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Moved parameters to the right file. Almost clean.

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Andreas Froehlich 2014-04-23 14:52:18 +01:00 • committed by Christoph M. Wintersteiger
parent b5a9e0a1f5
commit c4fb21cca1
6 changed files with 52 additions and 52 deletions
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5
src/tactic/sls/sls_compilation_settings.h
View file

@ -22,10 +22,7 @@ Notes:
#ifndef _SLS_COMPILATION_SETTINGS_H_
#define _SLS_COMPILATION_SETTINGS_H_
// should we use unsat-structures as done in SLS 4 SAT instead for random or bfs selection?
// should we use unsat-structures as done in SLS 4 SAT?
#define _REAL_RS_ 0
// shall we use early pruning for incremental update?
#define _EARLY_PRUNE_ 1
#endif

38
src/tactic/sls/sls_engine.cpp
View file

@ -70,6 +70,8 @@ void sls_engine::updt_params(params_ref const & _p) {
m_restart_next = m_restart_base;
m_restart_init = p.restart_init();
m_early_prune = p.early_prune();
// Andreas: Would cause trouble because repick requires an assertion being picked before which is not the case in GSAT.
if (m_walksat_repick && !m_walksat)
NOT_IMPLEMENTED_YET();
@ -117,7 +119,7 @@ double sls_engine::top_score() {
m_tracker.set_top_sum(top_sum);
return top_sum / (double)sz;
return top_sum;
}
double sls_engine::rescore() {
@ -129,21 +131,21 @@ double sls_engine::rescore() {
double sls_engine::serious_score(func_decl * fd, const mpz & new_value) {
m_evaluator.serious_update(fd, new_value);
m_stats.m_incr_evals++;
return (m_tracker.get_top_sum() / m_assertions.size());
return m_tracker.get_top_sum();
}
double sls_engine::incremental_score(func_decl * fd, const mpz & new_value) {
m_evaluator.update(fd, new_value);
m_stats.m_incr_evals++;
return (m_tracker.get_top_sum() / m_assertions.size());
return m_tracker.get_top_sum();
}
double sls_engine::incremental_score_prune(func_decl * fd, const mpz & new_value) {
m_stats.m_incr_evals++;
if (m_evaluator.update_prune(fd, new_value))
return (m_tracker.get_top_sum() / m_assertions.size());
return m_tracker.get_top_sum();
else
return 0.0;
return -DBL_MAX;
}
// checks whether the score outcome of a given move is better than the previous score
@ -160,11 +162,11 @@ bool sls_engine::what_if(
m_mpz_manager.set(old_value, m_tracker.get_value(fd));
#endif
#if _EARLY_PRUNE_
double r = incremental_score_prune(fd, temp);
#else
double r = incremental_score(fd, temp);
#endif
double r;
if (m_early_prune)
r = incremental_score_prune(fd, temp);
else
r = incremental_score(fd, temp);
#ifdef Z3DEBUG
TRACE("sls_whatif", tout << "WHAT IF " << fd->get_name() << " WERE " << m_mpz_manager.to_string(temp) <<
" --> " << r << std::endl;);
@ -342,11 +344,8 @@ double sls_engine::find_best_move(
if (what_if(fd, i, temp, new_score, best_const, best_value))
move = MV_INV;
}
// reset to what it was before
double check = incremental_score(fd, old_value);
// Andreas: does not hold anymore now that we use top level score caching
//SASSERT(check == score);
incremental_score(fd, old_value);
}
m_mpz_manager.del(old_value);
@ -381,9 +380,8 @@ double sls_engine::find_best_move_mc(ptr_vector<func_decl> & to_evaluate, double
}
}
}
// reset to what it was before
double check = incremental_score(fd, old_value);
incremental_score(fd, old_value);
}
m_mpz_manager.del(old_value);
@ -408,7 +406,10 @@ lbool sls_engine::search() {
checkpoint();
m_stats.m_moves++;
if (m_stats.m_moves % m_restart_base == 0)
{
m_tracker.ucb_forget(m_assertions);
//score = rescore();
}
#if _REAL_RS_
//m_tracker.debug_real(g, m_stats.m_moves);
@ -425,7 +426,7 @@ lbool sls_engine::search() {
if (m_wp && m_tracker.get_random_uint(10) < m_wp)
{
mk_random_move(to_evaluate);
score = m_tracker.get_top_sum() / sz;
score = m_tracker.get_top_sum();
continue;
}
@ -465,7 +466,7 @@ lbool sls_engine::search() {
else
m_evaluator.randomize_local(to_evaluate);
score = m_tracker.get_top_sum() / m_assertions.size();
score = m_tracker.get_top_sum();
// update assertion weights if a weigthing is enabled (sp < 1024)
if (m_paws)
@ -513,7 +514,6 @@ void sls_engine::operator()(goal_ref const & g, model_converter_ref & mc) {
assert_expr(g->form(i));
verbose_stream() << "_REAL_RS_ " << _REAL_RS_ << std::endl;
verbose_stream() << "_EARLY_PRUNE_ " << _EARLY_PRUNE_ << std::endl;
lbool res = operator()();

