/usr/include/fst/prune.h is in libfst-dev 1.5.3+r3-2.
This file is owned by root:root, with mode 0o644.
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// finite-state transducer library.
//
// Functions implementing pruning.
#ifndef FST_LIB_PRUNE_H_
#define FST_LIB_PRUNE_H_
#include <vector>
#include <fst/arcfilter.h>
#include <fst/heap.h>
#include <fst/shortest-distance.h>
namespace fst {
template <class A, class ArcFilter>
class PruneOptions {
public:
typedef typename A::Weight Weight;
typedef typename A::StateId StateId;
// Pruning weight threshold.
Weight weight_threshold;
// Pruning state threshold.
StateId state_threshold;
// Arc filter.
ArcFilter filter;
// If non-zero, passes in pre-computed shortest distance to final states.
const std::vector<Weight> *distance;
// Determines the degree of convergence required when computing shortest
// distances.
float delta;
explicit PruneOptions(const Weight &w, StateId s, ArcFilter f,
std::vector<Weight> *d = 0, float e = kDelta)
: weight_threshold(w),
state_threshold(s),
filter(f),
distance(d),
delta(e) {}
private:
PruneOptions(); // disallow
};
template <class S, class W>
class PruneCompare {
public:
typedef S StateId;
typedef W Weight;
PruneCompare(const std::vector<Weight> &idistance,
const std::vector<Weight> &fdistance)
: idistance_(idistance), fdistance_(fdistance) {}
bool operator()(const StateId x, const StateId y) const {
Weight wx = Times(x < idistance_.size() ? idistance_[x] : Weight::Zero(),
x < fdistance_.size() ? fdistance_[x] : Weight::Zero());
Weight wy = Times(y < idistance_.size() ? idistance_[y] : Weight::Zero(),
y < fdistance_.size() ? fdistance_[y] : Weight::Zero());
return less_(wx, wy);
}
private:
const std::vector<Weight> &idistance_;
const std::vector<Weight> &fdistance_;
NaturalLess<Weight> less_;
};
// Pruning algorithm: this version modifies its input and it takes an
// options class as an argment. Delete states and arcs in 'fst' that
// do not belong to a successful path whose weight is no more than
// the weight of the shortest path Times() 'opts.weight_threshold'.
// When 'opts.state_threshold != kNoStateId', the resulting transducer
// will restricted further to have at most 'opts.state_threshold'
// states. Weights need to be commutative and have the path
// property. The weight 'w' of any cycle needs to be bounded, i.e.,
// 'Plus(w, W::One()) = One()'.
template <class Arc, class ArcFilter>
void Prune(MutableFst<Arc> *fst, const PruneOptions<Arc, ArcFilter> &opts) {
typedef typename Arc::Weight Weight;
typedef typename Arc::StateId StateId;
if ((Weight::Properties() & (kPath | kCommutative)) !=
(kPath | kCommutative)) {
FSTERROR() << "Prune: Weight needs to have the path property and"
<< " be commutative: " << Weight::Type();
fst->SetProperties(kError, kError);
return;
}
StateId ns = fst->NumStates();
if (ns == 0) return;
std::vector<Weight> idistance(ns, Weight::Zero());
std::vector<Weight> tmp;
if (!opts.distance) {
tmp.reserve(ns);
ShortestDistance(*fst, &tmp, true, opts.delta);
}
const std::vector<Weight> *fdistance = opts.distance ? opts.distance : &tmp;
if ((opts.state_threshold == 0) || (fdistance->size() <= fst->Start()) ||
