666 lines
31 KiB
C
666 lines
31 KiB
C
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/***************************************************************************************[Solver.cc]
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MiniSat -- Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
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Copyright (c) 2007-2010, Niklas Sorensson
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Chanseok Oh's MiniSat Patch Series -- Copyright (c) 2015, Chanseok Oh
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Maple_LCM, Based on MapleCOMSPS_DRUP -- Copyright (c) 2017, Mao Luo, Chu-Min LI, Fan Xiao: implementing a learnt clause minimisation approach
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Reference: M. Luo, C.-M. Li, F. Xiao, F. Manya, and Z. L. , “An effective learnt clause minimization approach for cdcl sat solvers,” in IJCAI-2017, 2017, pp. to–appear.
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Maple_LCM_Dist, Based on Maple_LCM -- Copyright (c) 2017, Fan Xiao, Chu-Min LI, Mao Luo: using a new branching heuristic called Distance at the beginning of search
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MapleLCMDistChronoBT, based on Maple_LCM_Dist -- Copyright (c), Alexander Nadel, Vadim Ryvchin: "Chronological Backtracking" in SAT-2018, pp. 111-121.
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MapleLCMDistChronoBT-DL, based on MapleLCMDistChronoBT -- Copyright (c), Stepan Kochemazov, Oleg Zaikin, Victor Kondratiev, Alexander Semenov: The solver was augmented with heuristic that moves duplicate learnt clauses into the core/tier2 tiers depending on a number of parameters.
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lstech, Relaxed_newTech -- Copyright (c) 2019-2021, Shaowei Cai, Xindi Zhang
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Reference: Shaowei Cai, Xindi Zhang: Deep Cooperation of CDCL and Local Search for SAT.
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Xindi Zhang, Shaowei Cai: Relaxed Backtracking with Rephasing.
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Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
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associated documentation files (the "Software"), to deal in the Software without restriction,
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including without limitation the rights to use, copy, modify, merge, publish, distribute,
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sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all copies or
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substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
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NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
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DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT
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OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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**************************************************************************************************/
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#ifndef Minisat_Solver_h
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#define Minisat_Solver_h
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#define ANTI_EXPLORATION
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#define BIN_DRUP
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#define GLUCOSE23
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//#define INT_QUEUE_AVG
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//#define LOOSE_PROP_STAT
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#ifdef GLUCOSE23
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#define INT_QUEUE_AVG
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#define LOOSE_PROP_STAT
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#endif
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#include "mtl/Vec.h"
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#include "mtl/Heap.h"
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#include "mtl/Alg.h"
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#include "utils/Options.h"
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#include "core/SolverTypes.h"
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#include "utils/ccnr.h"
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// duplicate learnts version
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#include <chrono>
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#include <vector>
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#include <unordered_map>
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#include <unordered_set>
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#include <set>
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#include <map>
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#include <algorithm>
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// duplicate learnts version
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// Don't change the actual numbers.
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#define LOCAL 0
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#define TIER2 2
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#define CORE 3
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namespace Minisat {
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//=================================================================================================
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// Solver -- the main class:
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class Solver {
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private:
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template<typename T>
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class MyQueue {
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int max_sz, q_sz;
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int ptr;
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int64_t sum;
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vec<T> q;
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public:
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MyQueue(int sz) : max_sz(sz), q_sz(0), ptr(0), sum(0) { assert(sz > 0); q.growTo(sz); }
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inline bool full () const { return q_sz == max_sz; }
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#ifdef INT_QUEUE_AVG
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inline T avg () const { assert(full()); return sum / max_sz; }
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#else
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inline double avg () const { assert(full()); return sum / (double) max_sz; }
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#endif
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inline void clear() { sum = 0; q_sz = 0; ptr = 0; }
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void push(T e) {
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if (q_sz < max_sz) q_sz++;
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else sum -= q[ptr];
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sum += e;
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q[ptr++] = e;
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if (ptr == max_sz) ptr = 0;
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}
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};
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public:
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// Constructor/Destructor:
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//
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Solver();
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virtual ~Solver();
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// Problem specification:
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//
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Var newVar (bool polarity = true, bool dvar = true); // Add a new variable with parameters specifying variable mode.
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bool addClause (const vec<Lit>& ps); // Add a clause to the solver.
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bool addEmptyClause(); // Add the empty clause, making the solver contradictory.
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bool addClause (Lit p); // Add a unit clause to the solver.
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bool addClause (Lit p, Lit q); // Add a binary clause to the solver.
