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ortools-clone/ortools/sat/sat_inprocessing.cc

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// Copyright 2010-2022 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "ortools/sat/sat_inprocessing.h"
#include <algorithm>
#include <cmath>
#include <cstdint>
#include <deque>
#include <limits>
#include <utility>
#include <vector>
#include "absl/container/inlined_vector.h"
#include "absl/random/distributions.h"
#include "absl/types/span.h"
#include "ortools/base/logging.h"
#include "ortools/base/stl_util.h"
#include "ortools/base/strong_vector.h"
#include "ortools/base/timer.h"
#include "ortools/sat/clause.h"
#include "ortools/sat/drat_checker.h"
#include "ortools/sat/probing.h"
#include "ortools/sat/sat_base.h"
#include "ortools/sat/sat_decision.h"
#include "ortools/sat/sat_parameters.pb.h"
#include "ortools/sat/sat_solver.h"
#include "ortools/util/bitset.h"
#include "ortools/util/integer_pq.h"
#include "ortools/util/strong_integers.h"
#include "ortools/util/time_limit.h"
namespace operations_research {
namespace sat {
void PostsolveClauses::AddClauseWithSpecialLiteral(
Literal literal, absl::Span<const Literal> clause) {
bool found = false;
clauses.emplace_back(clause.begin(), clause.end());
for (int i = 0; i < clause.size(); ++i) {
if (clause[i] == literal) {
found = true;
std::swap(clauses.back()[0], clauses.back()[i]);
break;
}
}
CHECK(found);
}
#define RETURN_IF_FALSE(f) \
if (!(f)) return false;
bool Inprocessing::PresolveLoop(SatPresolveOptions options) {
WallTimer wall_timer;
wall_timer.Start();
const bool log_info = options.log_info || VLOG_IS_ON(1);
const bool log_round_info = VLOG_IS_ON(1);
// Mainly useful for development.
double probing_time = 0.0;
// We currently do the transformations in a given order and restart each time
// we did something to make sure that the earlier step cannot srengthen more.
// This might not be the best, but it is really good during development phase
// to make sure each individual functions is as incremental and as fast as
// possible.
const double start_dtime = time_limit_->GetElapsedDeterministicTime();
const double stop_dtime = start_dtime + options.deterministic_time_limit;
while (!time_limit_->LimitReached() &&
time_limit_->GetElapsedDeterministicTime() <= stop_dtime) {
CHECK_EQ(sat_solver_->CurrentDecisionLevel(), 0);
if (!LevelZeroPropagate()) return false;
// This one is fast since only newly fixed variables are considered.
implication_graph_->RemoveFixedVariables();
// This also prepare the stamping below so that we do that on a DAG and do
// not consider potential new implications added by
// RemoveFixedAndEquivalentVariables().
RETURN_IF_FALSE(DetectEquivalencesAndStamp(options.use_transitive_reduction,
log_round_info));
// TODO(user): This should/could be integrated with the stamping since it
// seems better to do just one loop instead of two over all clauses. Because
// of memory access. it isn't that clear though.
RETURN_IF_FALSE(RemoveFixedAndEquivalentVariables(log_round_info));
RETURN_IF_FALSE(stamping_simplifier_->DoOneRound(log_round_info));
// We wait for the fix-point to be reached before doing the other
// simplifications below.
if (MoreFixedVariableToClean() || MoreRedundantVariableToClean() ||
!implication_graph_->IsDag()) {
continue;
}
RETURN_IF_FALSE(SubsumeAndStrenghtenRound(log_round_info));
if (MoreFixedVariableToClean() || MoreRedundantVariableToClean() ||
!implication_graph_->IsDag()) {
continue;
}
// TODO(user): Combine the two? this way we don't create a full literal <->
// clause graph twice. It might make sense to reach the BCE fix point which
// is unique before each variable elimination.
blocked_clause_simplifier_->DoOneRound(log_round_info);
RETURN_IF_FALSE(bounded_variable_elimination_->DoOneRound(log_round_info));
RETURN_IF_FALSE(LevelZeroPropagate());
// Probing.
const double saved_wtime = wall_timer.Get();
const double time_left =
stop_dtime - time_limit_->GetElapsedDeterministicTime();
if (time_left <= 0) break;
ProbingOptions probing_options;
probing_options.log_info = log_round_info;
probing_options.deterministic_limit = time_left;
probing_options.extract_binary_clauses =
options.extract_binary_clauses_in_probing;
RETURN_IF_FALSE(FailedLiteralProbingRound(probing_options, model_));
probing_time += wall_timer.Get() - saved_wtime;
if (MoreFixedVariableToClean() || MoreRedundantVariableToClean() ||
!implication_graph_->IsDag()) {
continue;
}
break;
}
// TODO(user): Maintain the total number of literals in the watched clauses.
if (!LevelZeroPropagate()) return false;
LOG_IF(INFO, log_info)
<< "Presolve."
<< " num_fixed: " << trail_->Index()
<< " num_redundant: " << implication_graph_->num_redundant_literals() / 2
<< "/" << sat_solver_->NumVariables()
<< " num_implications: " << implication_graph_->num_implications()
<< " num_watched_clauses: " << clause_manager_->num_watched_clauses()
<< " dtime: " << time_limit_->GetElapsedDeterministicTime() - start_dtime
<< "/" << options.deterministic_time_limit
<< " wtime: " << wall_timer.Get()
<< " non-probing time: " << (wall_timer.Get() - probing_time);
return true;
}
bool Inprocessing::InprocessingRound() {
DCHECK_EQ(sat_solver_->CurrentDecisionLevel(), 0);
WallTimer wall_timer;
wall_timer.Start();
const bool log_info = true || VLOG_IS_ON(1);
const bool log_round_info = VLOG_IS_ON(1);
// Mainly useful for development.
double probing_time = 0.0;
const double start_dtime = time_limit_->GetElapsedDeterministicTime();
// Try to spend a given ratio of time in the inprocessing.
if (total_dtime_ > 0.1 * start_dtime) return true;
// We make sure we do not "pollute" the current saved polarities. We will
// restore them at the end.
//
// TODO(user): We should probably also disable the variable/clauses activity
// updates.
decision_policy_->MaybeEnablePhaseSaving(/*save_phase=*/false);
RETURN_IF_FALSE(DetectEquivalencesAndStamp(true, log_round_info));
RETURN_IF_FALSE(RemoveFixedAndEquivalentVariables(log_round_info));
RETURN_IF_FALSE(LevelZeroPropagate());
// Probing.
const double saved_wtime = wall_timer.Get();
ProbingOptions probing_options;
probing_options.log_info = log_round_info;
probing_options.deterministic_limit = 5;
probing_options.extract_binary_clauses = true;
RETURN_IF_FALSE(FailedLiteralProbingRound(probing_options, model_));
probing_time += wall_timer.Get() - saved_wtime;
RETURN_IF_FALSE(DetectEquivalencesAndStamp(true, log_round_info));
RETURN_IF_FALSE(RemoveFixedAndEquivalentVariables(log_round_info));
RETURN_IF_FALSE(LevelZeroPropagate());
RETURN_IF_FALSE(stamping_simplifier_->DoOneRound(log_round_info));
RETURN_IF_FALSE(RemoveFixedAndEquivalentVariables(log_round_info));
// TODO(user): Add a small wrapper function to time this.
