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#include "hg_intersect.h"
#include <vector>
#include <tr1/unordered_map>
#include <boost/lexical_cast.hpp>
#include <boost/functional/hash.hpp>
#include "tdict.h"
#include "hg.h"
#include "trule.h"
#include "wordid.h"
#include "bottom_up_parser.h"
using boost::lexical_cast;
using namespace std::tr1;
using namespace std;
struct RuleFilter {
unordered_map<vector<WordID>, bool, boost::hash<vector<WordID> > > exists_;
bool true_lattice;
RuleFilter(const Lattice& target, int max_phrase_size) {
true_lattice = false;
for (int i = 0; i < target.size(); ++i) {
vector<WordID> phrase;
int lim = min(static_cast<int>(target.size()), i + max_phrase_size);
for (int j = i; j < lim; ++j) {
if (target[j].size() > 1) { true_lattice = true; break; }
phrase.push_back(target[j][0].label);
exists_[phrase] = true;
}
}
vector<WordID> sos(1, TD::Convert("<s>"));
exists_[sos] = true;
}
bool operator()(const TRule& r) const {
// TODO do some smarter filtering for lattices
if (true_lattice) return false; // don't filter "true lattice" input
const vector<WordID>& e = r.e();
for (int i = 0; i < e.size(); ++i) {
if (e[i] <= 0) continue;
vector<WordID> phrase;
for (int j = i; j < e.size(); ++j) {
if (e[j] <= 0) break;
phrase.push_back(e[j]);
if (exists_.count(phrase) == 0) return true;
}
}
return false;
}
};
static bool FastLinearIntersect(const Lattice& target, Hypergraph* hg) {
cerr << " Fast linear-chain intersection...\n";
vector<bool> prune(hg->edges_.size(), false);
set<int> cov;
for (int i = 0; i < prune.size(); ++i) {
Hypergraph::Edge& edge = hg->edges_[i];
if (edge.Arity() == 0) {
const int trg_index = edge.prev_i_;
const WordID trg = target[trg_index][0].label;
assert(edge.rule_->EWords() == 1);
prune[i] = (edge.rule_->e_[0] != trg);
if (!prune[i]) {
cov.insert(trg_index);
swap(edge.prev_i_, edge.i_);
swap(edge.prev_j_, edge.j_);
}
}
}
hg->PruneEdges(prune, true);
return (cov.size() == target.size());
}
bool HG::Intersect(const Lattice& target, Hypergraph* hg) {
// there are a number of faster algorithms available for restricted
// classes of hypergraph and/or target.
if (hg->IsLinearChain() && target.IsSentence())
return FastLinearIntersect(target, hg);
vector<bool> rem(hg->edges_.size(), false);
const RuleFilter filter(target, 15); // TODO make configurable
for (int i = 0; i < rem.size(); ++i)
rem[i] = filter(*hg->edges_[i].rule_);
hg->PruneEdges(rem, true);
const int nedges = hg->edges_.size();
const int nnodes = hg->nodes_.size();
TextGrammar* g = new TextGrammar;
GrammarPtr gp(g);
vector<int> cats(nnodes);
// each node in the translation forest becomes a "non-terminal" in the new
// grammar, create the labels here
for (int i = 0; i < nnodes; ++i)
cats[i] = TD::Convert("CAT_" + lexical_cast<string>(i)) * -1;
// construct the grammar
for (int i = 0; i < nedges; ++i) {
const Hypergraph::Edge& edge = hg->edges_[i];
const vector<WordID>& tgt = edge.rule_->e();
const vector<WordID>& src = edge.rule_->f();
TRulePtr rule(new TRule);
rule->prev_i = edge.i_;
rule->prev_j = edge.j_;
rule->lhs_ = cats[edge.head_node_];
vector<WordID>& f = rule->f_;
vector<WordID>& e = rule->e_;
f.resize(tgt.size()); // swap source and target, since the parser
e.resize(src.size()); // parses using the source side!
Hypergraph::TailNodeVector tn(edge.tail_nodes_.size());
int ntc = 0;
for (int j = 0; j < tgt.size(); ++j) {
const WordID& cur = tgt[j];
if (cur > 0) {
f[j] = cur;
} else {
tn[ntc++] = cur;
f[j] = cats[edge.tail_nodes_[-cur]];
}
}
ntc = 0;
for (int j = 0; j < src.size(); ++j) {
const WordID& cur = src[j];
if (cur > 0) {
e[j] = cur;
} else {
e[j] = tn[ntc++];
}
}
rule->scores_ = edge.feature_values_;
rule->parent_rule_ = edge.rule_;
rule->ComputeArity();
//cerr << "ADD: " << rule->AsString() << endl;
g->AddRule(rule);
}
g->SetMaxSpan(target.size() + 1);
const string& new_goal = TD::Convert(cats.back() * -1);
vector<GrammarPtr> grammars(1, gp);
Hypergraph tforest;
ExhaustiveBottomUpParser parser(new_goal, grammars);
if (!parser.Parse(target, &tforest))
return false;
else
hg->swap(tforest);
return true;
}
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