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Almost cleaned up version.

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This commit is contained in:
Andreas Froehlich 2014-04-22 00:32:45 +01:00 • committed by Christoph M. Wintersteiger
parent c56e55b230
commit de028e7a30
6 changed files with 315 additions and 2270 deletions
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156
src/tactic/sls/sls_compilation_settings.h
View file

@ -22,167 +22,13 @@ Notes:
#ifndef _SLS_COMPILATION_SETTINGS_H_
#define _SLS_COMPILATION_SETTINGS_H_
// which unsatisfied assertion is selected? only works with _FOCUS_ > 0
// 0 = random, 1 = #moves, 2 = assertion with min score, 3 = assertion with max score
#define _BFS_ 0
// how many terms are considered for variable selection?
// 0 = all terms (GSAT), 1 = only one top level assertion (WSAT), 2 = only one bottom level atom
#define _FOCUS_ 1
// probability of choosing the same assertion again in the next step
#define _PERC_STICKY_ 0
// do we use dirty unit propagation to get rid of nested top level assertions?
#define _DIRTY_UP_ 0
// shall we use additive weighting scheme?
#define _PAWS_ 5
#define _PAWS_INIT_ 40
// do we use restarts?
// 0 = no, 1 = use #moves, 2 = use #plateaus, 3 = use time
#define _RESTARTS_ 1
// limit of moves/plateaus/seconds until first restart occurs
#define _RESTART_LIMIT_ 100
// 0 = initialize with all zero, 1 initialize with random value
#define _RESTART_INIT_ 0
// 0 = even intervals, 1 = pseudo luby, 2 = real luby, 3 = armin, 4 = rapid, 5 = minisat
#define _RESTART_SCHEME_ 1
// base value c for armin restart scheme using c^inner - only applies for _RESTART_SCHEME_ 3
#define _RESTART_CONST_ARMIN_ 2.0
// timelimit
#define _TIMELIMIT_ 3600
// should score of conjunctions be calculated by average rather than max?
#define _SCORE_AND_AVG_ 0
// should score of discunctions be calculated by multiplication of the inverse score rather than min?
#define _SCORE_OR_MUL_ 0
// do we use some kind of variable neighbourhood-search?
// 0 = no, 1 = only consider flipping bits if no better score can be obtained otherwise, 2 = only consider flipping bits until a better score can be obtained
#define _VNS_ 0
// shall we check 2-bit flips in plateaus using Monte Carlo?
#define _VNS_MC_ 0
// how many 2-bit flips shall we try per bit?
#define _VNS_MC_TRIES_ 1
// shall we check another assertion if no improving step was found in the first one?
#define _VNS_REPICK_ 0
// what is the probability of doing so (percentage)?
#define _VNS_PERC_ 100
// do a decreasing move with percentage ...
#define _INSIST_PERC_ 0
// do we reduce the score of unsatisfied literals?
// 0 = no
// 1 = yes, by multiplying it with some factor
// 2 = yes, by squaring it
// 3 = yes, by setting it to zero
// 4 = by progessively increasing weight (_TIMELIMIT_ needs to be set appropriately!)
#define _WEIGHT_DIST_ 1
// the factor used for _WEIGHT_DIST_ = 1
#define _WEIGHT_DIST_FACTOR_ 0.5
// shall we toggle the weight after each restart?
#define _WEIGHT_TOGGLE_ 0
// do we use intensification steps in local minima? if so, how many?
#define _INTENSIFICATION_ 0
#define _INTENSIFICATION_TRIES_ 0
// what is the percentage of random moves in plateaus (instead of full randomization)?
#define _PERC_PLATEAU_MOVES_ 0
// shall we repick assertion when randomizing in a plateau or use the current one?
// 0 = use old one, 1 = repick according to usual scheme, 2 = repick randomly and force different one
#define _REPICK_ 1
// do we use some UCT-like scheme for assertion-selection? overrides _BFS_
#define _UCT_ 1
// how much diversification is used in the UCT-scheme?
