update vendor/

This commit is contained in:
Ettore Di Giacinto 2020-11-03 17:21:32 +01:00
parent 25f69d4f1c
commit d7a04465fd
12 changed files with 199 additions and 89 deletions

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@ -230,6 +230,8 @@ func (a and) String() string {
}
func (a and) Eval(model map[string]bool) (res bool) {
res = true
for i, s := range a {
b := s.Eval(model)
if i == 0 {

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@ -29,7 +29,7 @@ func (s *Solver) addClauseLits(confl *Clause, lvl decLevel, met, metLvl []bool,
if abs(s.model[v]) == lvl {
metLvl[v] = true
nbLvl++
} else if abs(s.model[v]) != 1 {
} else {
*lits = append(*lits, l)
}
}
@ -39,8 +39,9 @@ func (s *Solver) addClauseLits(confl *Clause, lvl decLevel, met, metLvl []bool,
var bufLits = make([]Lit, 10000) // Buffer for lits in learnClause. Used to reduce allocations.
// learnClause creates a conflict clause and returns either:
// the clause itself, if its len is at least 2.
// a nil clause and a unit literal, if its len is exactly 1.
// - the clause itself, if its len is at least 2,
// - a nil clause and a unit literal, if its len is exactly 1,
// - a nil clause and -1, if the empty clause was learned.
func (s *Solver) learnClause(confl *Clause, lvl decLevel) (learned *Clause, unit Lit) {
s.clauseBumpActivity(confl)
lits := bufLits[:1] // Not 0: make room for asserting literal
@ -58,6 +59,10 @@ func (s *Solver) learnClause(confl *Clause, lvl decLevel) (learned *Clause, unit
ptr--
}
v := s.trail[ptr].Var()
if s.assumptions[v] {
// Now we only have assumed lits: this is a top-level conflict
return nil, -1
}
ptr--
nbLvl--
if reason := s.reason[v]; reason != nil {
@ -65,7 +70,7 @@ func (s *Solver) learnClause(confl *Clause, lvl decLevel) (learned *Clause, unit
for i := 0; i < reason.Len(); i++ {
lit := reason.Get(i)
if v2 := lit.Var(); !met[v2] {
if s.litStatus(lit) != Unsat {
if s.litStatus(lit) != Unsat { // In clauses where cardinality > 1, some lits might be true in the conflict clause: ignore them
continue
}
met[v2] = true
@ -73,7 +78,7 @@ func (s *Solver) learnClause(confl *Clause, lvl decLevel) (learned *Clause, unit
if abs(s.model[v2]) == lvl {
metLvl[v2] = true
nbLvl++
} else if abs(s.model[v2]) != 1 {
} else {
lits = append(lits, lit)
}
}
@ -109,7 +114,7 @@ func (s *Solver) minimizeLearned(met []bool, learned []Lit) int {
} else {
for k := 0; k < reason.Len(); k++ {
lit := reason.Get(k)
if !met[lit.Var()] && abs(s.model[lit.Var()]) > 1 {
if !met[lit.Var()] /*&& abs(s.model[lit.Var()]) > 1*/ {
learned[sz] = learned[i]
sz++
break

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@ -12,11 +12,25 @@ import (
// The argument is supposed to be a well-formed CNF.
func ParseSlice(cnf [][]int) *Problem {
var pb Problem
pb.parseSlice(cnf)
return &pb
}
// ParseSliceNb parse a slice of slice of lits and returns the equivalent problem.
// The argument is supposed to be a well-formed CNF.
// The number of vars is provided because clauses might be added to it later.
func ParseSliceNb(cnf [][]int, nbVars int) *Problem {
pb := Problem{NbVars: nbVars}
pb.parseSlice(cnf)
return &pb
}
func (pb *Problem) parseSlice(cnf [][]int) {
for _, line := range cnf {
switch len(line) {
case 0:
pb.Status = Unsat
return &pb
return
case 1:
if line[0] == 0 {
panic("null unit clause")
@ -31,7 +45,7 @@ func ParseSlice(cnf [][]int) *Problem {
lits := make([]Lit, len(line))
for j, val := range line {
if val == 0 {
panic("null literal in clause %q")
panic(fmt.Sprintf("null literal in clause %v", lits))
}
lits[j] = IntToLit(int32(val))
if v := int(lits[j].Var()); v >= pb.NbVars {
@ -52,11 +66,10 @@ func ParseSlice(cnf [][]int) *Problem {
}
} else if pb.Model[v] > 0 != unit.IsPositive() {
pb.Status = Unsat
return &pb
return
}
}
pb.simplify2()
return &pb
}
func isSpace(b byte) bool {