RETURN_IF_FALSE(LevelZeroPropagate());
sat_solver_->MinimizeSomeClauses(/*decisions_budget=*/1000);
RETURN_IF_FALSE(LevelZeroPropagate());
RETURN_IF_FALSE(SubsumeAndStrenghtenRound(log_round_info));
RETURN_IF_FALSE(RemoveFixedAndEquivalentVariables(log_round_info));
blocked_clause_simplifier_->DoOneRound(log_round_info);
RETURN_IF_FALSE(bounded_variable_elimination_->DoOneRound(log_round_info));
RETURN_IF_FALSE(LevelZeroPropagate());
total_dtime_ += time_limit_->GetElapsedDeterministicTime() - start_dtime;
LOG_IF(INFO, log_info)
<< "Presolve."
<< " num_fixed: " << trail_->Index()
<< " num_redundant: " << implication_graph_->num_redundant_literals() / 2
<< "/" << sat_solver_->NumVariables()
<< " num_implications: " << implication_graph_->num_implications()
<< " num_watched_clauses: " << clause_manager_->num_watched_clauses()
<< " dtime: " << time_limit_->GetElapsedDeterministicTime() - start_dtime
<< " wtime: " << wall_timer.Get()
<< " non-probing time: " << (wall_timer.Get() - probing_time);
decision_policy_->MaybeEnablePhaseSaving(/*save_phase=*/true);
return true;
}
#undef RETURN_IF_FALSE
bool Inprocessing::MoreFixedVariableToClean() const {
const int64_t new_num_fixed_variables = trail_->Index();
return last_num_fixed_variables_ < new_num_fixed_variables;
}
bool Inprocessing::MoreRedundantVariableToClean() const {
const int64_t new_num_redundant_literals =
implication_graph_->num_redundant_literals();
return last_num_redundant_literals_ < new_num_redundant_literals;
}
bool Inprocessing::LevelZeroPropagate() {
CHECK_EQ(sat_solver_->CurrentDecisionLevel(), 0);
clause_manager_->AttachAllClauses();
return sat_solver_->Propagate();
}
// It make sense to do the pre-stamping right after the equivalence detection
// since it needs a DAG and can detect extra failed literal.
bool Inprocessing::DetectEquivalencesAndStamp(bool use_transitive_reduction,
bool log_info) {
if (!LevelZeroPropagate()) return false;
implication_graph_->RemoveFixedVariables();
if (!implication_graph_->IsDag()) {
// TODO(user): consider doing the transitive reduction after each SCC.
// It might be slow but we could try to make it more incremental to
// compensate and it should allow further reduction.
if (!implication_graph_->DetectEquivalences(log_info)) return false;
if (!LevelZeroPropagate()) return false;
if (use_transitive_reduction) {
if (!implication_graph_->ComputeTransitiveReduction(log_info)) {
return false;
}
if (!LevelZeroPropagate()) return false;
}
}
if (!stamping_simplifier_->ComputeStampsForNextRound(log_info)) return false;
return LevelZeroPropagate();
}
bool Inprocessing::RemoveFixedAndEquivalentVariables(bool log_info) {
// Preconditions.
//
// TODO(user): The level zero is required because we remove fixed variables
// but if we split this into two functions, we could rewrite clause at any
// level.
CHECK_EQ(sat_solver_->CurrentDecisionLevel(), 0);
if (!LevelZeroPropagate()) return false;
// Test if some work is needed.
//
// TODO(user): If only new fixed variables are there, we can use a faster
// function. We should also merge the code with the deletion code in
// sat_solver_.cc, but that require some refactoring of the dependence between
// files.
const int64_t new_num_redundant_literals =
implication_graph_->num_redundant_literals();
const int64_t new_num_fixed_variables = trail_->Index();
if (last_num_redundant_literals_ == new_num_redundant_literals &&
last_num_fixed_variables_ == new_num_fixed_variables) {
return true;
}
last_num_fixed_variables_ = new_num_fixed_variables;
last_num_redundant_literals_ = new_num_redundant_literals;
// Start the round.
WallTimer wall_timer;
wall_timer.Start();
int64_t num_removed_literals = 0;
int64_t num_inspected_literals = 0;
// We need this temporary vector for the DRAT proof settings, otherwise
// we could just have done an in-place transformation.
std::vector<Literal> new_clause;
// Used to mark clause literals.
const int num_literals(sat_solver_->NumVariables() * 2);
absl::StrongVector<LiteralIndex, bool> marked(num_literals, false);
clause_manager_->DeleteRemovedClauses();
clause_manager_->DetachAllClauses();
for (SatClause* clause : clause_manager_->AllClausesInCreationOrder()) {
bool removed = false;
bool need_rewrite = false;
// We first do a loop to see if there is anything to do.
for (const Literal l : clause->AsSpan()) {
if (assignment_.LiteralIsTrue(l)) {
// TODO(user): we should output literal to the proof right away,
// currently if we remove clauses before fixing literal the proof is
// wrong.
if (!clause_manager_->InprocessingFixLiteral(l)) return false;
clause_manager_->InprocessingRemoveClause(clause);
num_removed_literals += clause->size();
removed = true;
break;
}
if (assignment_.LiteralIsFalse(l) || implication_graph_->IsRedundant(l)) {
need_rewrite = true;
break;
}
}
num_inspected_literals += clause->size();
if (removed || !need_rewrite) continue;
num_inspected_literals += clause->size();
// Rewrite the clause.
new_clause.clear();
for (const Literal l : clause->AsSpan()) {
const Literal r = implication_graph_->RepresentativeOf(l);
if (marked[r.Index()] || assignment_.LiteralIsFalse(r)) {
continue;
}
if (marked[r.NegatedIndex()] || assignment_.LiteralIsTrue(r)) {
clause_manager_->InprocessingRemoveClause(clause);
num_removed_literals += clause->size();
removed = true;
break;
}
marked[r.Index()] = true;
new_clause.push_back(r);
}
// Restore marked.
for (const Literal l : new_clause) marked[l.Index()] = false;
if (removed) continue;
num_removed_literals += clause->size() - new_clause.size();
if (!clause_manager_->InprocessingRewriteClause(clause, new_clause)) {
return false;
}
}
// TODO(user): find a way to auto-tune that after a run on borg...
const double dtime = static_cast<double>(num_inspected_literals) * 1e-8;
time_limit_->AdvanceDeterministicTime(dtime);
LOG_IF(INFO, log_info) << "Cleanup. num_removed_literals: "
<< num_removed_literals << " dtime: " << dtime
<< " wtime: " << wall_timer.Get();
return true;
}
// TODO(user): Use better work limits, see SAT09.CRAFTED.ramseycube.Q3inK12
//
// TODO(user): Be more incremental, each time a clause is added/reduced track
// which literal are impacted? Also try to do orthogonal reductions from one
// round to the next.
bool Inprocessing::SubsumeAndStrenghtenRound(bool log_info) {
WallTimer wall_timer;
wall_timer.Start();
int64_t num_subsumed_clauses = 0;
int64_t num_removed_literals = 0;
int64_t num_inspected_signatures = 0;
int64_t num_inspected_literals = 0;
// We need this temporary vector for the DRAT proof settings, otherwise
// we could just have done an in-place transformation.
std::vector<Literal> new_clause;
// This function needs the watcher to be detached as we might remove some
// of the watched literals.
