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authorredpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f>2010-06-22 05:12:27 +0000
committerredpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f>2010-06-22 05:12:27 +0000
commit0172721855098ca02b207231a654dffa5e4eb1c9 (patch)
tree8069c3a62e2d72bd64a2cdeee9724b2679c8a56b /decoder/maxtrans_blunsom.cc
parent37728b8be4d0b3df9da81fdda2198ff55b4b2d91 (diff)
initial checkin
git-svn-id: https://ws10smt.googlecode.com/svn/trunk@2 ec762483-ff6d-05da-a07a-a48fb63a330f
Diffstat (limited to 'decoder/maxtrans_blunsom.cc')
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diff --git a/decoder/maxtrans_blunsom.cc b/decoder/maxtrans_blunsom.cc
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+#include "apply_models.h"
+
+#include <vector>
+#include <algorithm>
+#include <tr1/unordered_map>
+#include <tr1/unordered_set>
+
+#include <boost/tuple/tuple.hpp>
+#include <boost/functional/hash.hpp>
+
+#include "tdict.h"
+#include "hg.h"
+#include "ff.h"
+
+using boost::tuple;
+using namespace std;
+using namespace std::tr1;
+
+namespace Hack {
+
+struct Candidate;
+typedef SmallVector JVector;
+typedef vector<Candidate*> CandidateHeap;
+typedef vector<Candidate*> CandidateList;
+
+// life cycle: candidates are created, placed on the heap
+// and retrieved by their estimated cost, when they're
+// retrieved, they're incorporated into the +LM hypergraph
+// where they also know the head node index they are
+// attached to. After they are added to the +LM hypergraph
+// inside_prob_ and est_prob_ fields may be updated as better
+// derivations are found (this happens since the successor's
+// of derivation d may have a better score- they are
+// explored lazily). However, the updates don't happen
+// when a candidate is in the heap so maintaining the heap
+// property is not an issue.
+struct Candidate {
+ int node_index_; // -1 until incorporated
+ // into the +LM forest
+ const Hypergraph::Edge* in_edge_; // in -LM forest
+ Hypergraph::Edge out_edge_;
+ vector<WordID> state_;
+ const JVector j_;
+ prob_t inside_prob_; // these are fixed until the cand
+ // is popped, then they may be updated
+ prob_t est_prob_;
+
+ Candidate(const Hypergraph::Edge& e,
+ const JVector& j,
+ const vector<CandidateList>& D,
+ bool is_goal) :
+ node_index_(-1),
+ in_edge_(&e),
+ j_(j) {
+ InitializeCandidate(D, is_goal);
+ }
+
+ // used to query uniqueness
+ Candidate(const Hypergraph::Edge& e,
+ const JVector& j) : in_edge_(&e), j_(j) {}
+
+ bool IsIncorporatedIntoHypergraph() const {
+ return node_index_ >= 0;
+ }
+
+ void InitializeCandidate(const vector<vector<Candidate*> >& D,
+ const bool is_goal) {
+ const Hypergraph::Edge& in_edge = *in_edge_;
+ out_edge_.rule_ = in_edge.rule_;
+ out_edge_.feature_values_ = in_edge.feature_values_;
+ Hypergraph::TailNodeVector& tail = out_edge_.tail_nodes_;
+ tail.resize(j_.size());
+ prob_t p = prob_t::One();
+ // cerr << "\nEstimating application of " << in_edge.rule_->AsString() << endl;
+ vector<const vector<WordID>* > ants(tail.size());
+ for (int i = 0; i < tail.size(); ++i) {
+ const Candidate& ant = *D[in_edge.tail_nodes_[i]][j_[i]];
+ ants[i] = &ant.state_;
+ assert(ant.IsIncorporatedIntoHypergraph());
+ tail[i] = ant.node_index_;
+ p *= ant.inside_prob_;
+ }
+ prob_t edge_estimate = prob_t::One();
+ if (is_goal) {
+ assert(tail.size() == 1);
+ out_edge_.edge_prob_ = in_edge.edge_prob_;
+ } else {
+ in_edge.rule_->ESubstitute(ants, &state_);
+ out_edge_.edge_prob_ = in_edge.edge_prob_;