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@ -97,26 +97,6 @@ func (pb *Problem) updateStatus(nbClauses int) {
}
}
func (pb *Problem) simplify() {
idxClauses := make([][]int, pb.NbVars*2) // For each lit, indexes of clauses it appears in
removed := make([]bool, len(pb.Clauses)) // Clauses that have to be removed
for i := range pb.Clauses {
pb.simplifyClause(i, idxClauses, removed)
if pb.Status == Unsat {
return
}
}
for i := 0; i < len(pb.Units); i++ {
lit := pb.Units[i]
neg := lit.Negation()
clauses := idxClauses[neg]
for j := range clauses {
pb.simplifyClause(j, idxClauses, removed)
}
}
pb.rmClauses(removed)
}
func (pb *Problem) simplifyClause(idx int, idxClauses [][]int, removed []bool) {
c := pb.Clauses[idx]
k := 0

View File

@ -54,15 +54,18 @@ func (m Model) String() string {
// A Solver solves a given problem. It is the main data structure.
type Solver struct {
Verbose bool // Indicates whether the solver should display information during solving or not. False by default
nbVars int
status Status
wl watcherList
trail []Lit // Current assignment stack
model Model // 0 means unbound, other value is a binding
lastModel Model // Placeholder for last model found, useful when looking for several models
activity []float64 // How often each var is involved in conflicts
polarity []bool // Preferred sign for each var
Verbose bool // Indicates whether the solver should display information during solving or not. False by default
Certified bool // Indicates whether a certificate should be generated during solving or not, using the RUP notation. This is useful to prove UNSAT instances. False by default.
CertChan chan string // Indicates where to write the certificate. If Certified is true but CertChan is nil, the certificate will be written on stdout.
nbVars int
status Status
wl watcherList
trail []Lit // Current assignment stack
model Model // 0 means unbound, other value is a binding
lastModel Model // Placeholder for last model found, useful when looking for several models
activity []float64 // How often each var is involved in conflicts
polarity []bool // Preferred sign for each var
assumptions []bool // True iff the var's binding is assumed
// For each var, clause considered when it was unified
// If the var is not bound yet, or if it was bound by a decision, value is nil.
reason []*Clause
@ -73,7 +76,7 @@ type Solver struct {
Stats Stats // Statistics about the solving process.
minLits []Lit // Lits to minimize if the problem was an optimization problem.
minWeights []int // Weight of each lit to minimize if the problem was an optimization problem.
asumptions []Lit // Literals that are, ideally, true. Useful when trying to minimize a function.
hypothesis []Lit // Literals that are, ideally, true. Useful when trying to minimize a function.
localNbRestarts int // How many restarts since Solve() was called?
varDecay float64 // On each var decay, how much the varInc should be decayed
trailBuf []int // A buffer while cleaning bindings
@ -94,19 +97,20 @@ func New(problem *Problem) *Solver {
}
s := &Solver{
nbVars: nbVars,
status: problem.Status,
trail: make([]Lit, len(problem.Units), trailCap),
model: problem.Model,
activity: make([]float64, nbVars),
polarity: make([]bool, nbVars),
reason: make([]*Clause, nbVars),
varInc: 1.0,
clauseInc: 1.0,
minLits: problem.minLits,
minWeights: problem.minWeights,
varDecay: defaultVarDecay,
trailBuf: make([]int, nbVars),
nbVars: nbVars,
status: problem.Status,
trail: make([]Lit, len(problem.Units), trailCap),
model: problem.Model,
activity: make([]float64, nbVars),
polarity: make([]bool, nbVars),
assumptions: make([]bool, nbVars),
reason: make([]*Clause, nbVars),
varInc: 1.0,
clauseInc: 1.0,