//
// TODO(user): We could do that only if we do some reduction, but this is
// quite fast though.
clause_manager_->DeleteRemovedClauses();
clause_manager_->DetachAllClauses();
// Process clause by increasing sizes.
// TODO(user): probably faster without the size indirection.
std::vector<SatClause*> clauses =
clause_manager_->AllClausesInCreationOrder();
std::sort(clauses.begin(), clauses.end(),
[](SatClause* a, SatClause* b) { return a->size() < b->size(); });
// Used to mark clause literals.
const LiteralIndex num_literals(sat_solver_->NumVariables() * 2);
SparseBitset<LiteralIndex> marked(num_literals);
// Clause index in clauses.
// TODO(user): Storing signatures here might be faster?
absl::StrongVector<LiteralIndex, absl::InlinedVector<int, 6>> one_watcher(
num_literals.value());
// Clause signatures in the same order as clauses.
std::vector<uint64_t> signatures(clauses.size());
std::vector<Literal> candidates_for_removal;
for (int clause_index = 0; clause_index < clauses.size(); ++clause_index) {
SatClause* clause = clauses[clause_index];
// TODO(user): Better abort limit. We could also limit the watcher sizes and
// never look at really long clauses. Note that for an easier
// incrementality, it is better to reach some kind of completion so we know
// what new stuff need to be done.
if (num_inspected_literals + num_inspected_signatures > 1e9) {
break;
}
// Check for subsumption, note that this currently ignore all clauses in the
// binary implication graphs. Stamping is doing some of that (and some also
// happen during probing), but we could consider only direct implications
// here and be a bit more exhaustive than what stamping do with them (at
// least for node with many incoming and outgoing implications).
//
// TODO(user): Do some reduction using binary clauses. Note that only clause
// that never propagated since last round need to be checked for binary
// subsumption.
// Compute hash and mark literals.
uint64_t signature = 0;
marked.SparseClearAll();
for (const Literal l : clause->AsSpan()) {
marked.Set(l.Index());
signature |= (uint64_t{1} << (l.Variable().value() % 64));
}
// Look for clause that subsumes this one. Note that because we inspect
// all one watcher lists for the literals of this clause, if a clause is
// included inside this one, it must appear in one of these lists.
bool removed = false;
candidates_for_removal.clear();
const uint64_t mask = ~signature;
for (const Literal l : clause->AsSpan()) {
num_inspected_signatures += one_watcher[l.Index()].size();
for (const int i : one_watcher[l.Index()]) {
if ((mask & signatures[i]) != 0) continue;
bool subsumed = true;
bool stengthen = true;
LiteralIndex to_remove = kNoLiteralIndex;
num_inspected_literals += clauses[i]->size();
for (const Literal o : clauses[i]->AsSpan()) {
if (!marked[o.Index()]) {
subsumed = false;
if (to_remove == kNoLiteralIndex && marked[o.NegatedIndex()]) {
to_remove = o.NegatedIndex();
} else {
stengthen = false;
break;
}
}
}
if (subsumed) {
++num_subsumed_clauses;
num_removed_literals += clause->size();
clause_manager_->InprocessingRemoveClause(clause);
removed = true;
break;
}
if (stengthen) {
CHECK_NE(kNoLiteralIndex, to_remove);
candidates_for_removal.push_back(Literal(to_remove));
}
}
if (removed) break;
}
if (removed) continue;
// For strengthenning we also need to check the negative watcher lists.
for (const Literal l : clause->AsSpan()) {
num_inspected_signatures += one_watcher[l.NegatedIndex()].size();
for (const int i : one_watcher[l.NegatedIndex()]) {
if ((mask & signatures[i]) != 0) continue;
bool stengthen = true;
num_inspected_literals += clauses[i]->size();
for (const Literal o : clauses[i]->AsSpan()) {
if (o == l.Negated()) continue;
if (!marked[o.Index()]) {
stengthen = false;
break;
}
}
if (stengthen) {
candidates_for_removal.push_back(l);
}
}
}
// Any literal here can be removed, but afterwards the other might not. For
// now we just remove the first one.
//
// TODO(user): remove first and see if other still removable. Alternatively
// use a "removed" marker and redo a check for each clause that simplifies
// this one? Or just remove the first one, and wait for next round.
if (!candidates_for_removal.empty()) {
new_clause.clear();
for (const Literal l : clause->AsSpan()) {
new_clause.push_back(l);
}
int new_size = 0;
for (const Literal l : new_clause) {
if (l == candidates_for_removal[0]) continue;
new_clause[new_size++] = l;
}
CHECK_EQ(new_size + 1, new_clause.size());
new_clause.resize(new_size);
num_removed_literals += clause->size() - new_clause.size();
if (!clause_manager_->InprocessingRewriteClause(clause, new_clause)) {
return false;
}
if (clause->size() == 0) continue;
// Recompute signature.
signature = 0;
for (const Literal l : clause->AsSpan()) {
signature |= (uint64_t{1} << (l.Variable().value() % 64));
}
}
// Register one literal to watch. Any literal works, but we choose the
// smallest list.
//
// TODO(user): No need to add this clause if we know it cannot subsume
// any new clause since last round. i.e. unchanged clause that do not
// contains any literals of newly added clause do not need to be added
// here. We can track two bitset in LiteralWatchers via a register
// mechanism:
// - literal of newly watched clauses since last clear.
// - literal of reduced clauses since last clear.
//
// Important: we can only use this clause to subsume/strenghten others if
// it cannot be deleted later.
if (!clause_manager_->IsRemovable(clause)) {
int min_size = std::numeric_limits<int32_t>::max();
LiteralIndex min_literal = kNoLiteralIndex;
for (const Literal l : clause->AsSpan()) {
if (one_watcher[l.Index()].size() < min_size) {
min_size = one_watcher[l.Index()].size();
min_literal = l.Index();
}
}
// TODO(user): We could/should sort the literal in this clause by
// using literals that appear in a small number of clauses first so that
// we maximize the chance of early abort in the critical loops above.