#define _UCT_CONSTANT_ 20.0
// is uct clause selection probabilistic similar to variable selection in sparrow?
// 0 = no, 1 = yes, use uct-value, 2 = yes, use score-value (_UCT_CONSTANT_ = 0.0) with squared score
#define _PROBABILISTIC_UCT_ 0
// additive constants for probabilistic uct > 0
#define _UCT_EPS_ 0.0001
// shall we reset _UCT_ touched values after restart?
#define _UCT_RESET_ 0
// how shall we initialize the _UCT_ total touched counter?
// 0 = initialize with one, 1 = initialize with number of assertions
#define _UCT_INIT_ 0
// do we gradually reduce the touched values of _UCT_?
#define _UCT_FORGET_ 0
#define _UCT_FORGET_FACTOR_ 0.9
// shall we use addition/subtraction?
#define _USE_ADDSUB_ 1
// shall we try multilication and division by 2?
#define _USE_MUL2DIV2_ 0
// shall we try multiplication by 3?
#define _USE_MUL3_ 0
// shall we try unary minus (= inverting and incrementing)
#define _USE_UNARY_MINUS_ 0
// is random selection for assertions uniform? only works with _BFS_ = _UCT_ = 0
#define _UNIFORM_RANDOM_ 0
#define _USE_ADDSUB_ 0
// should we use unsat-structures as done in SLS 4 SAT instead for random or bfs selection?
#define _REAL_RS_ 0
#define _REAL_PBFS_ 0
// how many bits do we neglect in each iteration?
#define _SKIP_BITS_ 0
// when randomizing local, what is the probability for changing a single bit?
// 0 = use standard scheme and pick a new value at random (= 50), otherwise the value (as int) gives the percentage
#define _PERC_CHANGE_ 0
// do we use random steps for noise?
// 0 = no, 1 = randomize local, 2 = make random move
#define _TYPE_RSTEP_ 0
// with what probability _PERM_STEP_/1000 will the random step happen?
#define _PERM_RSTEP_ 0
// shall we use early pruning for incremental update?
#define _EARLY_PRUNE_ 1
// shall we use caching for top_score?
#define _CACHE_TOP_SCORE_ 1
#if ((_BFS_ > 0) + (_UCT_ > 0) + _UNIFORM_RANDOM_ + _REAL_RS_ + _REAL_PBFS_ > 1)
InvalidConfiguration;
#endif
#if (_PROBABILISTIC_UCT_ && !_UCT_)
InvalidConfiguration;
#endif
#if (_PERM_RSTEP_ && !_TYPE_RSTEP_)
InvalidConfiguration;
#endif
#if (_PERC_CHANGE_ == 50)
InvalidConfiguration;
#endif
#if (_PERC_STICKY_ && !_FOCUS_)
InvalidConfiguration;
#endif
#endif

1168
src/tactic/sls/sls_engine.cpp
View file

File diff suppressed because it is too large Load diff

89
src/tactic/sls/sls_engine.h
View file

@ -22,6 +22,7 @@ Notes:
#include"stopwatch.h"
#include"lbool.h"
#include"model_converter.h"
#include"goal.h"
#include"sls_compilation_settings.h"
#include"sls_tracker.h"
@ -35,17 +36,13 @@ public:
stopwatch m_stopwatch;
unsigned m_full_evals;
unsigned m_incr_evals;
unsigned m_moves, m_flips, m_incs, m_decs, m_invs, m_umins, m_mul2s, m_mul3s, m_div2s;
unsigned m_moves, m_flips, m_incs, m_decs, m_invs;
stats() :
m_restarts(0),
m_full_evals(0),
m_incr_evals(0),
m_moves(0),
m_umins(0),
m_mul2s(0),
m_mul3s(0),
m_div2s(0),
m_flips(0),
m_incs(0),
m_decs(0),
@ -71,14 +68,22 @@ protected:
bv_util m_bv_util;
sls_tracker m_tracker;
sls_evaluator m_evaluator;
ptr_vector<expr> m_assertions;
unsigned m_restart_limit;
unsigned m_max_restarts;
unsigned m_plateau_limit;