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bool addClause (Lit p, Lit q, Lit r); // Add a ternary clause to the solver.
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bool addClause_( vec<Lit>& ps); // Add a clause to the solver without making superflous internal copy. Will
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// change the passed vector 'ps'.
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// Parallel support
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//
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bool importClauses();
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vec<Lit> importedClause;
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void * issuer; // used as the callback parameter
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bool (* cbkImportClause)(void *, int *, vec<Lit> &);
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void (* cbkExportClause)(void *, int, vec<Lit> &); // callback for clause learning
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// Solving:
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//
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bool simplify (); // Removes already satisfied clauses.
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bool solve (const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions.
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lbool solveLimited (const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions (With resource constraints).
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bool solve (); // Search without assumptions.
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bool solve (Lit p); // Search for a model that respects a single assumption.
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bool solve (Lit p, Lit q); // Search for a model that respects two assumptions.
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bool solve (Lit p, Lit q, Lit r); // Search for a model that respects three assumptions.
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bool okay () const; // FALSE means solver is in a conflicting state
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void toDimacs (FILE* f, const vec<Lit>& assumps); // Write CNF to file in DIMACS-format.
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void toDimacs (const char *file, const vec<Lit>& assumps);
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void toDimacs (FILE* f, Clause& c, vec<Var>& map, Var& max);
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// Convenience versions of 'toDimacs()':
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void toDimacs (const char* file);
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void toDimacs (const char* file, Lit p);
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void toDimacs (const char* file, Lit p, Lit q);
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void toDimacs (const char* file, Lit p, Lit q, Lit r);
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// Variable mode:
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//
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void setPolarity (Var v, bool b); // Declare which polarity the decision heuristic should use for a variable. Requires mode 'polarity_user'.
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void setDecisionVar (Var v, bool b); // Declare if a variable should be eligible for selection in the decision heuristic.
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// Read state:
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//
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lbool value (Var x) const; // The current value of a variable.
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lbool value (Lit p) const; // The current value of a literal.
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lbool modelValue (Var x) const; // The value of a variable in the last model. The last call to solve must have been satisfiable.
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lbool modelValue (Lit p) const; // The value of a literal in the last model. The last call to solve must have been satisfiable.
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int nAssigns () const; // The current number of assigned literals.
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int nClauses () const; // The current number of original clauses.
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int nLearnts () const; // The current number of learnt clauses.
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int nVars () const; // The current number of variables.
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int nFreeVars () const;
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// Resource contraints:
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//
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void setConfBudget(int64_t x);
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void setPropBudget(int64_t x);
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void budgetOff();
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void interrupt(); // Trigger a (potentially asynchronous) interruption of the solver.
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void clearInterrupt(); // Clear interrupt indicator flag.
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// Memory managment:
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//
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virtual void garbageCollect();
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void checkGarbage(double gf);
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void checkGarbage();
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// Extra results: (read-only member variable)
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//
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vec<lbool> model; // If problem is satisfiable, this vector contains the model (if any).
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vec<Lit> conflict; // If problem is unsatisfiable (possibly under assumptions),
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// this vector represent the final conflict clause expressed in the assumptions.
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// Mode of operation:
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//
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FILE* drup_file;
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int worker_index;
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int worker_number;
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int worker_seed;
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int verbosity;
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double step_size;
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double step_size_dec;
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double min_step_size;
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int timer;
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double var_decay;
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double clause_decay;
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double random_var_freq;
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double random_seed;
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bool VSIDS;
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int ccmin_mode; // Controls conflict clause minimization (0=none, 1=basic, 2=deep).
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int phase_saving; // Controls the level of phase saving (0=none, 1=limited, 2=full).
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bool rnd_pol; // Use random polarities for branching heuristics.
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bool rnd_init_act; // Initialize variable activities with a small random value.
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double garbage_frac; // The fraction of wasted memory allowed before a garbage collection is triggered.