//
// TODO(user): We could also move the watched literal first so we always
// skip it.
signatures[clause_index] = signature;
one_watcher[min_literal].push_back(clause_index);
}
}
// We might have fixed variables, finish the propagation.
if (!LevelZeroPropagate()) return false;
// TODO(user): tune the deterministic time.
const double dtime = static_cast<double>(num_inspected_signatures) * 1e-8 +
static_cast<double>(num_inspected_literals) * 5e-9;
time_limit_->AdvanceDeterministicTime(dtime);
LOG_IF(INFO, log_info) << "Subsume. num_removed_literals: "
<< num_removed_literals
<< " num_subsumed: " << num_subsumed_clauses
<< " dtime: " << dtime
<< " wtime: " << wall_timer.Get();
return true;
}
bool StampingSimplifier::DoOneRound(bool log_info) {
WallTimer wall_timer;
wall_timer.Start();
dtime_ = 0.0;
num_subsumed_clauses_ = 0;
num_removed_literals_ = 0;
num_fixed_ = 0;
if (implication_graph_->literal_size() == 0) return true;
if (implication_graph_->num_implications() == 0) return true;
if (!stamps_are_already_computed_) {
// We need a DAG so that we don't have cycle while we sample the tree.
// TODO(user): We could probably deal with it if needed so that we don't
// need to do equivalence detection each time we want to run this.
implication_graph_->RemoveFixedVariables();
if (!implication_graph_->DetectEquivalences(log_info)) return true;
SampleTreeAndFillParent();
if (!ComputeStamps()) return false;
}
stamps_are_already_computed_ = false;
if (!ProcessClauses()) return false;
// Note that num_removed_literals_ do not count the literals of the subsumed
// clauses.
time_limit_->AdvanceDeterministicTime(dtime_);
log_info |= VLOG_IS_ON(1);
LOG_IF(INFO, log_info) << "Stamping. num_removed_literals: "
<< num_removed_literals_
<< " num_subsumed: " << num_subsumed_clauses_
<< " num_fixed: " << num_fixed_ << " dtime: " << dtime_
<< " wtime: " << wall_timer.Get();
return true;
}
bool StampingSimplifier::ComputeStampsForNextRound(bool log_info) {
WallTimer wall_timer;
wall_timer.Start();
dtime_ = 0.0;
num_fixed_ = 0;
if (implication_graph_->literal_size() == 0) return true;
if (implication_graph_->num_implications() == 0) return true;
implication_graph_->RemoveFixedVariables();
if (!implication_graph_->DetectEquivalences(log_info)) return true;
SampleTreeAndFillParent();
if (!ComputeStamps()) return false;
stamps_are_already_computed_ = true;
// TODO(user): compute some dtime, it is always zero currently.
time_limit_->AdvanceDeterministicTime(dtime_);
log_info |= VLOG_IS_ON(1);
LOG_IF(INFO, log_info) << "Prestamping."
<< " num_fixed: " << num_fixed_ << " dtime: " << dtime_
<< " wtime: " << wall_timer.Get();
return true;
}
void StampingSimplifier::SampleTreeAndFillParent() {
const int size = implication_graph_->literal_size();
CHECK(implication_graph_->IsDag()); // so we don't have cycle.
parents_.resize(size);
for (LiteralIndex i(0); i < size; ++i) {
parents_[i] = i; // default.
if (implication_graph_->IsRedundant(Literal(i))) continue;
if (assignment_.LiteralIsAssigned(Literal(i))) continue;
// TODO(user): Better algo to not select redundant parent.
//
// TODO(user): if parents_[x] = y, try not to have parents_[not(y)] = not(x)
// because this is not as useful for the simplification power.
//
// TODO(user): More generally, we could sample a parent while probing so
// that we consider all hyper binary implications (in the case we don't add
// them to the implication graph already).
const auto& children_of_not_l =
implication_graph_->DirectImplications(Literal(i).Negated());
if (children_of_not_l.empty()) continue;
for (int num_tries = 0; num_tries < 10; ++num_tries) {
const Literal candidate =
children_of_not_l[absl::Uniform<int>(*random_, 0,
children_of_not_l.size())]
.Negated();
if (implication_graph_->IsRedundant(candidate)) continue;
if (i == candidate.Index()) continue;
// We found an interesting parent.
parents_[i] = candidate.Index();
break;
}
}
}
bool StampingSimplifier::ComputeStamps() {
const int size = implication_graph_->literal_size();
// Compute sizes.
sizes_.assign(size, 0);
for (LiteralIndex i(0); i < size; ++i) {
if (parents_[i] == i) continue; // leaf.
sizes_[parents_[i]]++;
}
// Compute starts in the children_ vector for each node.
starts_.resize(size + 1); // We use a sentinel.
starts_[LiteralIndex(0)] = 0;
for (LiteralIndex i(1); i <= size; ++i) {
starts_[i] = starts_[i - 1] + sizes_[i - 1];
}
// Fill children. This messes up starts_.
children_.resize(size);
for (LiteralIndex i(0); i < size; ++i) {
if (parents_[i] == i) continue; // leaf.
children_[starts_[parents_[i]]++] = i;
}
// Reset starts to correct value.
for (LiteralIndex i(0); i < size; ++i) {
starts_[i] -= sizes_[i];
}
if (DEBUG_MODE) {
CHECK_EQ(starts_[LiteralIndex(0)], 0);
for (LiteralIndex i(1); i <= size; ++i) {
CHECK_EQ(starts_[i], starts_[i - 1] + sizes_[i - 1]);
}
}
// Perform a DFS from each root to compute the stamps.
int64_t stamp = 0;
first_stamps_.resize(size);
last_stamps_.resize(size);
marked_.assign(size, false);
for (LiteralIndex i(0); i < size; ++i) {
if (parents_[i] != i) continue; // Not a root.
DCHECK(!marked_[i]);
const LiteralIndex tree_root = i;
dfs_stack_.push_back(i);
while (!dfs_stack_.empty()) {
const LiteralIndex top = dfs_stack_.back();
if (marked_[top]) {
dfs_stack_.pop_back();
last_stamps_[top] = stamp++;
continue;
}
first_stamps_[top] = stamp++;
marked_[top] = true;
// Failed literal detection. If the negation of top is in the same
// tree, we can fix the LCA of top and its negation to false.
if (marked_[Literal(top).NegatedIndex()] &&
first_stamps_[Literal(top).NegatedIndex()] >=
first_stamps_[tree_root]) {
// Find the LCA.
const int first_stamp = first_stamps_[Literal(top).NegatedIndex()];
LiteralIndex lca = top;
while (first_stamps_[lca] > first_stamp) {
lca = parents_[lca];
}
++num_fixed_;
if (!clause_manager_->InprocessingFixLiteral(Literal(lca).Negated())) {
return false;
}
}
const int end = starts_[top + 1]; // Ok with sentinel.
for (int j = starts_[top]; j < end; ++j) {
DCHECK_NE(top, children_[j]); // We removed leaf self-loop.
DCHECK(!marked_[children_[j]]); // This is a tree.
dfs_stack_.push_back(children_[j]);
}
}
}
DCHECK_EQ(stamp, 2 * size);
return true;
}
bool StampingSimplifier::ProcessClauses() {
struct Entry {
int i; // Index in the clause.
bool is_negated; // Correspond to clause[i] or clause[i].Negated();
int start; // Note that all start stamps are different.
int end;
bool operator<(const Entry& o) const { return start < o.start; }
};
std::vector<int> to_remove;
std::vector<Literal> new_clause;
std::vector<Entry> entries;
clause_manager_->DeleteRemovedClauses();
clause_manager_->DetachAllClauses();
for (SatClause* clause : clause_manager_->AllClausesInCreationOrder()) {
const auto span = clause->AsSpan();
if (span.empty()) continue;
// Note that we might fix literal as we perform the loop here, so we do
// need to deal with them.