+ }
+ inside_prob_ = out_edge_.edge_prob_ * p;
+ est_prob_ = inside_prob_ * edge_estimate;
+ }
+};
+
+ostream& operator<<(ostream& os, const Candidate& cand) {
+ os << "CAND[";
+ if (!cand.IsIncorporatedIntoHypergraph()) { os << "PENDING "; }
+ else { os << "+LM_node=" << cand.node_index_; }
+ os << " edge=" << cand.in_edge_->id_;
+ os << " j=<";
+ for (int i = 0; i < cand.j_.size(); ++i)
+ os << (i==0 ? "" : " ") << cand.j_[i];
+ os << "> vit=" << log(cand.inside_prob_);
+ os << " est=" << log(cand.est_prob_);
+ return os << ']';
+}
+
+struct HeapCandCompare {
+ bool operator()(const Candidate* l, const Candidate* r) const {
+ return l->est_prob_ < r->est_prob_;
+ }
+};
+
+struct EstProbSorter {
+ bool operator()(const Candidate* l, const Candidate* r) const {
+ return l->est_prob_ > r->est_prob_;
+ }
+};
+
+// the same candidate <edge, j> can be added multiple times if
+// j is multidimensional (if you're going NW in Manhattan, you
+// can first go north, then west, or you can go west then north)
+// this is a hash function on the relevant variables from
+// Candidate to enforce this.
+struct CandidateUniquenessHash {
+ size_t operator()(const Candidate* c) const {
+ size_t x = 5381;
+ x = ((x << 5) + x) ^ c->in_edge_->id_;
+ for (int i = 0; i < c->j_.size(); ++i)
+ x = ((x << 5) + x) ^ c->j_[i];
+ return x;
+ }
+};
+
+struct CandidateUniquenessEquals {
+ bool operator()(const Candidate* a, const Candidate* b) const {
+ return (a->in_edge_ == b->in_edge_) && (a->j_ == b->j_);
+ }
+};
+
+typedef unordered_set<const Candidate*, CandidateUniquenessHash, CandidateUniquenessEquals> UniqueCandidateSet;
+typedef unordered_map<vector<WordID>, Candidate*, boost::hash<vector<WordID> > > State2Node;
+
+class MaxTransBeamSearch {
+
+public:
+ MaxTransBeamSearch(const Hypergraph& i, int pop_limit, Hypergraph* o) :
+ in(i),
+ out(*o),
+ D(in.nodes_.size()),
+ pop_limit_(pop_limit) {
+ cerr << " Finding max translation (cube pruning, pop_limit = " << pop_limit_ << ')' << endl;
+ }
+
+ void Apply() {
+ int num_nodes = in.nodes_.size();
+ int goal_id = num_nodes - 1;
+ int pregoal = goal_id - 1;
+ assert(in.nodes_[pregoal].out_edges_.size() == 1);
+ cerr << " ";
+ for (int i = 0; i < in.nodes_.size(); ++i) {
+ cerr << '.';
+ KBest(i, i == goal_id);
+ }
+ cerr << endl;
+ int best_node = D[goal_id].front()->in_edge_->tail_nodes_.front();
+ Candidate& best = *D[best_node].front();
+ cerr << " Best path: " << log(best.inside_prob_)
+ << "\t" << log(best.est_prob_) << endl;
+ cout << TD::GetString(D[best_node].front()->state_) << endl;
+ FreeAll();
+ }
+
+ private:
+ void FreeAll() {
+ for (int i = 0; i < D.size(); ++i) {
+ CandidateList& D_i = D[i];
+ for (int j = 0; j < D_i.size(); ++j)
+ delete D_i[j];
+ }
+ D.clear();
+ }
+
+ void IncorporateIntoPlusLMForest(Candidate* item, State2Node* s2n, CandidateList* freelist) {
+ Hypergraph::Edge* new_edge = out.AddEdge(item->out_edge_.rule_, item->out_edge_.tail_nodes_);
+ new_edge->feature_values_ = item->out_edge_.feature_values_;
+ new_edge->edge_prob_ = item->out_edge_.edge_prob_;
+ Candidate*& o_item = (*s2n)[item->state_];
+ if (!o_item) o_item = item;
+
+ int& node_id = o_item->node_index_;
+ if (node_id < 0) {
+ Hypergraph::Node* new_node = out.AddNode(in.nodes_[item->in_edge_->head_node_].cat_);
+ node_id = new_node->id_;
+ }
+ Hypergraph::Node* node = &out.nodes_[node_id];
+ out.ConnectEdgeToHeadNode(new_edge, node);
+
+ if (item != o_item) {
+ assert(o_item->state_ == item->state_); // sanity check!