unsigned m_walksat;
unsigned m_walksat_repick;
unsigned m_wp;
unsigned m_vns_mc;
unsigned m_vns_repick;
unsigned m_paws_sp;
unsigned m_restart_base;
unsigned m_restart_next;
unsigned m_restart_init;
ptr_vector<mpz> m_old_values;
typedef enum { MV_FLIP = 0, MV_INC, MV_DEC, MV_INV, MV_UMIN, MV_MUL2, MV_MUL3, MV_DIV2 } move_type;
typedef enum { MV_FLIP = 0, MV_INC, MV_DEC, MV_INV } move_type;
public:
sls_engine(ast_manager & m, params_ref const & p);
@ -92,78 +97,46 @@ public:
void updt_params(params_ref const & _p);
void assert_expr(expr * e) { m_assertions.push_back(e); }
stats const & get_stats(void) { return m_stats; }
void reset_statistics(void) { m_stats.reset(); }
bool full_eval(goal_ref const & g, model & mdl);
bool full_eval(model & mdl);
void mk_add(unsigned bv_sz, const mpz & old_value, mpz & add_value, mpz & result);
void mk_mul2(unsigned bv_sz, const mpz & old_value, mpz & result);
void mk_div2(unsigned bv_sz, const mpz & old_value, mpz & result);
void mk_inc(unsigned bv_sz, const mpz & old_value, mpz & incremented);
void mk_dec(unsigned bv_sz, const mpz & old_value, mpz & decremented);
void mk_inv(unsigned bv_sz, const mpz & old_value, mpz & inverted);
void mk_flip(sort * s, const mpz & old_value, unsigned bit, mpz & flipped);
void mk_flip(sort * s, const mpz & old_value, unsigned bit, mpz & flipped);
double find_best_move(goal_ref const & g, ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value, unsigned & new_bit, move_type & move);
double find_best_move_lsb(goal_ref const & g, ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value, unsigned & new_bit, move_type & move);
double find_best_move_mc(goal_ref const & g, ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value);
double find_best_move_local(expr * e, ptr_vector<func_decl> & to_evaluate,
unsigned & best_const, mpz & best_value, unsigned & new_bit, move_type & move);
bool what_if(goal_ref const & g, expr * e, func_decl * fd, const mpz & temp,
double & best_score, mpz & best_value, unsigned i);
double find_best_move_local(goal_ref const & g, expr * e, func_decl * fd, mpz & best_value, unsigned i);
lbool search(goal_ref const & g);
lbool search(void);
lbool operator()();
void operator()(goal_ref const & g, model_converter_ref & mc);
protected:
void checkpoint();
lbool search_old(goal_ref const & g);
double get_restart_armin(unsigned cnt_restarts);
bool what_if(goal_ref const & g, func_decl * fd, const unsigned & fd_inx, const mpz & temp,
bool what_if(func_decl * fd, const unsigned & fd_inx, const mpz & temp,
double & best_score, unsigned & best_const, mpz & best_value);
bool what_if_new(goal_ref const & g, func_decl * fd, const unsigned & fd_inx, const mpz & temp,
double & best_score, unsigned & best_const, mpz & best_value);
double incremental_score_prune_new(goal_ref const & g, func_decl * fd, const mpz & new_value);
double top_score();
double rescore();
double serious_score(func_decl * fd, const mpz & new_value);
double incremental_score(func_decl * fd, const mpz & new_value);
bool what_if_local(expr * e, func_decl * fd, const unsigned & fd_inx, const mpz & temp,