3
src/tactic/sls/sls_engine.h
View file

@ -81,8 +81,7 @@ protected:
unsigned m_restart_base;
unsigned m_restart_next;
unsigned m_restart_init;
ptr_vector<mpz> m_old_values;
unsigned m_early_prune;
typedef enum { MV_FLIP = 0, MV_INC, MV_DEC, MV_INV } move_type;

5
src/tactic/sls/sls_evaluator.h
View file

@ -554,9 +554,7 @@ public:
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
m_tracker.set_score(cur, new_score);
#if _EARLY_PRUNE_
m_tracker.set_score_prune(cur, new_score);
#endif
if (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
@ -599,9 +597,6 @@ public:
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
m_tracker.set_score(cur, new_score);
#if _EARLY_PRUNE_
m_tracker.set_score_prune(cur, new_score);
#endif
if (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
for (unsigned j = 0; j < ups.size(); j++) {

20
src/tactic/sls/sls_params.pyg
View file

@ -2,7 +2,21 @@ def_module_params('sls',
export=True,
description='Experimental Stochastic Local Search Solver (for QFBV only).',
params=(max_memory_param(),
('restarts', UINT, UINT_MAX, '(max) number of restarts'),
('plateau_limit', UINT, 10, 'pleateau limit'),
('random_seed', UINT, 0, 'random seed')
('max_restarts', UINT, UINT_MAX, 'maximum number of restarts'),
('walksat', BOOL, 1, 'use walksat assertion selection (instead of gsat)'),
('walksat_ucb', BOOL, 1, 'use bandit heuristic for walksat assertion selection (instead of random)'),
('walksat_ucb_constant', DOUBLE, 20.0, 'the ucb constant c in the term score + c * f(touched)'),
('walksat_ucb_init', BOOL, 0, 'initialize total ucb touched to formula size'),
('walksat_ucb_forget', DOUBLE, 1.0, 'scale touched by this factor every base restart interval'),
('walksat_repick', BOOL, 1, 'repick assertion if randomizing in local minima'),
('scale_unsat', DOUBLE, 0.5, 'scale score of unsat expressions by this factor'),
('paws_init', UINT, 40, 'initial/minimum assertion weights'),
('paws_sp', UINT, 52, 'smooth assertion weights with probability paws_sp / 1024'),
('wp', UINT, 0, 'random walk with probability wp / 1024'),
('vns_mc', UINT, 0, 'in local minima, try Monte Carlo sampling vns_mc many 2-bit-flips per bit'),
('vns_repick', BOOL, 0, 'in local minima, try picking a different assertion (only for walksat)'),
('restart_base', UINT, 100, 'base restart interval given by moves per run'),
('restart_init', BOOL, 0, 'initialize to 0 or random value (= 1) after restart'),
('early_prune', BOOL, 1, 'use early pruning for score prediction'),
('random_seed', UINT, 0, 'random seed')
))