+ o_item->est_prob_ += item->est_prob_;
+ o_item->inside_prob_ += item->inside_prob_;
+ freelist->push_back(item);
+ }
+ }
+
+ void KBest(const int vert_index, const bool is_goal) {
+ // cerr << "KBest(" << vert_index << ")\n";
+ CandidateList& D_v = D[vert_index];
+ assert(D_v.empty());
+ const Hypergraph::Node& v = in.nodes_[vert_index];
+ // cerr << " has " << v.in_edges_.size() << " in-coming edges\n";
+ const vector<int>& in_edges = v.in_edges_;
+ CandidateHeap cand;
+ CandidateList freelist;
+ cand.reserve(in_edges.size());
+ UniqueCandidateSet unique_cands;
+ for (int i = 0; i < in_edges.size(); ++i) {
+ const Hypergraph::Edge& edge = in.edges_[in_edges[i]];
+ const JVector j(edge.tail_nodes_.size(), 0);
+ cand.push_back(new Candidate(edge, j, D, is_goal));
+ assert(unique_cands.insert(cand.back()).second); // these should all be unique!
+ }
+// cerr << " making heap of " << cand.size() << " candidates\n";
+ make_heap(cand.begin(), cand.end(), HeapCandCompare());
+ State2Node state2node; // "buf" in Figure 2
+ int pops = 0;
+ while(!cand.empty() && pops < pop_limit_) {
+ pop_heap(cand.begin(), cand.end(), HeapCandCompare());
+ Candidate* item = cand.back();
+ cand.pop_back();
+ // cerr << "POPPED: " << *item << endl;
+ PushSucc(*item, is_goal, &cand, &unique_cands);
+ IncorporateIntoPlusLMForest(item, &state2node, &freelist);
+ ++pops;
+ }
+ D_v.resize(state2node.size());
+ int c = 0;
+ for (State2Node::iterator i = state2node.begin(); i != state2node.end(); ++i)
+ D_v[c++] = i->second;
+ sort(D_v.begin(), D_v.end(), EstProbSorter());
+ // cerr << " expanded to " << D_v.size() << " nodes\n";
+
+ for (int i = 0; i < cand.size(); ++i)
+ delete cand[i];
+ // freelist is necessary since even after an item merged, it still stays in
+ // the unique set so it can't be deleted til now
+ for (int i = 0; i < freelist.size(); ++i)
+ delete freelist[i];
+ }
+
+ void PushSucc(const Candidate& item, const bool is_goal, CandidateHeap* pcand, UniqueCandidateSet* cs) {
+ CandidateHeap& cand = *pcand;
+ for (int i = 0; i < item.j_.size(); ++i) {
+ JVector j = item.j_;
+ ++j[i];
+ if (j[i] < D[item.in_edge_->tail_nodes_[i]].size()) {
+ Candidate query_unique(*item.in_edge_, j);
+ if (cs->count(&query_unique) == 0) {
+ Candidate* new_cand = new Candidate(*item.in_edge_, j, D, is_goal);
+ cand.push_back(new_cand);
+ push_heap(cand.begin(), cand.end(), HeapCandCompare());
+ assert(cs->insert(new_cand).second); // insert into uniqueness set, sanity check
+ }
+ }
+ }
+ }
+
+ const Hypergraph& in;
+ Hypergraph& out;
+
+ vector<CandidateList> D; // maps nodes in in-HG to the
+ // equivalent nodes (many due to state
+ // splits) in the out-HG.
+ const int pop_limit_;
+};
+
+// each node in the graph has one of these, it keeps track of
+void MaxTrans(const Hypergraph& in,
+ int beam_size) {
+ Hypergraph out;
+ MaxTransBeamSearch ma(in, beam_size, &out);
+ ma.Apply();
+}
+
+}