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int restart_first; // The initial restart limit. (default 100)
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double restart_inc; // The factor with which the restart limit is multiplied in each restart. (default 1.5)
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double learntsize_factor; // The intitial limit for learnt clauses is a factor of the original clauses. (default 1 / 3)
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double learntsize_inc; // The limit for learnt clauses is multiplied with this factor each restart. (default 1.1)
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int learntsize_adjust_start_confl;
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double learntsize_adjust_inc;
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// duplicate learnts version
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uint32_t min_number_of_learnts_copies;
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uint32_t dupl_db_init_size;
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uint32_t max_lbd_dup;
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std::chrono::microseconds duptime;
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// duplicate learnts version
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// Statistics: (read-only member variable)
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//
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uint64_t solves, starts, decisions, rnd_decisions, propagations, conflicts, conflicts_VSIDS;
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uint64_t dec_vars, clauses_literals, learnts_literals, max_literals, tot_literals;
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uint64_t chrono_backtrack, non_chrono_backtrack;
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// duplicate learnts version
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uint64_t duplicates_added_conflicts;
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uint64_t duplicates_added_tier2;
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uint64_t duplicates_added_minimization;
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uint64_t dupl_db_size;
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// duplicate learnts version
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vec<uint32_t> picked;
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vec<uint32_t> conflicted;
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vec<uint32_t> almost_conflicted;
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#ifdef ANTI_EXPLORATION
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vec<uint32_t> canceled;
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#endif
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protected:
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// Helper structures:
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//
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struct VarData { CRef reason; int level; };
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static inline VarData mkVarData(CRef cr, int l){ VarData d = {cr, l}; return d; }
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struct Watcher {
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CRef cref;
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Lit blocker;
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Watcher(CRef cr, Lit p) : cref(cr), blocker(p) {}
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bool operator==(const Watcher& w) const { return cref == w.cref; }
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bool operator!=(const Watcher& w) const { return cref != w.cref; }
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};
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struct WatcherDeleted
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{
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const ClauseAllocator& ca;
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WatcherDeleted(const ClauseAllocator& _ca) : ca(_ca) {}
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bool operator()(const Watcher& w) const { return ca[w.cref].mark() == 1; }
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};
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struct VarOrderLt {
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const vec<double>& activity;
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bool operator () (Var x, Var y) const { return activity[x] > activity[y]; }
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VarOrderLt(const vec<double>& act) : activity(act) { }
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};
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struct ConflictData
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{
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ConflictData() :
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nHighestLevel(-1),
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bOnlyOneLitFromHighest(false)
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{}
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int nHighestLevel;
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bool bOnlyOneLitFromHighest;
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};
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// Solver state:
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//
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bool ok; // If FALSE, the constraints are already unsatisfiable. No part of the solver state may be used!
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vec<CRef> clauses; // List of problem clauses.
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vec<CRef> learnts_core, // List of learnt clauses.
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learnts_tier2,
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learnts_local;
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double cla_inc; // Amount to bump next clause with.
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vec<double> activity_CHB, // A heuristic measurement of the activity of a variable.
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activity_VSIDS;
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double var_inc; // Amount to bump next variable with.
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OccLists<Lit, vec<Watcher>, WatcherDeleted>
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watches_bin, // Watches for binary clauses only.
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watches; // 'watches[lit]' is a list of constraints watching 'lit' (will go there if literal becomes true).
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vec<lbool> assigns; // The current assignments.
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vec<char> polarity; // The preferred polarity of each variable.
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vec<char> decision; // Declares if a variable is eligible for selection in the decision heuristic.
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vec<Lit> trail; // Assignment stack; stores all assigments made in the order they were made.
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vec<int> trail_lim; // Separator indices for different decision levels in 'trail'.
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vec<VarData> vardata; // Stores reason and level for each variable.
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int qhead; // Head of queue (as index into the trail -- no more explicit propagation queue in MiniSat).
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int simpDB_assigns; // Number of top-level assignments since last execution of 'simplify()'.
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int64_t simpDB_props; // Remaining number of propagations that must be made before next execution of 'simplify()'.
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vec<Lit> assumptions; // Current set of assumptions provided to solve by the user.
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Heap<VarOrderLt> order_heap_CHB, // A priority queue of variables ordered with respect to the variable activity.
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order_heap_VSIDS;
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double progress_estimate;// Set by 'search()'.
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bool remove_satisfied; // Indicates whether possibly inefficient linear scan for satisfied clauses should be performed in 'simplify'.
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int core_lbd_cut;
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float global_lbd_sum;
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MyQueue<int> lbd_queue; // For computing moving averages of recent LBD values.