double & best_score, unsigned & best_const, mpz & best_value);
double incremental_score_prune(func_decl * fd, const mpz & new_value);
double find_best_move(ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value, unsigned & new_bit, move_type & move);
double top_score(goal_ref const & g);
double rescore(goal_ref const & g);
double serious_score(goal_ref const & g, func_decl * fd, const mpz & new_value);
double incremental_score(goal_ref const & g, func_decl * fd, const mpz & new_value);
#if _EARLY_PRUNE_
double incremental_score_prune(goal_ref const & g, func_decl * fd, const mpz & new_value);
#endif
double find_best_move_vns(goal_ref const & g, ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value, unsigned & new_bit, move_type & move);
double find_best_move_mc(ptr_vector<func_decl> & to_evaluate, double score,
unsigned & best_const, mpz & best_value);
void mk_random_move(ptr_vector<func_decl> & unsat_constants);
void mk_random_move(goal_ref const & g);
bool handle_plateau(goal_ref const & g);
bool handle_plateau(goal_ref const & g, double old_score);
//inline double get_restart_armin(unsigned cnt_restarts);
inline unsigned check_restart(unsigned curr_value);
};
#endif
#endif

262
src/tactic/sls/sls_evaluator.h
View file

@ -81,11 +81,7 @@ public:
case OP_AND: {
m_mpz_manager.set(result, m_one);
for (unsigned i = 0; i < n_args; i++)
#if _DIRTY_UP_
if (m_mpz_manager.neq(m_tracker.get_value(args[i]), result) && !m_tracker.is_top_expr(args[i])) {
#else
if (m_mpz_manager.neq(m_tracker.get_value(args[i]), result)) {
#endif
m_mpz_manager.set(result, m_zero);
break;
}
@ -93,11 +89,7 @@ public:
}
case OP_OR: {
for (unsigned i = 0; i < n_args; i++)
#if _DIRTY_UP_
if (m_mpz_manager.neq(m_tracker.get_value(args[i]), result) || m_tracker.is_top_expr(args[i])) {
#else
if (m_mpz_manager.neq(m_tracker.get_value(args[i]), result)) {
#endif
m_mpz_manager.set(result, m_one);
break;
}
@ -105,16 +97,9 @@ public:
}
case OP_NOT: {
SASSERT(n_args == 1);
#if _DIRTY_UP_
if (m_tracker.is_top_expr(args[0]))
m_mpz_manager.set(result, m_zero);
else
m_mpz_manager.set(result, (m_mpz_manager.is_zero(m_tracker.get_value(args[0]))) ? m_one : m_zero);
#else
const mpz & child = m_tracker.get_value(args[0]);
SASSERT(m_mpz_manager.is_one(child) || m_mpz_manager.is_zero(child));
m_mpz_manager.set(result, (m_mpz_manager.is_zero(child)) ? m_one : m_zero);
#endif
break;
}
case OP_EQ: {
@ -545,9 +530,7 @@ public:
expr_fast_mark1 visited;
mpz new_value;
#if _EARLY_PRUNE_ || _CACHE_TOP_SCORE_
double new_score;
#endif
SASSERT(cur_depth < m_traversal_stack.size());
while (cur_depth != static_cast<unsigned>(-1)) {
@ -559,8 +542,7 @@ public:
(*this)(to_app(cur), new_value);
m_tracker.set_value(cur, new_value);
#if _REAL_RS_ || _REAL_PBFS_
//if (!m_tracker.has_uplinks(cur))
#if _REAL_RS_
if (m_tracker.is_top_expr(cur))
{
if (m_mpz_manager.eq(new_value,m_one))
@ -570,25 +552,12 @@ public:
}
#endif
new_score = m_tracker.score(cur);
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_
new_score = m_tracker.score(cur);
#if _CACHE_TOP_SCORE_
//if (!m_tracker.has_uplinks(cur))