minLits: problem.minLits,
minWeights: problem.minWeights,
varDecay: defaultVarDecay,
trailBuf: make([]int, nbVars),
}
s.resetOptimPolarity()
s.initOptimActivity()
@ -322,26 +326,11 @@ func (s *Solver) rebuildOrderHeap() {
s.varQueue.build(ints)
}
// satClause returns true iff c is satisfied by a literal assigned at top level.
func (s *Solver) satClause(c *Clause) bool {
if c.Len() == 2 || c.Cardinality() != 1 || c.PseudoBoolean() {
// TODO improve this, but it will be ok since we only call this function for removing useless clauses.
return false
}
for i := 0; i < c.Len(); i++ {
lit := c.Get(i)
assign := s.model[lit.Var()]
if assign == 1 && lit.IsPositive() || assign == -1 && !lit.IsPositive() {
return true
}
}
return false
}
// propagate binds the given lit, propagates it and searches for a solution,
// until it is found or a restart is needed.
func (s *Solver) propagateAndSearch(lit Lit, lvl decLevel) Status {
for lit != -1 {
// log.Printf("picked %d at lvl %d", lit.Int(), lvl)
if conflict := s.unifyLiteral(lit, lvl); conflict == nil { // Pick new branch or restart
if s.lbdStats.mustRestart() {
s.lbdStats.clear()
@ -363,15 +352,17 @@ func (s *Solver) propagateAndSearch(lit Lit, lvl decLevel) Status {
s.lbdStats.addConflict(len(s.trail))
learnt, unit := s.learnClause(conflict, lvl)
if learnt == nil { // Unit clause was learned: this lit is known for sure
if unit == -1 || (abs(s.model[unit.Var()]) == 1 && s.litStatus(unit) == Unsat) { // Top-level conflict
return s.setUnsat()
}
s.Stats.NbUnitLearned++
s.lbdStats.addLbd(1)
s.cleanupBindings(1)
s.addLearnedUnit(unit)
s.model[unit.Var()] = lvlToSignedLvl(unit, 1)
if conflict = s.unifyLiteral(unit, 1); conflict != nil { // top-level conflict
s.status = Unsat
return Unsat
return s.setUnsat()
}
// s.rmSatClauses()
s.rebuildOrderHeap()
lit = s.chooseLit()
lvl = 2
@ -392,6 +383,19 @@ func (s *Solver) propagateAndSearch(lit Lit, lvl decLevel) Status {
return Sat
}
// Sets the status to unsat and do cleanup tasks.
func (s *Solver) setUnsat() Status {
if s.Certified {
if s.CertChan == nil {
fmt.Printf("0\n")
} else {
s.CertChan <- "0"
}
}
s.status = Unsat
return Unsat
}
// Searches until a restart is needed.
func (s *Solver) search() Status {
s.localNbRestarts++
@ -455,6 +459,28 @@ func (s *Solver) Solve() Status {
return s.status
}
// Assume adds unit literals to the solver.
// This is useful when calling the solver several times, e.g to keep it "hot" while removing clauses.
func (s *Solver) Assume(lits []Lit) Status {
s.cleanupBindings(0)
s.trail = s.trail[:0]
s.assumptions = make([]bool, s.nbVars)
for _, lit := range lits {
s.addLearnedUnit(lit)
s.assumptions[lit.Var()] = true
s.trail = append(s.trail, lit)
}
s.status = Indet
if confl := s.propagate(0, 1); confl != nil {
// Conflict after unit propagation
s.status = Unsat
return s.status
}
return s.status
}
// Enumerate returns the total number of models for the given problems.
// if "models" is non-nil, it will write models on it as soon as it discovers them.
// models will be closed at the end of the method.
@ -474,10 +500,11 @@ func (s *Solver) Enumerate(models chan []bool, stop chan struct{}) int {
}
}
if s.status == Sat {
nb++
copy(s.lastModel, s.model)
if models != nil {
copy(s.lastModel, s.model)
models <- s.Model()
nb += s.addCurrentModels(models)
} else {
nb += s.countCurrentModels()
}
s.status = Indet
lits := s.decisionLits()
@ -543,7 +570,8 @@ func (s *Solver) CountModels() int {
}
}
if s.status == Sat {
nb++
s.lastModel = s.model
nb += s.countCurrentModels()
if s.Verbose {
fmt.Printf("c found %d model(s)\n", nb)
}
@ -695,6 +723,52 @@ func (s *Solver) Model() []bool {
return res
}
// addCurrentModels is called when a model was found.