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uint64_t next_T2_reduce,
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next_L_reduce;
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ClauseAllocator ca;
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|||
|
|
|
|||
|
|
// duplicate learnts version
|
|||
|
|
std::map<int32_t,std::map<uint32_t,std::unordered_map<uint64_t,uint32_t>>> ht;
|
|||
|
|
|
|||
|
|
// duplicate learnts version
|
|||
|
|
|
|||
|
|
int confl_to_chrono;
|
|||
|
|
int chrono;
|
|||
|
|
|
|||
|
|
// Temporaries (to reduce allocation overhead). Each variable is prefixed by the method in which it is
|
|||
|
|
// used, exept 'seen' wich is used in several places.
|
|||
|
|
//
|
|||
|
|
vec<char> seen;
|
|||
|
|
vec<Lit> analyze_stack;
|
|||
|
|
vec<Lit> analyze_toclear;
|
|||
|
|
vec<Lit> add_tmp;
|
|||
|
|
vec<Lit> add_oc;
|
|||
|
|
|
|||
|
|
vec<uint64_t> seen2; // Mostly for efficient LBD computation. 'seen2[i]' will indicate if decision level or variable 'i' has been seen.
|
|||
|
|
uint64_t counter; // Simple counter for marking purpose with 'seen2'.
|
|||
|
|
|
|||
|
|
double max_learnts;
|
|||
|
|
double learntsize_adjust_confl;
|
|||
|
|
int learntsize_adjust_cnt;
|
|||
|
|
|
|||
|
|
// Resource contraints:
|
|||
|
|
//
|
|||
|
|
int64_t conflict_budget; // -1 means no budget.
|
|||
|
|
int64_t propagation_budget; // -1 means no budget.
|
|||
|
|
bool asynch_interrupt;
|
|||
|
|
|
|||
|
|
// Main internal methods:
|
|||
|
|
//
|
|||
|
|
void insertVarOrder (Var x); // Insert a variable in the decision order priority queue.
|
|||
|
|
Lit pickBranchLit (); // Return the next decision variable.
|
|||
|
|
void newDecisionLevel (); // Begins a new decision level.
|
|||
|
|
void uncheckedEnqueue (Lit p, int level = 0, CRef from = CRef_Undef); // Enqueue a literal. Assumes value of literal is undefined.
|
|||
|
|
bool enqueue (Lit p, CRef from = CRef_Undef); // Test if fact 'p' contradicts current state, enqueue otherwise.
|
|||
|
|
CRef propagate (); // Perform unit propagation. Returns possibly conflicting clause.
|
|||
|
|
void cancelUntil (int level); // Backtrack until a certain level.
|
|||
|
|
void analyze (CRef confl, vec<Lit>& out_learnt, int& out_btlevel, int& out_lbd); // (bt = backtrack)
|
|||
|
|
void analyzeFinal (Lit p, vec<Lit>& out_conflict); // COULD THIS BE IMPLEMENTED BY THE ORDINARIY "analyze" BY SOME REASONABLE GENERALIZATION?
|
|||
|
|
bool litRedundant (Lit p, uint32_t abstract_levels); // (helper method for 'analyze()')
|
|||
|
|
lbool search (int& nof_conflicts); // Search for a given number of conflicts.
|
|||
|
|
lbool solve_ (); // Main solve method (assumptions given in 'assumptions').
|
|||
|
|
void reduceDB (); // Reduce the set of learnt clauses.
|
|||
|
|
void reduceDB_Tier2 ();
|
|||
|
|
void removeSatisfied (vec<CRef>& cs); // Shrink 'cs' to contain only non-satisfied clauses.
|
|||
|
|
void safeRemoveSatisfied(vec<CRef>& cs, unsigned valid_mark);
|
|||
|
|
void rebuildOrderHeap ();
|
|||
|
|
bool binResMinimize (vec<Lit>& out_learnt); // Further learnt clause minimization by binary resolution.
|
|||
|
|
|
|||
|
|
// Maintaining Variable/Clause activity:
|
|||
|
|
//
|
|||
|
|
void varDecayActivity (); // Decay all variables with the specified factor. Implemented by increasing the 'bump' value instead.
|
|||
|
|
void varBumpActivity (Var v, double mult); // Increase a variable with the current 'bump' value.
|
|||
|
|
void claDecayActivity (); // Decay all clauses with the specified factor. Implemented by increasing the 'bump' value instead.
|
|||
|
|
void claBumpActivity (Clause& c); // Increase a clause with the current 'bump' value.
|
|||
|
|
|
|||
|
|
// Operations on clauses:
|
|||
|
|
//
|
|||
|
|
void attachClause (CRef cr); // Attach a clause to watcher lists.
|
|||
|
|
void detachClause (CRef cr, bool strict = false); // Detach a clause to watcher lists.
|
|||
|
|
void removeClause (CRef cr); // Detach and free a clause.
|
|||
|
|
bool locked (const Clause& c) const; // Returns TRUE if a clause is a reason for some implication in the current state.