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
#endif
m_tracker.set_score(cur, new_score);
m_tracker.set_score_prune(cur, new_score);
#else
#if _CACHE_TOP_SCORE_
new_score = m_tracker.score(cur);
//if (!m_tracker.has_uplinks(cur))
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);
#else
m_tracker.set_score(cur, m_tracker.score(cur));
#endif
#endif
if (m_tracker.has_uplinks(cur)) {
@ -617,9 +586,7 @@ public:
expr_fast_mark1 visited;
mpz new_value;
#if _EARLY_PRUNE_ || _CACHE_TOP_SCORE_
double new_score;
#endif
SASSERT(cur_depth < m_traversal_stack.size());
while (cur_depth != static_cast<unsigned>(-1)) {
@ -630,25 +597,12 @@ public:
(*this)(to_app(cur), new_value);
m_tracker.set_value(cur, new_value);
new_score = m_tracker.score(cur);
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_
new_score = m_tracker.score(cur);
#if _CACHE_TOP_SCORE_
//if (!m_tracker.has_uplinks(cur))
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
#endif
m_tracker.set_score(cur, new_score);
m_tracker.set_score_prune(cur, new_score);
#else
#if _CACHE_TOP_SCORE_
new_score = m_tracker.score(cur);
//if (!m_tracker.has_uplinks(cur))
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);
#else
m_tracker.set_score(cur, m_tracker.score(cur));
#endif
#endif
if (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
@ -684,11 +638,7 @@ public:
m_traversal_stack[cur_depth].push_back(ep);
if (cur_depth > max_depth) max_depth = cur_depth;
}
#if _REAL_RS_ || _REAL_PBFS_ || _PAWS_
run_serious_update(max_depth);
#else
run_update(max_depth);
#endif
}
void update(func_decl * fd, const mpz & new_value) {
@ -713,7 +663,6 @@ public:
run_serious_update(cur_depth);
}
#if _EARLY_PRUNE_
unsigned run_update_bool_prune(unsigned cur_depth) {
expr_fast_mark1 visited;
@ -727,19 +676,15 @@ public:
expr * cur = cur_depth_exprs[i];
new_score = m_tracker.score(cur);
#if _CACHE_TOP_SCORE_
//if (!m_tracker.has_uplinks(cur))
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
#endif
prune_score = m_tracker.get_score_prune(cur);
m_tracker.set_score(cur, new_score);
if ((new_score > prune_score) && (m_tracker.has_pos_occ(cur)))
//if ((new_score >= prune_score) && (m_tracker.has_pos_occ(cur)))
pot_benefits = 1;
if ((new_score <= prune_score) && (m_tracker.has_neg_occ(cur)))
//if ((new_score < prune_score) && (m_tracker.has_neg_occ(cur)))
pot_benefits = 1;
if (m_tracker.has_uplinks(cur)) {
@ -754,9 +699,6 @@ public:
}
}
}
else
{
}
}
cur_depth_exprs.reset();
@ -770,15 +712,11 @@ public:
for (unsigned i = 0; i < cur_size; i++) {
expr * cur = cur_depth_exprs[i];
#if _CACHE_TOP_SCORE_
new_score = m_tracker.score(cur);
//if (!m_tracker.has_uplinks(cur))
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);
#else
m_tracker.set_score(cur, m_tracker.score(cur));
#endif
if (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
for (unsigned j = 0; j < ups.size(); j++) {
@ -859,161 +797,18 @@ public:
}
return run_update_bool_prune(cur_depth);
}
#endif
unsigned run_update_bool_prune_new(unsigned cur_depth) {
expr_fast_mark1 visited;
double prune_score, new_score;
unsigned pot_benefits = 0;
