_wrapper.cpp
*/
#include "sat/sat_ddfw_wrapper.h"
#include "sat/sat_solver.h"
#include "sat/sat_parallel.h"
namespace sat {
lbool ddfw_wrapper::check(unsigned sz, literal const* assumptions, parallel* p) {
flet<parallel*> _p(m_par, p);
m_ddfw.m_parallel_sync = nullptr;
if (m_par) {
m_ddfw.m_parallel_sync = [&]() -> bool {
if (should_parallel_sync()) {
do_parallel_sync();
return true;
}
else
return false;
};
}
return m_ddfw.check(sz, assumptions);
}
bool ddfw_wrapper::should_parallel_sync() {
return m_par != nullptr && m_ddfw.m_flips >= m_parsync_next;
}
void ddfw_wrapper::do_parallel_sync() {
if (m_par->from_solver(*this))
m_par->to_solver(*this);
++m_parsync_count;
m_parsync_next *= 3;
m_parsync_next /= 2;
}
void ddfw_wrapper::reinit(solver& s, bool_vector const& phase) {
add(s);
m_ddfw.add_assumptions();
for (unsigned v = 0; v < phase.size(); ++v) {
m_ddfw.value(v) = phase[v];
m_ddfw.reward(v) = 0;
m_ddfw.make_count(v) = 0;
}
m_ddfw.init_clause_data();
m_ddfw.flatten_use_list();
}
void ddfw_wrapper::add(solver const& s) {
m_ddfw.m_clauses.reset();
m_ddfw.m_use_list.reset();
m_ddfw.m_num_non_binary_clauses = 0;
unsigned trail_sz = s.init_trail_size();
for (unsigned i = 0; i < trail_sz; ++i) {
m_ddfw.add(1, s.m_trail.data() + i);
}
unsigned sz = s.m_watches.size();
for (unsigned l_idx = 0; l_idx < sz; ++l_idx) {
literal l1 = ~to_literal(l_idx);
watch_list const & wlist = s.m_watches[l_idx];
for (watched const& w : wlist) {
if (!w.is_binary_non_learned_clause())
continue;
literal l2 = w.get_literal();
if (l1.index() > l2.index())
continue;
literal ls[2] = { l1, l2 };
m_ddfw.add(2, ls);
}
}
for (clause* c : s.m_clauses)
m_ddfw.add(c->size(), c->begin());
}
}

89
src/sat/sat_ddfw_wrapper.h Normal file
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@ -0,0 +1,89 @@
/*++
Copyright (c) 2019 Microsoft Corporation
Module Name:
sat_ddfw_wrapper.h
--*/
#pragma once
#include "util/uint_set.h"
#include "util/rlimit.h"
#include "util/params.h"
#include "util/ema.h"
#include "util/sat_sls.h"
#include "util/map.h"
#include "ast/sls/sat_ddfw.h"
#include "sat/sat_types.h"
namespace sat {
class solver;
class parallel;
class ddfw_wrapper : public i_local_search {
protected:
ddfw m_ddfw;
parallel* m_par = nullptr;
unsigned m_parsync_count = 0;
uint64_t m_parsync_next = 0;
void do_parallel_sync();
bool should_parallel_sync();
public:
ddfw_wrapper() {}
~ddfw_wrapper() override {}
void set_plugin(local_search_plugin* p) { m_ddfw.set_plugin(p); }
lbool check(unsigned sz, literal const* assumptions, parallel* p) override;
void updt_params(params_ref const& p) override { m_ddfw.updt_params(p); }
model const& get_model() const override { return m_ddfw.get_model(); }
reslimit& rlimit() override { return m_ddfw.rlimit(); }
void set_seed(unsigned n) override { m_ddfw.set_seed(n); }
void add(solver const& s) override;
bool get_value(bool_var v) const override { return m_ddfw.get_value(v); }
std::ostream& display(std::ostream& out) const { return m_ddfw.display(out); }
// for parallel integration
unsigned num_non_binary_clauses() const override { return m_ddfw.num_non_binary_clauses(); }
void reinit(solver& s, bool_vector const& phase) override;
void collect_statistics(statistics& st) const override {}
double get_priority(bool_var v) const override { return m_ddfw.get_priority(v); }
// access clause information and state of Boolean search
indexed_uint_set& unsat_set() { return m_ddfw.unsat_set(); }
vector<clause_info> const& clauses() const { return m_ddfw.clauses(); }
clause_info& get_clause_info(unsigned idx) { return m_ddfw.get_clause_info(idx); }
void remove_assumptions() { m_ddfw.remove_assumptions(); }
void flip(bool_var v) { m_ddfw.flip(v); }
inline double get_reward(bool_var v) const { return m_ddfw.get_reward(v); }
void add(unsigned sz, literal const* c) { m_ddfw.add(sz, c); }
void reinit() { m_ddfw.reinit(); }
};
}