|
|||
|
|
bool satisfied (const Clause& c) const; // Returns TRUE if a clause is satisfied in the current state.
|
|||
|
|
|
|||
|
|
void relocAll (ClauseAllocator& to);
|
|||
|
|
|
|||
|
|
// duplicate learnts version
|
|||
|
|
int is_duplicate (std::vector<uint32_t>&c); //returns TRUE if a clause is duplicate
|
|||
|
|
// duplicate learnts version
|
|||
|
|
|
|||
|
|
// Misc:
|
|||
|
|
//
|
|||
|
|
int decisionLevel () const; // Gives the current decisionlevel.
|
|||
|
|
uint32_t abstractLevel (Var x) const; // Used to represent an abstraction of sets of decision levels.
|
|||
|
|
CRef reason (Var x) const;
|
|||
|
|
|
|||
|
|
ConflictData FindConflictLevel(CRef cind);
|
|||
|
|
|
|||
|
|
public:
|
|||
|
|
int level (Var x) const;
|
|||
|
|
protected:
|
|||
|
|
double progressEstimate () const; // DELETE THIS ?? IT'S NOT VERY USEFUL ...
|
|||
|
|
bool withinBudget () const;
|
|||
|
|
|
|||
|
|
template<class V> int computeLBD(const V& c) {
|
|||
|
|
int lbd = 0;
|
|||
|
|
|
|||
|
|
counter++;
|
|||
|
|
for (int i = 0; i < c.size(); i++){
|
|||
|
|
int l = level(var(c[i]));
|
|||
|
|
if (l != 0 && seen2[l] != counter){
|
|||
|
|
seen2[l] = counter;
|
|||
|
|
lbd++; } }
|
|||
|
|
|
|||
|
|
return lbd;
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
#ifdef BIN_DRUP
|
|||
|
|
static int buf_len;
|
|||
|
|
static unsigned char drup_buf[];
|
|||
|
|
static unsigned char* buf_ptr;
|
|||
|
|
|
|||
|
|
static inline void byteDRUP(Lit l){
|
|||
|
|
unsigned int u = 2 * (var(l) + 1) + sign(l);
|
|||
|
|
do{
|
|||
|
|
*buf_ptr++ = u & 0x7f | 0x80; buf_len++;
|
|||
|
|
u = u >> 7;
|
|||
|
|
}while (u);
|
|||
|
|
*(buf_ptr - 1) &= 0x7f; // End marker of this unsigned number.
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
template<class V>
|
|||
|
|
static inline void binDRUP(unsigned char op, const V& c, FILE* drup_file){
|
|||
|
|
assert(op == 'a' || op == 'd');
|
|||
|
|
*buf_ptr++ = op; buf_len++;
|
|||
|
|
for (int i = 0; i < c.size(); i++) byteDRUP(c[i]);
|
|||
|
|
*buf_ptr++ = 0; buf_len++;
|
|||
|
|
if (buf_len > 1048576) binDRUP_flush(drup_file);
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
static inline void binDRUP_strengthen(const Clause& c, Lit l, FILE* drup_file){
|
|||
|
|
*buf_ptr++ = 'a'; buf_len++;
|
|||
|
|
for (int i = 0; i < c.size(); i++)
|
|||
|
|
if (c[i] != l) byteDRUP(c[i]);
|
|||
|
|
*buf_ptr++ = 0; buf_len++;
|
|||
|
|
if (buf_len > 1048576) binDRUP_flush(drup_file);
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
static inline void binDRUP_flush(FILE* drup_file){
|
|||
|
|
// fwrite(drup_buf, sizeof(unsigned char), buf_len, drup_file);
|
|||
|
|
fwrite_unlocked(drup_buf, sizeof(unsigned char), buf_len, drup_file);
|
|||
|
|
buf_ptr = drup_buf; buf_len = 0;
|
|||
|
|
}
|
|||
|
|
#endif
|
|||
|
|
|
|||
|
|
// Static helpers:
|
|||
|
|
//
|
|||
|
|
|
|||
|
|
// Returns a random float 0 <= x < 1. Seed must never be 0.
|
|||
|
|
static inline double drand(double& seed) {
|
|||
|
|
seed *= 1389796;
|
|||
|
|
int q = (int)(seed / 2147483647);
|
|||
|
|
seed -= (double)q * 2147483647;
|
|||
|
|
return seed / 2147483647; }
|
|||
|
|
|
|||
|
|
// Returns a random integer 0 <= x < size. Seed must never be 0.