SASSERT(cur_depth < m_traversal_stack_bool.size());
ptr_vector<expr> & cur_depth_exprs = m_traversal_stack_bool[cur_depth];
for (unsigned i = 0; i < cur_depth_exprs.size(); i++) {
expr * cur = cur_depth_exprs[i];
new_score = m_tracker.score(cur);
//if (!m_tracker.has_uplinks(cur))
if (m_tracker.is_top_expr(cur))
m_tracker.adapt_top_sum(cur, new_score, m_tracker.get_score(cur));
prune_score = m_tracker.get_score_prune(cur);
m_tracker.set_score(cur, new_score);
if ((new_score >= prune_score) && (m_tracker.has_pos_occ(cur)))
pot_benefits = 1;
if ((new_score < prune_score) && (m_tracker.has_neg_occ(cur)))
pot_benefits = 1;
if (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
for (unsigned j = 0; j < ups.size(); j++) {
expr * next = ups[j];
unsigned next_d = m_tracker.get_distance(next);
SASSERT(next_d < cur_depth);
if (!visited.is_marked(next)) {
m_traversal_stack_bool[next_d].push_back(next);
visited.mark(next);
}
}
}
else
{
}
}
cur_depth_exprs.reset();
cur_depth--;
while (cur_depth != static_cast<unsigned>(-1)) {
ptr_vector<expr> & cur_depth_exprs = m_traversal_stack_bool[cur_depth];
if (pot_benefits)
{
unsigned cur_size = cur_depth_exprs.size();
for (unsigned i = 0; i < cur_size; i++) {
expr * cur = cur_depth_exprs[i];
new_score = m_tracker.score(cur);
//if (!m_tracker.has_uplinks(cur))
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 (m_tracker.has_uplinks(cur)) {
ptr_vector<expr> & ups = m_tracker.get_uplinks(cur);
for (unsigned j = 0; j < ups.size(); j++) {
expr * next = ups[j];
unsigned next_d = m_tracker.get_distance(next);
SASSERT(next_d < cur_depth);
if (!visited.is_marked(next)) {
m_traversal_stack_bool[next_d].push_back(next);
visited.mark(next);
}
}
}
}
}
cur_depth_exprs.reset();
cur_depth--;
}
return pot_benefits;
}
unsigned update_prune_new(func_decl * fd, const mpz & new_value) {
m_tracker.set_value(fd, new_value);
expr * ep = m_tracker.get_entry_point(fd);
unsigned cur_depth = m_tracker.get_distance(ep);
if (m_traversal_stack_bool.size() <= cur_depth)
m_traversal_stack_bool.resize(cur_depth+1);
if (m_traversal_stack.size() <= cur_depth)
m_traversal_stack.resize(cur_depth+1);
if (m_manager.is_bool(ep))
m_traversal_stack_bool[cur_depth].push_back(ep);
else
{
m_traversal_stack[cur_depth].push_back(ep);
run_update_prune(cur_depth);
}
return run_update_bool_prune_new(cur_depth);
}
void randomize_local(ptr_vector<func_decl> & unsat_constants) {
// Randomize _all_ candidates:
//// bool did_something = false;
//for (unsigned i = 0; i < unsat_constants.size(); i++) {
// func_decl * fd = unsat_constants[i];
// mpz temp = m_tracker.get_random(fd->get_range());
// // if (m_mpz_manager.neq(temp, m_tracker.get_value(fd))) {
// // did_something = true;
// // }
// update(fd, temp);
// m_mpz_manager.del(temp);
//}
// Randomize _one_ candidate:
unsigned r = m_tracker.get_random_uint(16) % unsat_constants.size();
func_decl * fd = unsat_constants[r];
#if _PERC_CHANGE_
sort * srt = fd->get_range();
mpz temp;
if (m_manager.is_bool(srt))
m_mpz_manager.set(temp, (m_mpz_manager.is_zero(m_tracker.get_value(fd))) ? m_one : m_zero);
else
{
mpz temp2, mask;