// It returns the total number of models from this point, and sends all models on ch.
// The number can be different of 1 if there are unbound variables.
// For instance, if there are 4 variables in the problem and only 1, 3 and 4 are bound,
// there are actually 2 models currently: one with 2 set to true, the other with 2 set to false.
func (s *Solver) addCurrentModels(ch chan []bool) int {
unbound := make([]int, 0, s.nbVars) // indices of unbound variables
var nb uint64 = 1 // total number of models found
model := make([]bool, s.nbVars) // partial model
for i, lvl := range s.lastModel {
if lvl == 0 {
unbound = append(unbound, i)
nb *= 2
} else {
model[i] = lvl > 0
}
}
for i := uint64(0); i < nb; i++ {
for j := range unbound {
mask := uint64(1 << j)
cur := i & mask
idx := unbound[j]
model[idx] = cur != 0
}
model2 := make([]bool, len(model))
copy(model2, model)
ch <- model2
}
return int(nb)
}
// countCurrentModels is called when a model was found.
// It returns the total number of models from this point.
// The number can be different of 1 if there are unbound variables.
// For instance, if there are 4 variables in the problem and only 1, 3 and 4 are bound,
// there are actually 2 models currently: one with 2 set to true, the other with 2 set to false.
func (s *Solver) countCurrentModels() int {
var nb uint64 = 1 // total number of models found
for _, lvl := range s.lastModel {
if lvl == 0 {
nb *= 2
}
}
return int(nb)
}
// Optimal returns the optimal solution, if any.
// If results is non-nil, all solutions will be written to it.
// In any case, results will be closed at the end of the call.
@ -731,13 +805,13 @@ func (s *Solver) Optimal(results chan Result, stop chan struct{}) (res Result) {
maxCost += w
}
}
s.asumptions = make([]Lit, len(s.minLits))
s.hypothesis = make([]Lit, len(s.minLits))
for i, lit := range s.minLits {
s.asumptions[i] = lit.Negation()
s.hypothesis[i] = lit.Negation()
}
weights := make([]int, len(s.minWeights))
copy(weights, s.minWeights)
sort.Sort(wLits{lits: s.asumptions, weights: weights})
sort.Sort(wLits{lits: s.hypothesis, weights: weights})
s.lastModel = make(Model, len(s.model))
var cost int
for status == Sat {
@ -766,7 +840,7 @@ func (s *Solver) Optimal(results chan Result, stop chan struct{}) (res Result) {
// Add a constraint incrementing current best cost
lits2 := make([]Lit, len(s.minLits))
weights2 := make([]int, len(s.minWeights))
copy(lits2, s.asumptions)
copy(lits2, s.hypothesis)
copy(weights2, weights)
s.AppendClause(NewPBClause(lits2, weights2, maxCost-cost+1))
s.rebuildOrderHeap()
@ -796,13 +870,13 @@ func (s *Solver) Minimize() int {
maxCost += w
}
}
s.asumptions = make([]Lit, len(s.minLits))
s.hypothesis = make([]Lit, len(s.minLits))
for i, lit := range s.minLits {
s.asumptions[i] = lit.Negation()
s.hypothesis[i] = lit.Negation()
}
weights := make([]int, len(s.minWeights))
copy(weights, s.minWeights)
sort.Sort(wLits{lits: s.asumptions, weights: weights})
sort.Sort(wLits{lits: s.hypothesis, weights: weights})
s.lastModel = make(Model, len(s.model))
var cost int
for status == Sat {
@ -826,7 +900,7 @@ func (s *Solver) Minimize() int {
// Add a constraint incrementing current best cost
lits2 := make([]Lit, len(s.minLits))
weights2 := make([]int, len(s.minWeights))
copy(lits2, s.asumptions)
copy(lits2, s.hypothesis)
copy(weights2, weights)
s.AppendClause(NewPBClause(lits2, weights2, maxCost-cost+1))
s.rebuildOrderHeap()
@ -835,7 +909,7 @@ func (s *Solver) Minimize() int {
return cost
}
// functions to sort asumptions for pseudo-boolean minimization clause.
// functions to sort hypothesis for pseudo-boolean minimization clause.
type wLits struct {
lits []Lit
weights []int