//
// For a and b in the clause, if not(a) => b is present, then the clause is
// subsumed. If a => b, then a can be removed, and if not(a) => not(b) then
// b can be removed. Nothing can be done if a => not(b).
entries.clear();
for (int i = 0; i < span.size(); ++i) {
if (assignment_.LiteralIsTrue(span[i])) {
clause_manager_->InprocessingRemoveClause(clause);
break;
}
if (assignment_.LiteralIsFalse(span[i])) continue;
entries.push_back({i, false, first_stamps_[span[i].Index()],
last_stamps_[span[i].Index()]});
entries.push_back({i, true, first_stamps_[span[i].NegatedIndex()],
last_stamps_[span[i].NegatedIndex()]});
}
if (clause->empty()) continue;
// The sort should be dominant.
if (!entries.empty()) {
const double n = static_cast<double>(entries.size());
dtime_ += 1.5e-8 * n * std::log(n);
std::sort(entries.begin(), entries.end());
}
Entry top_entry;
top_entry.end = -1; // Sentinel.
to_remove.clear();
for (const Entry& e : entries) {
if (e.end < top_entry.end) {
// We found an implication: top_entry => this entry.
const Literal lhs = top_entry.is_negated ? span[top_entry.i].Negated()
: span[top_entry.i];
const Literal rhs = e.is_negated ? span[e.i].Negated() : span[e.i];
DCHECK(ImplicationIsInTree(lhs, rhs));
if (top_entry.is_negated != e.is_negated) {
// Failed literal?
if (top_entry.i == e.i) {
++num_fixed_;
if (top_entry.is_negated) {
// not(span[i]) => span[i] so span[i] true.
// And the clause is satisfied (so we count as as subsumed).
if (!clause_manager_->InprocessingFixLiteral(span[top_entry.i])) {
return false;
}
} else {
// span[i] => not(span[i]) so span[i] false.
if (!clause_manager_->InprocessingFixLiteral(
span[top_entry.i].Negated())) {
return false;
}
to_remove.push_back(top_entry.i);
continue;
}
}
// not(a) => b : subsumption.
// a => not(b), we cannot deduce anything, but it might make sense
// to see if not(b) implies anything instead of just keeping
// top_entry. See TODO below.
if (top_entry.is_negated) {
num_subsumed_clauses_++;
clause_manager_->InprocessingRemoveClause(clause);
break;
}
} else {
CHECK_NE(top_entry.i, e.i);
if (top_entry.is_negated) {
// not(a) => not(b), we can remove b.
to_remove.push_back(e.i);
} else {
// a => b, we can remove a.
//
// TODO(user): Note that it is okay to still use top_entry, but we
// might miss the removal of b if b => c. Also the paper do things
// differently. Make sure we don't miss any simplification
// opportunites by not changing top_entry. Same in the other
// branches.
to_remove.push_back(top_entry.i);
}
}
} else {
top_entry = e;
}
}
if (clause->empty()) continue;
// Strengthen the clause.
if (!to_remove.empty() || entries.size() < span.size()) {
new_clause.clear();
gtl::STLSortAndRemoveDuplicates(&to_remove);
int to_remove_index = 0;
for (int i = 0; i < span.size(); ++i) {
if (to_remove_index < to_remove.size() &&
i == to_remove[to_remove_index]) {
++to_remove_index;
continue;
}
if (assignment_.LiteralIsTrue(span[i])) {
clause_manager_->InprocessingRemoveClause(clause);
continue;
}
if (assignment_.LiteralIsFalse(span[i])) continue;
new_clause.push_back(span[i]);
}
num_removed_literals_ += span.size() - new_clause.size();
if (!clause_manager_->InprocessingRewriteClause(clause, new_clause)) {
return false;
}
}
}
return true;
}
void BlockedClauseSimplifier::DoOneRound(bool log_info) {
WallTimer wall_timer;
wall_timer.Start();
dtime_ = 0.0;
num_blocked_clauses_ = 0;
num_inspected_literals_ = 0;
InitializeForNewRound();
while (!time_limit_->LimitReached() && !queue_.empty()) {
const Literal l = queue_.front();
in_queue_[l.Index()] = false;
queue_.pop_front();
ProcessLiteral(l);
}
// Release some memory.
literal_to_clauses_.clear();
dtime_ += 1e-8 * num_inspected_literals_;
time_limit_->AdvanceDeterministicTime(dtime_);
log_info |= VLOG_IS_ON(1);
LOG_IF(INFO, log_info) << "Blocked clause. num_blocked_clauses: "
<< num_blocked_clauses_ << " dtime: " << dtime_
<< " wtime: " << wall_timer.Get();
}
void BlockedClauseSimplifier::InitializeForNewRound() {
clauses_.clear();
clause_manager_->DeleteRemovedClauses();
clause_manager_->DetachAllClauses();
for (SatClause* c : clause_manager_->AllClausesInCreationOrder()) {
// We ignore redundant clause. This shouldn't cause any validity issue.
if (clause_manager_->IsRemovable(c)) continue;
clauses_.push_back(c);
}
const int num_literals = clause_manager_->literal_size();
// TODO(user): process in order of increasing number of clause that contains
// not(l)?
in_queue_.assign(num_literals, true);
for (LiteralIndex l(0); l < num_literals; ++l) {
queue_.push_back(Literal(l));
}
marked_.resize(num_literals);
DCHECK(
std::all_of(marked_.begin(), marked_.end(), [](bool b) { return !b; }));
// TODO(user): because we don't create new clause here we can use a flat
// vector for literal_to_clauses_.
literal_to_clauses_.clear();
literal_to_clauses_.resize(num_literals);
for (ClauseIndex i(0); i < clauses_.size(); ++i) {
for (const Literal l : clauses_[i]->AsSpan()) {
literal_to_clauses_[l.Index()].push_back(i);
}
num_inspected_literals_ += clauses_[i]->size();
}
}
void BlockedClauseSimplifier::ProcessLiteral(Literal current_literal) {
if (assignment_.LiteralIsAssigned(current_literal)) return;
if (implication_graph_->IsRemoved(current_literal)) return;
// We want to check first that this clause will resolve to trivial clause with
// all binary containing not(current_literal). So mark all literal l so that
// current_literal => l.
//
// TODO(user): We do not need to redo that each time we reprocess
// current_literal.
//
// TODO(user): Ignore redundant literals. That might require pushing
// equivalence to the postsolve stack though. Better to simply remove
// these equivalence if we are allowed to and update the postsolve then.