|
|||
|
|
static inline int irand(double& seed, int size) {
|
|||
|
|
return (int)(drand(seed) * size); }
|
|||
|
|
|
|||
|
|
|
|||
|
|
// simplify
|
|||
|
|
//
|
|||
|
|
public:
|
|||
|
|
bool simplifyAll();
|
|||
|
|
void simplifyLearnt(Clause& c);
|
|||
|
|
bool simplifyLearnt_x(vec<CRef>& learnts_x);
|
|||
|
|
bool simplifyLearnt_core();
|
|||
|
|
bool simplifyLearnt_tier2();
|
|||
|
|
int trailRecord;
|
|||
|
|
void litsEnqueue(int cutP, Clause& c);
|
|||
|
|
void cancelUntilTrailRecord();
|
|||
|
|
void simpleUncheckEnqueue(Lit p, CRef from = CRef_Undef);
|
|||
|
|
CRef simplePropagate();
|
|||
|
|
uint64_t nbSimplifyAll;
|
|||
|
|
uint64_t simplified_length_record, original_length_record;
|
|||
|
|
uint64_t s_propagations;
|
|||
|
|
|
|||
|
|
vec<Lit> simp_learnt_clause;
|
|||
|
|
vec<CRef> simp_reason_clause;
|
|||
|
|
void simpleAnalyze(CRef confl, vec<Lit>& out_learnt, vec<CRef>& reason_clause, bool True_confl);
|
|||
|
|
|
|||
|
|
// in redundant
|
|||
|
|
bool removed(CRef cr);
|
|||
|
|
// adjust simplifyAll occasion
|
|||
|
|
long curSimplify;
|
|||
|
|
int nbconfbeforesimplify;
|
|||
|
|
int incSimplify;
|
|||
|
|
|
|||
|
|
private:
|
|||
|
|
// to avoid the init_soln of two LS too near.
|
|||
|
|
int restarts_gap = 300;
|
|||
|
|
int restarts_basic = 300;
|
|||
|
|
// if trail.size() over c*nVars or p*max_trail, call ls.
|
|||
|
|
// float conflict_ratio = 0.4;
|
|||
|
|
// float percent_ratio = 0.9;
|
|||
|
|
// // control ls time total use.
|
|||
|
|
// float up_time_ratio = 0.2;
|
|||
|
|
// control ls memory use per call.
|
|||
|
|
long long ls_mems_num = 50*1000*1000;
|
|||
|
|
// whether the mediation_soln is used as rephase, if not
|
|||
|
|
// bool mediation_used = false;
|
|||
|
|
|
|||
|
|
int switch_heristic_mod = 500;//starts
|
|||
|
|
int last_switch_conflicts;
|
|||
|
|
|
|||
|
|
//informations
|
|||
|
|
// bool lssolver_constructed = false;
|
|||
|
|
CCAnr *lssolver;
|
|||
|
|
int freeze_ls_restart_num = 0;
|
|||
|
|
double ls_used_time = 0;
|
|||
|
|
int ls_call_num = 0;
|
|||
|
|
int ls_best_unsat_num = INT_MAX;
|
|||
|
|
bool solved_by_ls = false;
|
|||
|
|
int max_trail = 0;
|
|||
|
|
bool max_trail_improved = false;
|
|||
|
|
int up_build_num = 0;
|
|||
|
|
double up_build_time = 0.0;
|
|||
|
|
|
|||
|
|
//Phases
|
|||
|
|
// save the recent ls soln and best ls soln, need to call ls once.
|
|||
|
|
char* ls_mediation_soln;
|
|||
|
|
// with the minimum unsat clauses num in LS.
|
|||
|
|
char* ls_best_soln;
|
|||
|
|
// hold the soln with the best trail size.