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@ -42,6 +42,17 @@ type Var int32
// Thus the CNF literal -3 is encoded as 2 * (3-1) + 1 = 5.
type Lit int32
// IntsToLits converts a list of CNF literals to a []Lit.
// This is a helper function as the same result can be achieved by calling
// IntToLit several times.
func IntsToLits(vals ...int32) []Lit {
res := make([]Lit, len(vals))
for i, val := range vals {
res[i] = IntToLit(val)
}
return res
}
// IntToLit converts a CNF literal to a Lit.
func IntToLit(i int32) Lit {
if i < 0 {

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@ -1,6 +1,9 @@
package solver
import "sort"
import (
"fmt"
"sort"
)
type watcher struct {
other Lit // Another lit from the clause
@ -153,6 +156,26 @@ func (s *Solver) addLearned(c *Clause) {
s.wl.learned = append(s.wl.learned, c)
s.watchClause(c)
s.clauseBumpActivity(c)
if s.Certified {
if s.CertChan == nil {
fmt.Printf("%s\n", c.CNF())
} else {
s.CertChan <- c.CNF()
}
}
}
// Adds the given unit literal to the model at the top level.
func (s *Solver) addLearnedUnit(unit Lit) {
s.model[unit.Var()] = lvlToSignedLvl(unit, 1)
if s.Certified {
if s.CertChan == nil {
fmt.Printf("%d 0\n", unit.Int())
} else {
s.CertChan <- fmt.Sprintf("%d 0", unit.Int())
}
}
}
// If l is negative, -lvl is returned. Else, lvl is returned.

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@ -16,6 +16,7 @@ package topsort
import (
"fmt"
"sort"
"strings"
)
@ -98,6 +99,7 @@ func (n node) edges() []string {
for k := range n {
keys = append(keys, k)
}
sort.Strings(keys)
return keys
}

6
vendor/modules.txt vendored
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@ -59,7 +59,7 @@ github.com/containerd/continuity/syscallx
github.com/containerd/continuity/sysx
# github.com/cpuguy83/go-md2man/v2 v2.0.0
github.com/cpuguy83/go-md2man/v2/md2man
# github.com/crillab/gophersat v1.1.9-0.20200211102949-9a8bf7f2f0a3
# github.com/crillab/gophersat v1.3.2-0.20201023142334-3fc2ac466765
github.com/crillab/gophersat/bf
github.com/crillab/gophersat/solver
# github.com/cyphar/filepath-securejoin v0.2.2
@ -211,6 +211,8 @@ github.com/morikuni/aec
github.com/mudler/cobra-extensions
# github.com/mudler/docker-companion v0.4.6-0.20200418093252-41846f112d87
github.com/mudler/docker-companion/api
# github.com/mudler/topsort v0.0.0-20201103161459-db5c7901c290
github.com/mudler/topsort
# github.com/nxadm/tail v1.4.4
github.com/nxadm/tail
github.com/nxadm/tail/ratelimiter
@ -303,8 +305,6 @@ github.com/spf13/jwalterweatherman
github.com/spf13/pflag
# github.com/spf13/viper v1.6.3
github.com/spf13/viper
# github.com/stevenle/topsort v0.0.0-20130922064739-8130c1d7596b
github.com/stevenle/topsort
# github.com/subosito/gotenv v1.2.0
github.com/subosito/gotenv
# github.com/urfave/cli v1.22.1