//
// TODO(user): Make this work in the presence of at most ones.
int num_binary = 0;
const std::vector<Literal>& implications =
implication_graph_->DirectImplications(current_literal);
for (const Literal l : implications) {
if (l == current_literal) continue;
++num_binary;
marked_[l.Index()] = true;
}
// TODO(user): We could also mark a small clause containing
// current_literal.Negated(), and make sure we only include in
// clauses_to_process clauses that resolve trivially with that clause.
std::vector<ClauseIndex> clauses_to_process;
for (const ClauseIndex i : literal_to_clauses_[current_literal.Index()]) {
if (clauses_[i]->empty()) continue;
// Blocked with respect to binary clause only? all marked binary should have
// their negation in clause.
//
// TODO(user): Abort if size left is too small.
if (num_binary > 0) {
if (clauses_[i]->size() <= num_binary) continue;
int num_with_negation_marked = 0;
for (const Literal l : clauses_[i]->AsSpan()) {
if (l == current_literal) continue;
if (marked_[l.NegatedIndex()]) {
++num_with_negation_marked;
}
}
num_inspected_literals_ += clauses_[i]->size();
if (num_with_negation_marked < num_binary) continue;
}
clauses_to_process.push_back(i);
}
// Clear marked.
for (const Literal l : implications) {
marked_[l.Index()] = false;
}
// TODO(user): There is a possible optimization: If we mark all literals of
// all the clause to process, we can check that each clause containing
// current_literal.Negated() contains at least one of these literal negated
// other than current_literal. Otherwise none of the clause are blocked.
//
// TODO(user): If a clause cannot be blocked because of another clause, then
// when we call ProcessLiteral(current_literal.Negated()) we can skip some
// inspection.
for (const ClauseIndex i : clauses_to_process) {
const auto c = clauses_[i]->AsSpan();
if (ClauseIsBlocked(current_literal, c)) {
// Reprocess all clauses that have a negated literal in this one as
// some might be blocked now.
//
// TODO(user): Maybe we can remember for which (literal, clause) pair this
// was used as a certificate for "not-blocked" and just reprocess those,
// but it might be memory intensive.
for (const Literal l : c) {
if (!in_queue_[l.NegatedIndex()]) {
in_queue_[l.NegatedIndex()] = true;
queue_.push_back(l.Negated());
}
}
// Add the clause to the postsolving set.
postsolve_->AddClauseWithSpecialLiteral(current_literal, c);
// We can remove a blocked clause.
++num_blocked_clauses_;
clause_manager_->InprocessingRemoveClause(clauses_[i]);
}
}
}
// Note that this assume that the binary clauses have already been checked.
bool BlockedClauseSimplifier::ClauseIsBlocked(
Literal current_literal, absl::Span<const Literal> clause) {
bool is_blocked = true;
for (const Literal l : clause) marked_[l.Index()] = true;
// TODO(user): For faster reprocessing of the same literal, we should move
// all clauses that are used in a non-blocked certificate first in the list.
for (const ClauseIndex i :
literal_to_clauses_[current_literal.NegatedIndex()]) {
if (clauses_[i]->empty()) continue;
bool some_marked = false;
for (const Literal l : clauses_[i]->AsSpan()) {
// TODO(user): we can be faster here by only updating it at the end?
++num_inspected_literals_;
if (l == current_literal.Negated()) continue;
if (marked_[l.NegatedIndex()]) {
some_marked = true;
break;
}
}
if (!some_marked) {
is_blocked = false;
break;
}
}
for (const Literal l : clause) marked_[l.Index()] = false;
return is_blocked;
}
bool BoundedVariableElimination::DoOneRound(bool log_info) {
WallTimer wall_timer;
wall_timer.Start();
dtime_ = 0.0;
num_inspected_literals_ = 0;
num_eliminated_variables_ = 0;
num_literals_diff_ = 0;
num_clauses_diff_ = 0;
num_simplifications_ = 0;
num_blocked_clauses_ = 0;
clauses_.clear();
clause_manager_->DeleteRemovedClauses();
clause_manager_->DetachAllClauses();
for (SatClause* c : clause_manager_->AllClausesInCreationOrder()) {
// We ignore redundant clause. This shouldn't cause any validity issue.
// TODO(user): but we shouldn't keep clauses containing removed literals.
// It is still valid to do so, but it should be less efficient.
if (clause_manager_->IsRemovable(c)) continue;
clauses_.push_back(c);
}
const int num_literals = clause_manager_->literal_size();
const int num_variables = num_literals / 2;
literal_to_clauses_.clear();
literal_to_clauses_.resize(num_literals);
literal_to_num_clauses_.assign(num_literals, 0);
for (ClauseIndex i(0); i < clauses_.size(); ++i) {
for (const Literal l : clauses_[i]->AsSpan()) {
literal_to_clauses_[l.Index()].push_back(i);
literal_to_num_clauses_[l.Index()]++;
}
num_inspected_literals_ += clauses_[i]->size();
}
const int saved_trail_index = trail_->Index();
propagation_index_ = trail_->Index();
need_to_be_updated_.clear();
in_need_to_be_updated_.resize(num_variables);
queue_.Reserve(num_variables);
for (BooleanVariable v(0); v < num_variables; ++v) {
if (assignment_.VariableIsAssigned(v)) continue;
if (implication_graph_->IsRemoved(Literal(v, true))) continue;
UpdatePriorityQueue(v);
}
marked_.resize(num_literals);
DCHECK(
std::all_of(marked_.begin(), marked_.end(), [](bool b) { return !b; }));
// TODO(user): add a local dtime limit for the corner case where this take too
// much time. We can adapt the limit depending on how much we want to spend on
// inprocessing.
while (!time_limit_->LimitReached() && !queue_.IsEmpty()) {
const BooleanVariable top = queue_.Top().var;
queue_.Pop();
// Make sure we fix variables first if needed. Note that because new binary
// clause might appear when we fix variables, we need a loop here.
//
// TODO(user): we might also find new equivalent variable l => var => l
// here, but for now we ignore those.
bool is_unsat = false;
if (!Propagate()) return false;
while (implication_graph_->FindFailedLiteralAroundVar(top, &is_unsat)) {
if (!Propagate()) return false;
}
if (is_unsat) return false;
if (!CrossProduct(top)) return false;
for (const BooleanVariable v : need_to_be_updated_) {
in_need_to_be_updated_[v] = false;
// Currently we never re-add top if we just processed it.
if (v != top) UpdatePriorityQueue(v);
}
in_need_to_be_updated_.clear();
need_to_be_updated_.clear();
}
implication_graph_->CleanupAllRemovedVariables();
// Remove all redundant clause containing a removed literal. This avoid to
// re-introduce a removed literal via conflict learning.
for (SatClause* c : clause_manager_->AllClausesInCreationOrder()) {
if (!clause_manager_->IsRemovable(c)) continue;
bool remove = false;
for (const Literal l : c->AsSpan()) {
if (implication_graph_->IsRemoved(l)) {
remove = true;
break;
}
}
if (remove) clause_manager_->InprocessingRemoveClause(c);
}
// Release some memory.
literal_to_clauses_.clear();
literal_to_num_clauses_.clear();
dtime_ += 1e-8 * num_inspected_literals_;
time_limit_->AdvanceDeterministicTime(dtime_);
log_info |= VLOG_IS_ON(1);
LOG_IF(INFO, log_info) << "BVE."