33
src/tactic/sls/sls_tracker.h
View file

@ -44,11 +44,9 @@ class sls_tracker {
unsynch_mpz_manager * m;
mpz value;
double score;
#if _EARLY_PRUNE_
double score_prune;
unsigned has_pos_occ;
unsigned has_neg_occ;
#endif
unsigned distance; // max distance from any root
unsigned touched;
value_score & operator=(const value_score & other) {
@ -122,6 +120,7 @@ public:
m_paws_init = p.paws_init();
}
/* Andreas: Tried to give some measure for the formula size by the following two methods but both are not used currently.
unsigned get_formula_size() {
return m_scores.size();
}
@ -145,7 +144,7 @@ public:
}
return sum / count;
}
}*/
inline void adapt_top_sum(expr * e, double add, double sub) {
m_top_sum += m_weights.find(e) * (add - sub);
@ -417,6 +416,8 @@ public:
}
}
/* Andreas: Used this at some point to have values for the non-top-level expressions.
However, it did not give better performance but even cause some additional m/o - is not used currently.
void initialize_recursive(init_proc proc, expr_mark visited, expr * e) {
if (m_manager.is_and(e) || m_manager.is_or(e)) {
app * a = to_app(e);
@ -445,7 +446,7 @@ public:
find_func_decls_proc ffd_proc(m_manager, m_constants_occ.find(e));
expr_fast_mark1 visited;
quick_for_each_expr(ffd_proc, visited, e);
}
}*/
void initialize(ptr_vector<expr> const & as) {
init_proc proc(m_manager, *this);
@ -455,8 +456,6 @@ public:
expr * e = as[i];
if (!m_top_expr.contains(e))
m_top_expr.insert(e);
else
printf("this is already in ...\n");
for_each_expr(proc, visited, e);
}
@ -464,7 +463,6 @@ public:
for (unsigned i = 0; i < sz; i++) {
expr * e = as[i];
// Andreas: Maybe not fully correct.
ptr_vector<func_decl> t;
m_constants_occ.insert_if_not_there(e, t);
find_func_decls_proc ffd_proc(m_manager, m_constants_occ.find(e));
@ -488,15 +486,16 @@ public:
for (unsigned i = 0; i < sz; i++)
{
expr * e = as[i];
if (!m_weights.contains(e))
// initialize weights
if (!m_weights.contains(e))
m_weights.insert(e, m_paws_init);
// positive/negative occurences used for early pruning
setup_occs(as[i]);
}
#if _EARLY_PRUNE_
for (unsigned i = 0; i < sz; i++)
setup_occs(as[i]);
#endif
// initialize ucb total touched value (individual ones are always initialized to 1)
m_touched = m_ucb_init ? as.size() : 1;
}
@ -738,7 +737,6 @@ public:
SASSERT(!negated);
app * a = to_app(n);
expr * const * args = a->get_args();
// Andreas: Seems to have no effect. Probably it is still too similar to the original version.
double max = 0.0;
for (unsigned i = 0; i < a->get_num_args(); i++) {
double cur = get_score(args[i]);
@ -764,7 +762,6 @@ public:
const mpz & v1 = get_value(arg1);
if (negated) {
//res = (m_mpz_manager.eq(v0, v1)) ? 0.5 * (m_bv_util.get_bv_size(arg0) - 1.0) / m_bv_util.get_bv_size(arg0) : 1.0;
res = (m_mpz_manager.eq(v0, v1)) ? 0.0 : 1.0;
TRACE("sls_score", tout << "V0 = " << m_mpz_manager.to_string(v0) << " ; V1 = " <<
m_mpz_manager.to_string(v1) << std::endl; );
@ -1051,10 +1048,8 @@ public:
// for (unsigned i = 0; i < m_where_false.size(); i++) {
// expr * e = m_list_false[i];
vscore = m_scores.find(e);
double q = vscore.score + m_ucb_constant * sqrt(log((double)m_touched) / vscore.touched);
#if _UCT_ == 3
double q = vscore.score + _UCT_CONSTANT_ * sqrt(log(m_touched)/vscore.touched) + (get_random_uint(16) * 0.1 / (2<<16));
#endif
//double q = vscore.score + m_ucb_constant * sqrt(log((double)m_touched) / vscore.touched);
double q = vscore.score + m_ucb_constant * sqrt(log((double)m_touched) / vscore.touched) + (get_random_uint(8) * 0.0000002);
if (q > max && m_mpz_manager.neq(get_value(e), m_one) ) { max = q; pos = i; }
}
if (pos == static_cast<unsigned>(-1))