((*fdistance)[fst->Start()] == Weight::Zero())) {
fst->DeleteStates();
return;
}
PruneCompare<StateId, Weight> compare(idistance, *fdistance);
using StateHeap = Heap<StateId, PruneCompare<StateId, Weight>>;
StateHeap heap(compare);
std::vector<bool> visited(ns, false);
std::vector<size_t> enqueued(ns, StateHeap::kNoKey);
std::vector<StateId> dead;
dead.push_back(fst->AddState());
NaturalLess<Weight> less;
Weight limit = Times((*fdistance)[fst->Start()], opts.weight_threshold);
StateId num_visited = 0;
StateId s = fst->Start();
if (!less(limit, (*fdistance)[s])) {
idistance[s] = Weight::One();
enqueued[s] = heap.Insert(s);
++num_visited;
}
while (!heap.Empty()) {
s = heap.Top();
heap.Pop();
enqueued[s] = StateHeap::kNoKey;
visited[s] = true;
if (less(limit, Times(idistance[s], fst->Final(s))))
fst->SetFinal(s, Weight::Zero());
for (MutableArcIterator<MutableFst<Arc>> ait(fst, s); !ait.Done();
ait.Next()) {
Arc arc = ait.Value();
if (!opts.filter(arc)) continue;
Weight weight =
Times(Times(idistance[s], arc.weight),
arc.nextstate < fdistance->size() ? (*fdistance)[arc.nextstate]
: Weight::Zero());
if (less(limit, weight)) {
arc.nextstate = dead[0];
ait.SetValue(arc);
continue;
}
if (less(Times(idistance[s], arc.weight), idistance[arc.nextstate]))
idistance[arc.nextstate] = Times(idistance[s], arc.weight);
if (visited[arc.nextstate]) continue;
if ((opts.state_threshold != kNoStateId) &&
(num_visited >= opts.state_threshold))
continue;
if (enqueued[arc.nextstate] == StateHeap::kNoKey) {
enqueued[arc.nextstate] = heap.Insert(arc.nextstate);
++num_visited;
} else {
heap.Update(enqueued[arc.nextstate], arc.nextstate);
}
}
}
for (size_t i = 0; i < visited.size(); ++i)
if (!visited[i]) dead.push_back(i);
fst->DeleteStates(dead);
}
// Pruning algorithm: this version modifies its input and simply takes
// the pruning threshold as an argument. Delete states and arcs in
// 'fst' that do not belong to a successful path whose weight is no
// more than the weight of the shortest path Times()
// 'weight_threshold'. When 'state_threshold != kNoStateId', the
// resulting transducer will be restricted further to have at most
// 'opts.state_threshold' states. Weights need to be commutative and
// have the path property. The weight 'w' of any cycle needs to be
// bounded, i.e., 'Plus(w, W::One()) = One()'.
template <class Arc>
void Prune(MutableFst<Arc> *fst, typename Arc::Weight weight_threshold,
typename Arc::StateId state_threshold = kNoStateId,
double delta = kDelta) {
PruneOptions<Arc, AnyArcFilter<Arc>> opts(weight_threshold, state_threshold,
AnyArcFilter<Arc>(), 0, delta);
Prune(fst, opts);
}
// Pruning algorithm: this version writes the pruned input Fst to an
// output MutableFst and it takes an options class as an argument.
// 'ofst' contains states and arcs that belong to a successful path in
// 'ifst' whose weight is no more than the weight of the shortest path
// Times() 'opts.weight_threshold'. When 'opts.state_threshold !=
// kNoStateId', 'ofst' will be restricted further to have at most
// 'opts.state_threshold' states. Weights need to be commutative and
// have the path property. The weight 'w' of any cycle needs to be
// bounded, i.e., 'Plus(w, W::One()) = One()'.