8
src/sat/sat_solver.cpp
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@ -29,7 +29,7 @@ Revision History:
#include "sat/sat_solver.h"
#include "sat/sat_integrity_checker.h"
#include "sat/sat_lookahead.h"
#include "sat/sat_ddfw.h"
#include "sat/sat_ddfw_wrapper.h"
#include "sat/sat_prob.h"
#include "sat/sat_anf_simplifier.h"
#include "sat/sat_cut_simplifier.h"
@ -1362,7 +1362,7 @@ namespace sat {
}
literal_vector _lits;
scoped_limits scoped_rl(rlimit());
m_local_search = alloc(ddfw);
m_local_search = alloc(ddfw_wrapper);
scoped_ls _ls(*this);
SASSERT(m_local_search);
m_local_search->add(*this);
@ -1439,7 +1439,7 @@ namespace sat {
lbool solver::do_ddfw_search(unsigned num_lits, literal const* lits) {
if (m_ext) return l_undef;
SASSERT(!m_local_search);
m_local_search = alloc(ddfw);
m_local_search = alloc(ddfw_wrapper);
return invoke_local_search(num_lits, lits);
}
@ -1480,7 +1480,7 @@ namespace sat {
vector<reslimit> lims(num_ddfw);
// set up ddfw search
for (int i = 0; i < num_ddfw; ++i) {
ddfw* d = alloc(ddfw);
ddfw_wrapper* d = alloc(ddfw_wrapper);
d->updt_params(m_params);
d->set_seed(m_config.m_random_seed + i);
d->add(*this);

2
src/sat/sat_solver.h
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@ -228,7 +228,7 @@ namespace sat {
friend class parallel;
friend class lookahead;
friend class local_search;
friend class ddfw;
friend class ddfw_wrapper;
friend class prob;
friend class unit_walk;
friend struct mk_stat;

1
src/sat/smt/arith_solver.h
View file

@ -28,7 +28,6 @@ Author:
#include "math/polynomial/algebraic_numbers.h"
#include "math/polynomial/polynomial.h"
#include "sat/smt/sat_th.h"
#include "sat/sat_ddfw.h"
namespace euf {
class solver;

5
src/sat/smt/sat_th.h
View file

@ -18,7 +18,6 @@ Author:
#include "util/top_sort.h"
#include "sat/smt/sat_smt.h"
#include "sat/sat_ddfw.h"
#include "ast/euf/euf_egraph.h"
#include "model/model.h"
#include "smt/params/smt_params.h"
@ -139,10 +138,6 @@ namespace euf {
virtual euf::enode_pair get_justification_eq(size_t j);
/**
* Local search interface
*/
virtual void set_bool_search(sat::ddfw* ddfw) {}
virtual void set_bounds_begin() {}

4
src/sat/smt/sls_solver.cpp
View file

@ -201,13 +201,13 @@ namespace sls {
void solver::run_local_search_async() {
if (m_ddfw) {
m_result = m_ddfw->check(0, nullptr, nullptr);
m_result = m_ddfw->check(0, nullptr);
m_completed = true;
}
}
void solver::run_local_search_sync() {
m_result = m_ddfw->check(0, nullptr, nullptr);
m_result = m_ddfw->check(0, nullptr);
local_search_done();
}

2
src/sat/smt/sls_solver.h
View file

@ -20,7 +20,7 @@ Author:
#include "util/rlimit.h"
#include "ast/sls/bv_sls.h"
#include "sat/smt/sat_th.h"
#include "sat/sat_ddfw.h"
#include "ast/sls/sat_ddfw.h"
#ifdef SINGLE_THREAD

3
src/sat/tactic/sat_tactic.cpp
View file

@ -16,13 +16,14 @@ Author:
Notes:
--*/
#include "params/sat_params.hpp"
#include "ast/ast_pp.h"
#include "model/model_v2_pp.h"
#include "tactic/tactical.h"
#include "sat/tactic/goal2sat.h"
#include "sat/tactic/sat2goal.h"
#include "sat/sat_solver.h"
#include "params/sat_params.hpp"
class sat_tactic : public tactic {