<< " num_fixed: "
<< trail_->Index() - saved_trail_index
<< " num_simplified_literals: " << num_simplifications_
<< " num_blocked_clauses_: " << num_blocked_clauses_
<< " num_eliminations: " << num_eliminated_variables_
<< " num_literals_diff: " << num_literals_diff_
<< " num_clause_diff: " << num_clauses_diff_
<< " dtime: " << dtime_
<< " wtime: " << wall_timer.Get();
return true;
}
bool BoundedVariableElimination::RemoveLiteralFromClause(
Literal lit, SatClause* sat_clause) {
num_literals_diff_ -= sat_clause->size();
resolvant_.clear();
for (const Literal l : sat_clause->AsSpan()) {
if (l == lit || assignment_.LiteralIsFalse(l)) {
literal_to_num_clauses_[l.Index()]--;
continue;
}
if (assignment_.LiteralIsTrue(l)) {
num_clauses_diff_--;
clause_manager_->InprocessingRemoveClause(sat_clause);
return true;
}
resolvant_.push_back(l);
}
if (!clause_manager_->InprocessingRewriteClause(sat_clause, resolvant_)) {
return false;
}
if (sat_clause->empty()) {
--num_clauses_diff_;
for (const Literal l : resolvant_) literal_to_num_clauses_[l.Index()]--;
} else {
num_literals_diff_ += sat_clause->size();
}
return true;
}
bool BoundedVariableElimination::Propagate() {
for (; propagation_index_ < trail_->Index(); ++propagation_index_) {
// Make sure we always propagate the binary clauses first.
if (!implication_graph_->Propagate(trail_)) return false;
const Literal l = (*trail_)[propagation_index_];
for (const ClauseIndex index : literal_to_clauses_[l.Index()]) {
if (clauses_[index]->empty()) continue;
num_clauses_diff_--;
num_literals_diff_ -= clauses_[index]->size();
clause_manager_->InprocessingRemoveClause(clauses_[index]);
}
literal_to_clauses_[l.Index()].clear();
for (const ClauseIndex index : literal_to_clauses_[l.NegatedIndex()]) {
if (clauses_[index]->empty()) continue;
if (!RemoveLiteralFromClause(l.Negated(), clauses_[index])) return false;
}
literal_to_clauses_[l.NegatedIndex()].clear();
}
return true;
}
// Note that we use the estimated size here to make it fast. It is okay if the
// order of elimination is not perfect... We can improve on this later.
int BoundedVariableElimination::NumClausesContaining(Literal l) {
return literal_to_num_clauses_[l.Index()] +
implication_graph_->DirectImplicationsEstimatedSize(l.Negated());
}
// TODO(user): Only enqueue variable that can be removed.
void BoundedVariableElimination::UpdatePriorityQueue(BooleanVariable var) {
if (assignment_.VariableIsAssigned(var)) return;
const int priority = -NumClausesContaining(Literal(var, true)) -
NumClausesContaining(Literal(var, false));
if (queue_.Contains(var.value())) {
queue_.ChangePriority({var, priority});
} else {
queue_.Add({var, priority});
}
}
void BoundedVariableElimination::DeleteClause(SatClause* sat_clause) {
const auto clause = sat_clause->AsSpan();
num_clauses_diff_--;
num_literals_diff_ -= clause.size();
// Update literal <-> clause graph.
for (const Literal l : clause) {
literal_to_num_clauses_[l.Index()]--;
if (!in_need_to_be_updated_[l.Variable()]) {
in_need_to_be_updated_[l.Variable()] = true;
need_to_be_updated_.push_back(l.Variable());
}
}
// Lazy deletion of the clause.
clause_manager_->InprocessingRemoveClause(sat_clause);
}
void BoundedVariableElimination::DeleteAllClausesContaining(Literal literal) {
for (const ClauseIndex i : literal_to_clauses_[literal.Index()]) {
const auto clause = clauses_[i]->AsSpan();
if (clause.empty()) continue;
postsolve_->AddClauseWithSpecialLiteral(literal, clause);
DeleteClause(clauses_[i]);
}
literal_to_clauses_[literal.Index()].clear();
}
void BoundedVariableElimination::AddClause(absl::Span<const Literal> clause) {
SatClause* pt = clause_manager_->InprocessingAddClause(clause);
if (pt == nullptr) return;
num_clauses_diff_++;
num_literals_diff_ += clause.size();
const ClauseIndex index(clauses_.size());
clauses_.push_back(pt);
for (const Literal l : clause) {
literal_to_num_clauses_[l.Index()]++;
literal_to_clauses_[l.Index()].push_back(index);
if (!in_need_to_be_updated_[l.Variable()]) {
in_need_to_be_updated_[l.Variable()] = true;
need_to_be_updated_.push_back(l.Variable());
}
}
}
template <bool score_only, bool with_binary_only>
bool BoundedVariableElimination::ResolveAllClauseContaining(Literal lit) {
const int clause_weight = parameters_.presolve_bve_clause_weight();
const std::vector<Literal>& implications =
implication_graph_->DirectImplications(lit);
auto& clause_containing_lit = literal_to_clauses_[lit.Index()];
for (int i = 0; i < clause_containing_lit.size(); ++i) {
const ClauseIndex clause_index = clause_containing_lit[i];
const auto clause = clauses_[clause_index]->AsSpan();
if (clause.empty()) continue;
if (!score_only) resolvant_.clear();
for (const Literal l : clause) {
if (!score_only && l != lit) resolvant_.push_back(l);
marked_[l.Index()] = true;
}
DCHECK(marked_[lit.Index()]);
num_inspected_literals_ += clause.size() + implications.size();
// If this is true, then "clause" is subsumed by one of its resolvant and we
// can just remove lit from it. Then it doesn't need to be acounted at all.
bool clause_can_be_simplified = false;
const int64_t saved_score = new_score_;
// Resolution with binary clauses.
for (const Literal l : implications) {
CHECK_NE(l, lit);
if (marked_[l.NegatedIndex()]) continue; // trivial.
if (marked_[l.Index()]) {
clause_can_be_simplified = true;
break;
} else {
if (score_only) {
new_score_ += clause_weight + clause.size();
} else {
resolvant_.push_back(l);
AddClause(resolvant_);
resolvant_.pop_back();
}
}
}
// Resolution with non-binary clauses.
if (!with_binary_only && !clause_can_be_simplified) {
auto& clause_containing_not_lit = literal_to_clauses_[lit.NegatedIndex()];
for (int j = 0; j < clause_containing_not_lit.size(); ++j) {
if (score_only && new_score_ > score_threshold_) break;
const ClauseIndex other_index = clause_containing_not_lit[j];
const auto other = clauses_[other_index]->AsSpan();
if (other.empty()) continue;
bool trivial = false;
int extra_size = 0;
for (const Literal l : other) {
// TODO(user): we can optimize this by updating it outside the loop.