|
|||
|
|
char* top_trail_soln;
|
|||
|
|
char* tmp_up_build_soln;
|
|||
|
|
|
|||
|
|
|
|||
|
|
//functions
|
|||
|
|
// bool call_ls(bool use_up_build);
|
|||
|
|
bool ccanr_has_constructed = false;
|
|||
|
|
enum build_type{current_UP,top_trail_UP,random_build};
|
|||
|
|
bool call_ls(build_type type);
|
|||
|
|
void load_ls_data();
|
|||
|
|
void build_soln_with_UP();
|
|||
|
|
void rand_based_rephase();
|
|||
|
|
void info_based_rephase();
|
|||
|
|
};
|
|||
|
|
|
|||
|
|
|
|||
|
|
//=================================================================================================
|
|||
|
|
// Implementation of inline methods:
|
|||
|
|
|
|||
|
|
inline CRef Solver::reason(Var x) const { return vardata[x].reason; }
|
|||
|
|
inline int Solver::level (Var x) const { return vardata[x].level; }
|
|||
|
|
|
|||
|
|
inline void Solver::insertVarOrder(Var x) {
|
|||
|
|
// Heap<VarOrderLt>& order_heap = VSIDS ? order_heap_VSIDS : order_heap_CHB;
|
|||
|
|
Heap<VarOrderLt>& order_heap = ((!VSIDS)? order_heap_CHB:order_heap_VSIDS);
|
|||
|
|
if (!order_heap.inHeap(x) && decision[x]) order_heap.insert(x); }
|
|||
|
|
|
|||
|
|
inline void Solver::varDecayActivity() {
|
|||
|
|
var_inc *= (1 / var_decay); }
|
|||
|
|
|
|||
|
|
inline void Solver::varBumpActivity(Var v, double mult) {
|
|||
|
|
if ( (activity_VSIDS[v] += var_inc * mult) > 1e100 ) {
|
|||
|
|
// Rescale:
|
|||
|
|
for (int i = 0; i < nVars(); i++)
|
|||
|
|
activity_VSIDS[i] *= 1e-100;
|
|||
|
|
var_inc *= 1e-100; }
|
|||
|
|
|
|||
|
|
// Update order_heap with respect to new activity:
|
|||
|
|
if (order_heap_VSIDS.inHeap(v)) order_heap_VSIDS.decrease(v); }
|
|||
|
|
|
|||
|
|
inline void Solver::claDecayActivity() { cla_inc *= (1 / clause_decay); }
|
|||
|
|
inline void Solver::claBumpActivity (Clause& c) {
|
|||
|
|
if ( (c.activity() += cla_inc) > 1e20 ) {
|
|||
|
|
// Rescale:
|
|||
|
|
for (int i = 0; i < learnts_local.size(); i++)
|
|||
|
|
ca[learnts_local[i]].activity() *= 1e-20;
|
|||
|
|
cla_inc *= 1e-20; } }
|
|||
|
|
|
|||
|
|
inline void Solver::checkGarbage(void){ return checkGarbage(garbage_frac); }
|
|||
|
|
inline void Solver::checkGarbage(double gf){
|
|||
|
|
if (ca.wasted() > ca.size() * gf)
|
|||
|
|
garbageCollect(); }
|
|||
|
|
|
|||
|
|
// NOTE: enqueue does not set the ok flag! (only public methods do)
|
|||
|
|
inline bool Solver::enqueue (Lit p, CRef from) { return value(p) != l_Undef ? value(p) != l_False : (uncheckedEnqueue(p, decisionLevel(), from), true); }
|
|||
|
|
inline bool Solver::addClause (const vec<Lit>& ps) { ps.copyTo(add_tmp); return addClause_(add_tmp); }
|
|||
|
|
inline bool Solver::addEmptyClause () { add_tmp.clear(); return addClause_(add_tmp); }
|
|||
|
|
inline bool Solver::addClause (Lit p) { add_tmp.clear(); add_tmp.push(p); return addClause_(add_tmp); }
|
|||
|
|
inline bool Solver::addClause (Lit p, Lit q) { add_tmp.clear(); add_tmp.push(p); add_tmp.push(q); return addClause_(add_tmp); }
|
|||
|
|
inline bool Solver::addClause (Lit p, Lit q, Lit r) { add_tmp.clear(); add_tmp.push(p); add_tmp.push(q); add_tmp.push(r); return addClause_(add_tmp); }
|
|||
|
|
inline bool Solver::locked (const Clause& c) const {
|
|||
|
|
int i = c.size() != 2 ? 0 : (value(c[0]) == l_True ? 0 : 1);
|
|||
|
|
return value(c[i]) == l_True && reason(var(c[i])) != CRef_Undef && ca.lea(reason(var(c[i]))) == &c;
|
|||
|
|
}
|
|||
|
|
inline void Solver::newDecisionLevel() { trail_lim.push(trail.size()); }
|
|||
|
|
|
|||
|
|
inline int Solver::decisionLevel () const { return trail_lim.size(); }
|
|||
|
|
inline uint32_t Solver::abstractLevel (Var x) const { return 1 << (level(x) & 31); }
|
|||
|
|
inline lbool Solver::value (Var x) const { return assigns[x]; }
|
|||
|
|
inline lbool Solver::value (Lit p) const { return assigns[var(p)] ^ sign(p); }
|
|||
|
|
inline lbool Solver::modelValue (Var x) const { return model[x]; }
|
|||
|
|