template <class Arc, class ArcFilter>
void Prune(const Fst<Arc> &ifst, MutableFst<Arc> *ofst,
const PruneOptions<Arc, ArcFilter> &opts) {
typedef typename Arc::Weight Weight;
typedef typename Arc::StateId StateId;
if ((Weight::Properties() & (kPath | kCommutative)) !=
(kPath | kCommutative)) {
FSTERROR() << "Prune: Weight needs to have the path property and"
<< " be commutative: " << Weight::Type();
ofst->SetProperties(kError, kError);
return;
}
ofst->DeleteStates();
ofst->SetInputSymbols(ifst.InputSymbols());
ofst->SetOutputSymbols(ifst.OutputSymbols());
if (ifst.Start() == kNoStateId) return;
NaturalLess<Weight> less;
if (less(opts.weight_threshold, Weight::One()) || (opts.state_threshold == 0))
return;
std::vector<Weight> idistance;
std::vector<Weight> tmp;
if (!opts.distance) ShortestDistance(ifst, &tmp, true, opts.delta);
const std::vector<Weight> *fdistance = opts.distance ? opts.distance : &tmp;
if ((fdistance->size() <= ifst.Start()) ||
((*fdistance)[ifst.Start()] == Weight::Zero())) {
return;
}
PruneCompare<StateId, Weight> compare(idistance, *fdistance);
using StateHeap = Heap<StateId, PruneCompare<StateId, Weight>>;
StateHeap heap(compare);
std::vector<StateId> copy;
std::vector<size_t> enqueued;
std::vector<bool> visited;
StateId s = ifst.Start();
Weight limit = Times(s < fdistance->size() ? (*fdistance)[s] : Weight::Zero(),
opts.weight_threshold);
while (copy.size() <= s) copy.push_back(kNoStateId);
copy[s] = ofst->AddState();
ofst->SetStart(copy[s]);
while (idistance.size() <= s) idistance.push_back(Weight::Zero());
idistance[s] = Weight::One();
while (enqueued.size() <= s) {
enqueued.push_back(StateHeap::kNoKey);
visited.push_back(false);
}
enqueued[s] = heap.Insert(s);
while (!heap.Empty()) {
s = heap.Top();
heap.Pop();
enqueued[s] = StateHeap::kNoKey;
visited[s] = true;
if (!less(limit, Times(idistance[s], ifst.Final(s))))
ofst->SetFinal(copy[s], ifst.Final(s));
for (ArcIterator<Fst<Arc>> ait(ifst, s); !ait.Done(); ait.Next()) {
const Arc &arc = ait.Value();
if (!opts.filter(arc)) continue;
Weight weight =
Times(Times(idistance[s], arc.weight),
arc.nextstate < fdistance->size() ? (*fdistance)[arc.nextstate]
: Weight::Zero());
if (less(limit, weight)) continue;
if ((opts.state_threshold != kNoStateId) &&
(ofst->NumStates() >= opts.state_threshold))
continue;
while (idistance.size() <= arc.nextstate)
idistance.push_back(Weight::Zero());
if (less(Times(idistance[s], arc.weight), idistance[arc.nextstate]))
idistance[arc.nextstate] = Times(idistance[s], arc.weight);
while (copy.size() <= arc.nextstate) copy.push_back(kNoStateId);
if (copy[arc.nextstate] == kNoStateId)
copy[arc.nextstate] = ofst->AddState();
ofst->AddArc(copy[s], Arc(arc.ilabel, arc.olabel, arc.weight,
copy[arc.nextstate]));
while (enqueued.size() <= arc.nextstate) {
enqueued.push_back(StateHeap::kNoKey);
visited.push_back(false);
}
if (visited[arc.nextstate]) continue;
if (enqueued[arc.nextstate] == StateHeap::kNoKey)
enqueued[arc.nextstate] = heap.Insert(arc.nextstate);
else
heap.Update(enqueued[arc.nextstate], arc.nextstate);
}
}
}
// Pruning algorithm: this version writes the pruned input Fst to an
// output MutableFst and simply takes the pruning threshold as an
// argument. 'ofst' contains states and arcs that belong to a
// successful path in 'ifst' whose weight is no more than
// the weight of the shortest path Times() 'weight_threshold'. When
// 'state_threshold != kNoStateId', 'ofst' will be restricted further
// to have at most 'opts.state_threshold' states. Weights need to be
// commutative and have the path property. The weight 'w' of any cycle
// needs to be bounded, i.e., 'Plus(w, W::One()) = W::One()'.
template <class Arc>
void Prune(const Fst<Arc> &ifst, MutableFst<Arc> *ofst,
typename Arc::Weight weight_threshold,
typename Arc::StateId state_threshold = kNoStateId,
float delta = kDelta) {
PruneOptions<Arc, AnyArcFilter<Arc>> opts(weight_threshold, state_threshold,
AnyArcFilter<Arc>(), 0, delta);
Prune(ifst, ofst, opts);
}
} // namespace fst
#endif // FST_LIB_PRUNE_H_
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