++num_inspected_literals_;
if (l == lit.Negated()) continue;
if (marked_[l.NegatedIndex()]) {
trivial = true;
break;
}
if (!marked_[l.Index()]) {
++extra_size;
if (!score_only) resolvant_.push_back(l);
}
}
if (trivial) {
if (!score_only) resolvant_.resize(resolvant_.size() - extra_size);
continue;
}
// If this is the case, the other clause is subsumed by the resolvant.
// We can just remove not_lit from it and ignore it.
if (score_only && clause.size() + extra_size <= other.size()) {
// TODO(user): We should have an exact equality here, except if
// presolve is off before the clause are added to the sat solver and
// we have duplicate literals. The code should still work but it
// wasn't written with that in mind nor tested like this, so we should
// just enforce the invariant.
if (false) DCHECK_EQ(clause.size() + extra_size, other.size());
++num_simplifications_;
// Note that we update the threshold since this clause was counted in
// it.
score_threshold_ -= clause_weight + other.size();
if (extra_size == 0) {
// We have a double self-subsumption. We can just remove this
// clause since it will be subsumed by the clause created in the
// "clause_can_be_simplified" case below.
DeleteClause(clauses_[other_index]);
} else {
if (!RemoveLiteralFromClause(lit.Negated(),
clauses_[other_index])) {
return false;
}
std::swap(clause_containing_not_lit[j],
clause_containing_not_lit.back());
clause_containing_not_lit.pop_back();
--j; // Reprocess the new position.
continue;
}
}
if (extra_size == 0) {
clause_can_be_simplified = true;
break;
} else {
if (score_only) {
// Hack. We do not want to create long clauses during BVE.
if (clause.size() - 1 + extra_size > 100) {
new_score_ = score_threshold_ + 1;
break;
}
new_score_ += clause_weight + clause.size() - 1 + extra_size;
} else {
AddClause(resolvant_);
resolvant_.resize(resolvant_.size() - extra_size);
}
}
}
}
// Note that we need to clear marked before aborting.
for (const Literal l : clause) marked_[l.Index()] = false;
// In this case, we simplify and remove the clause from here.
if (clause_can_be_simplified) {
++num_simplifications_;
// Note that we update the threshold as if this was simplified before.
new_score_ = saved_score;
score_threshold_ -= clause_weight + clause.size();
if (!RemoveLiteralFromClause(lit, clauses_[clause_index])) return false;
std::swap(clause_containing_lit[i], clause_containing_lit.back());
clause_containing_lit.pop_back();
--i; // Reprocess the new position.
}
if (score_only && new_score_ > score_threshold_) return true;
// When this happen, then the clause is blocked (i.e. all its resolvant are
// trivial). So even if we do not actually perform the variable elimination,
// we can still remove this clause. Note that we treat the score as if the
// clause was removed before.
//
// Tricky: The detection only work if we didn't abort the computation above,
// so we do that after the score_threshold_ check.
//
// TODO(user): Also detect blocked clause for not(lit)? It is not as cheap
// though and require more code.
if (score_only && !with_binary_only && !clause_can_be_simplified &&
new_score_ == saved_score) {
++num_blocked_clauses_;
score_threshold_ -= clause_weight + clause.size();
postsolve_->AddClauseWithSpecialLiteral(lit, clause);
DeleteClause(clauses_[clause_index]);
}
}
return true;
}
bool BoundedVariableElimination::CrossProduct(BooleanVariable var) {
if (assignment_.VariableIsAssigned(var)) return true;
const Literal lit(var, true);
const Literal not_lit(var, false);
{
const int s1 = NumClausesContaining(lit);
const int s2 = NumClausesContaining(not_lit);
if (s1 == 0 && s2 == 0) return true;
if (s1 > 0 && s2 == 0) {
num_eliminated_variables_++;
if (!clause_manager_->InprocessingFixLiteral(lit)) return false;
DeleteAllClausesContaining(lit);
return true;
}
if (s1 == 0 && s2 > 0) {
num_eliminated_variables_++;
if (!clause_manager_->InprocessingFixLiteral(not_lit)) return false;
DeleteAllClausesContaining(not_lit);
return true;
}
if (implication_graph_->IsRedundant(lit)) {
// TODO(user): do that elsewhere?
CHECK_EQ(s1, 1);
CHECK_EQ(s2, 1);
CHECK_EQ(implication_graph_->NumImplicationOnVariableRemoval(var), 0);
num_eliminated_variables_++;
implication_graph_->RemoveBooleanVariable(var, &postsolve_->clauses);
return true;
}
// Heuristic. Abort if the work required to decide if var should be removed
// seems to big.
if (s1 > 1 && s2 > 1 && s1 * s2 > parameters_.presolve_bve_threshold()) {
return true;
}
}
// TODO(user): swap lit and not_lit for speed? it is unclear if we prefer
// to minimize the number of clause containing lit or not_lit though. Also,
// we might want to alternate since we also detect blocked clause containing
// lit, but don't do it for not_lit.
// Compute the current score.
// TODO(user): cleanup the list lazily at the same time?
int64_t score = 0;
const int clause_weight = parameters_.presolve_bve_clause_weight();
score +=
implication_graph_->DirectImplications(lit).size() * (clause_weight + 2);
score += implication_graph_->DirectImplications(not_lit).size() *
(clause_weight + 2);
for (const ClauseIndex i : literal_to_clauses_[lit.Index()]) {
const auto c = clauses_[i]->AsSpan();
if (!c.empty()) score += clause_weight + c.size();
}
for (const ClauseIndex i : literal_to_clauses_[not_lit.Index()]) {
const auto c = clauses_[i]->AsSpan();
if (!c.empty()) score += clause_weight + c.size();
}
// Compute the new score after BVE.
// Abort as soon as it crosses the threshold.
//
// TODO(user): Experiment with leaving the implications graph as is. This will
// not remove the variable completely, but it seems interesting since after
// equivalent variable removal and failed literal probing, the cross product
// of the implication always add a quadratic number of implication, except if
// the in (or out) degree is zero or one.
score_threshold_ = score;
new_score_ = implication_graph_->NumImplicationOnVariableRemoval(var) *
(clause_weight + 2);
if (new_score_ > score_threshold_) return true;
if (!ResolveAllClauseContaining</*score_only=*/true,
/*with_binary_only=*/true>(not_lit)) {
return false;
}
if (new_score_ > score_threshold_) return true;
if (!ResolveAllClauseContaining</*score_only=*/true,
/*with_binary_only=*/false>(lit)) {
return false;
}
if (new_score_ > score_threshold_) return true;
// Perform BVE.
if (new_score_ > 0) {
if (!ResolveAllClauseContaining</*score_only=*/false,
/*with_binary_only=*/false>(lit)) {
return false;
}
if (!ResolveAllClauseContaining</*score_only=*/false,
/*with_binary_only=*/true>(not_lit)) {
return false;
}
}
++num_eliminated_variables_;
implication_graph_->RemoveBooleanVariable(var, &postsolve_->clauses);
DeleteAllClausesContaining(lit);
DeleteAllClausesContaining(not_lit);
return true;
}
} // namespace sat
} // namespace operations_research
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