unsigned bv_sz = m_bv_util.get_bv_size(srt);
m_mpz_manager.set(temp, m_tracker.get_value(fd));
for (unsigned bit = 0; bit < bv_sz; bit++)
if (m_tracker.get_random_uint(16) % 100 < _PERC_CHANGE_)
{
m_mpz_manager.set(mask, m_powers(bit));
m_mpz_manager.bitwise_xor(temp, mask, temp2);
m_mpz_manager.set(temp, temp2);
}
m_mpz_manager.del(mask);
m_mpz_manager.del(temp2);
}
#else
mpz temp = m_tracker.get_random(fd->get_range());
#endif
#if _REAL_RS_ || _REAL_PBFS_ || _PAWS_
serious_update(fd, temp);
#else
update(fd, temp);
#endif
m_mpz_manager.del(temp);
TRACE("sls", /*tout << "Randomization candidates: ";
for (unsigned i = 0; i < unsat_constants.size(); i++)
tout << unsat_constants[i]->get_name() << ", ";
tout << std::endl;*/
tout << "Randomization candidate: " << unsat_constants[r]->get_name() << std::endl;
TRACE("sls", tout << "Randomization candidate: " << unsat_constants[r]->get_name() << std::endl;
tout << "Locally randomized model: " << std::endl;
m_tracker.show_model(tout); );
@ -1023,36 +818,9 @@ public:
randomize_local(m_tracker.get_constants(e));
}
void randomize_local(goal_ref const & g, unsigned int flip) {
randomize_local(m_tracker.get_unsat_constants(g, flip));
void randomize_local(ptr_vector<expr> const & as) {
randomize_local(m_tracker.get_unsat_constants(as));
}
void randomize_local_n(goal_ref const & g, ptr_vector<func_decl> & unsat_constants) {
unsigned r = m_tracker.get_random_uint(16) % unsat_constants.size();
func_decl * fd = unsat_constants[r];
sort * srt = fd->get_range();
unsigned bv_sz = m_manager.is_bool(srt) ? 1 : m_bv_util.get_bv_size(srt);
mpz max_val = m_tracker.get_random(srt);
update(fd, max_val);
double max_score = m_tracker.get_top_sum() / g->size();
mpz temp_val;
double temp_score;
for (unsigned i = 1; i < 2; i++)
//for (unsigned i = 1; i < bv_sz; i++)
{
m_mpz_manager.set(temp_val, m_tracker.get_random(srt));
update(fd, temp_val);
temp_score = m_tracker.get_top_sum() / g->size();
if (temp_score > max_score)
{
m_mpz_manager.set(max_val, temp_val);
max_score = temp_score;
}
}
update(fd, max_val);
m_mpz_manager.del(temp_val);
m_mpz_manager.del(max_val);
}
};
#endif

6
src/tactic/sls/sls_tactic.cpp
View file

@ -1507,16 +1507,12 @@ tactic * mk_preamble(ast_manager & m, params_ref const & p) {
using_params(mk_simplify_tactic(m), simp2_p)),
using_params(mk_simplify_tactic(m), hoist_p),
mk_max_bv_sharing_tactic(m),
// Andreas: It would be cool to get rid of shared top level assertions but which simplification is doing this?
//mk_ctx_simplify_tactic(m, ctx_p),
// Andreas: This one at least eliminates top level duplicates ... but has very bad effects on performance!
//mk_simplify_tactic(m),
mk_nnf_tactic(m, p));
}
tactic * mk_qfbv_sls_tactic(ast_manager & m, params_ref const & p) {
tactic * t = and_then(mk_preamble(m, p), mk_sls_tactic(m));
// tactic * t = and_then(mk_simplify_tactic(m), mk_nnf_tactic(m, p), mk_sls_tactic(m));
//tactic * t = and_then(mk_simplify_tactic(m), mk_nnf_tactic(m, p), mk_sls_tactic(m));
t->updt_params(p);
return t;
}

904
src/tactic/sls/sls_tracker.h
View file

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