inline lbool Solver::modelValue (Lit p) const { return model[var(p)] ^ sign(p); }
|
|||
|
|
inline int Solver::nAssigns () const { return trail.size(); }
|
|||
|
|
inline int Solver::nClauses () const { return clauses.size(); }
|
|||
|
|
inline int Solver::nLearnts () const { return learnts_core.size() + learnts_tier2.size() + learnts_local.size(); }
|
|||
|
|
inline int Solver::nVars () const { return vardata.size(); }
|
|||
|
|
inline int Solver::nFreeVars () const { return (int)dec_vars - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]); }
|
|||
|
|
inline void Solver::setPolarity (Var v, bool b) { polarity[v] = b; }
|
|||
|
|
inline void Solver::setDecisionVar(Var v, bool b)
|
|||
|
|
{
|
|||
|
|
if ( b && !decision[v]) dec_vars++;
|
|||
|
|
else if (!b && decision[v]) dec_vars--;
|
|||
|
|
|
|||
|
|
decision[v] = b;
|
|||
|
|
if (b && !order_heap_CHB.inHeap(v)){
|
|||
|
|
order_heap_CHB.insert(v);
|
|||
|
|
order_heap_VSIDS.insert(v);}
|
|||
|
|
}
|
|||
|
|
inline void Solver::setConfBudget(int64_t x){ conflict_budget = conflicts + x; }
|
|||
|
|
inline void Solver::setPropBudget(int64_t x){ propagation_budget = propagations + x; }
|
|||
|
|
inline void Solver::interrupt(){ asynch_interrupt = true; }
|
|||
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inline void Solver::clearInterrupt(){ asynch_interrupt = false; }
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inline void Solver::budgetOff(){ conflict_budget = propagation_budget = -1; }
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|
inline bool Solver::withinBudget() const {
|
|||
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|
return !asynch_interrupt &&
|
|||
|
|
(conflict_budget < 0 || conflicts < (uint64_t)conflict_budget) &&
|
|||
|
|
(propagation_budget < 0 || propagations < (uint64_t)propagation_budget); }
|
|||
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|
|
|||
|
|
// FIXME: after the introduction of asynchronous interrruptions the solve-versions that return a
|
|||
|
|
// pure bool do not give a safe interface. Either interrupts must be possible to turn off here, or
|
|||
|
|
// all calls to solve must return an 'lbool'. I'm not yet sure which I prefer.
|
|||
|
|
inline bool Solver::solve () { budgetOff(); assumptions.clear(); return solve_() == l_True; }
|
|||
|
|
inline bool Solver::solve (Lit p) { budgetOff(); assumptions.clear(); assumptions.push(p); return solve_() == l_True; }
|
|||
|
|
inline bool Solver::solve (Lit p, Lit q) { budgetOff(); assumptions.clear(); assumptions.push(p); assumptions.push(q); return solve_() == l_True; }
|
|||
|
|
inline bool Solver::solve (Lit p, Lit q, Lit r) { budgetOff(); assumptions.clear(); assumptions.push(p); assumptions.push(q); assumptions.push(r); return solve_() == l_True; }
|
|||
|
|
inline bool Solver::solve (const vec<Lit>& assumps){ budgetOff(); assumps.copyTo(assumptions); return solve_() == l_True; }
|
|||
|
|
inline lbool Solver::solveLimited (const vec<Lit>& assumps){ assumps.copyTo(assumptions); return solve_(); }
|
|||
|
|
inline bool Solver::okay () const { return ok; }
|
|||
|
|
|
|||
|
|
inline void Solver::toDimacs (const char* file){ vec<Lit> as; toDimacs(file, as); }
|
|||
|
|
inline void Solver::toDimacs (const char* file, Lit p){ vec<Lit> as; as.push(p); toDimacs(file, as); }
|
|||
|
|
inline void Solver::toDimacs (const char* file, Lit p, Lit q){ vec<Lit> as; as.push(p); as.push(q); toDimacs(file, as); }
|
|||
|
|
inline void Solver::toDimacs (const char* file, Lit p, Lit q, Lit r){ vec<Lit> as; as.push(p); as.push(q); as.push(r); toDimacs(file, as); }
|
|||
|
|
|
|||
|
|
//=================================================================================================
|
|||
|
|
// Debug etc:
|
|||
|
|
|
|||
|
|
|
|||
|
|
//=================================================================================================
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
#endif
|