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#include "arc_factored.h"
#include <set>
#include <tr1/unordered_set>
#include <boost/pending/disjoint_sets.hpp>
#include <boost/functional/hash.hpp>
#include "arc_ff.h"
using namespace std;
using namespace std::tr1;
using namespace boost;
void EdgeSubset::ExtractFeatures(const TaggedSentence& sentence,
const ArcFeatureFunctions& ffs,
SparseVector<double>* features) const {
SparseVector<weight_t> efmap;
for (int j = 0; j < h_m_pairs.size(); ++j) {
efmap.clear();
ffs.EdgeFeatures(sentence, h_m_pairs[j].first,
h_m_pairs[j].second,
&efmap);
(*features) += efmap;
}
for (int j = 0; j < roots.size(); ++j) {
efmap.clear();
ffs.EdgeFeatures(sentence, -1, roots[j], &efmap);
(*features) += efmap;
}
}
void ArcFactoredForest::ExtractFeatures(const TaggedSentence& sentence,
const ArcFeatureFunctions& ffs) {
for (int m = 0; m < num_words_; ++m) {
for (int h = 0; h < num_words_; ++h) {
ffs.EdgeFeatures(sentence, h, m, &edges_(h,m).features);
}
ffs.EdgeFeatures(sentence, -1, m, &root_edges_[m].features);
}
}
void ArcFactoredForest::PickBestParentForEachWord(EdgeSubset* st) const {
for (int m = 0; m < num_words_; ++m) {
int best_head = -2;
prob_t best_score;
for (int h = -1; h < num_words_; ++h) {
const Edge& edge = (*this)(h,m);
if (best_head < -1 || edge.edge_prob > best_score) {
best_score = edge.edge_prob;
best_head = h;
}
}
assert(best_head >= -1);
if (best_head >= 0)
st->h_m_pairs.push_back(make_pair<short,short>(best_head, m));
else
st->roots.push_back(m);
}
}
struct WeightedEdge {
WeightedEdge() : h(), m(), weight() {}
WeightedEdge(short hh, short mm, float w) : h(hh), m(mm), weight(w) {}
short h, m;
float weight;
inline bool operator==(const WeightedEdge& o) const {
return h == o.h && m == o.m && weight == o.weight;
}
inline bool operator!=(const WeightedEdge& o) const {
return h != o.h || m != o.m || weight != o.weight;
}
};
inline bool operator<(const WeightedEdge& l, const WeightedEdge& o) { return l.weight < o.weight; }
inline size_t hash_value(const WeightedEdge& e) { return reinterpret_cast<const size_t&>(e); }
struct PriorityQueue {
void push(const WeightedEdge& e) {}
const WeightedEdge& top() const {
static WeightedEdge w(1,2,3);
return w;
}
void pop() {}
void increment_all(float p) {}
};
// based on Trajan 1977
void ArcFactoredForest::MaximumSpanningTree(EdgeSubset* st) const {
typedef disjoint_sets_with_storage<identity_property_map, identity_property_map,
find_with_full_path_compression> DisjointSet;
DisjointSet strongly(num_words_ + 1);
DisjointSet weakly(num_words_ + 1);
set<unsigned> roots, rset;
unordered_set<WeightedEdge, boost::hash<WeightedEdge> > h;
vector<PriorityQueue> qs(num_words_ + 1);
vector<WeightedEdge> enter(num_words_ + 1);
vector<unsigned> mins(num_words_ + 1);
const WeightedEdge kDUMMY(0,0,0.0f);
for (unsigned i = 0; i <= num_words_; ++i) {
if (i > 0) {
// I(i) incidence on i -- all incoming edges
for (unsigned j = 0; j <= num_words_; ++j) {
qs[i].push(WeightedEdge(j, i, Weight(j,i)));
}
}
strongly.make_set(i);
weakly.make_set(i);
roots.insert(i);
enter[i] = kDUMMY;
mins[i] = i;
}
while(!roots.empty()) {
set<unsigned>::iterator it = roots.begin();
const unsigned k = *it;
roots.erase(it);
cerr << "k=" << k << endl;
WeightedEdge ij = qs[k].top(); // MAX(k)
qs[k].pop();
if (ij.weight <= 0) {
rset.insert(k);
} else {
if (strongly.find_set(ij.h) == k) {
roots.insert(k);
} else {
h.insert(ij);
if (weakly.find_set(ij.h) != weakly.find_set(ij.m)) {
weakly.union_set(ij.h, ij.m);
enter[k] = ij;
} else {
unsigned vertex = 0;
float val = 99999999999;
WeightedEdge xy = ij;
while(xy != kDUMMY) {
if (xy.weight < val) {
val = xy.weight;
vertex = strongly.find_set(xy.m);
}
xy = enter[strongly.find_set(xy.h)];
}
qs[k].increment_all(val - ij.weight);
mins[k] = mins[vertex];
xy = enter[strongly.find_set(ij.h)];
while (xy != kDUMMY) {
}
}
}
}
}
}
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