Merge remote-tracking branch 'upstream/master'

7 files changed, 200 insertions, 0 deletions

diff --git a/rst_parser/Makefile.am b/rst_parser/Makefile.am
new file mode 100644
index 00000000..e97ab5c5
--- /dev/null
+++ b/rst_parser/Makefile.am
@@ -0,0 +1,19 @@
+bin_PROGRAMS = \
+  mst_train
+
+noinst_PROGRAMS = \
+  rst_test
+
+TESTS = rst_test
+
+noinst_LIBRARIES = librst.a
+
+librst_a_SOURCES = arc_factored.cc rst.cc
+
+mst_train_SOURCES = mst_train.cc
+mst_train_LDADD = librst.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz
+
+rst_test_SOURCES = rst_test.cc
+rst_test_LDADD = librst.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz
+
+AM_CPPFLAGS = -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I$(top_srcdir)/decoder -I$(top_srcdir)/utils -I$(top_srcdir)/mteval -I../klm
diff --git a/rst_parser/arc_factored.cc b/rst_parser/arc_factored.cc
new file mode 100644
index 00000000..1e75600b
--- /dev/null
+++ b/rst_parser/arc_factored.cc
@@ -0,0 +1,31 @@
+#include "arc_factored.h"
+
+#include <set>
+
+#include <boost/pending/disjoint_sets.hpp>
+
+using namespace std;
+using namespace boost;
+
+// based on Trajan 1977
+void ArcFactoredForest::MaximumSpanningTree(SpanningTree* 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, h, rset;
+  vector<pair<short, short> > enter(num_words_ + 1);
+  for (unsigned i = 0; i <= num_words_; ++i) {
+    strongly.make_set(i);
+    weakly.make_set(i);
+    roots.insert(i);
+  }
+  while(!roots.empty()) {
+    set<unsigned>::iterator it = roots.begin();
+    const unsigned k = *it;
+    roots.erase(it);
+    cerr << "k=" << k << endl;
+    pair<short,short> ij; // TODO = Max(k);
+  }
+}
+
diff --git a/rst_parser/arc_factored.h b/rst_parser/arc_factored.h
new file mode 100644
index 00000000..e99be482
--- /dev/null
+++ b/rst_parser/arc_factored.h
@@ -0,0 +1,88 @@
+#ifndef _ARC_FACTORED_H_
+#define _ARC_FACTORED_H_
+
+#include <iostream>
+#include <cassert>
+#include <vector>
+#include <utility>
+#include "array2d.h"
+#include "sparse_vector.h"
+#include "prob.h"
+#include "weights.h"
+
+struct SpanningTree {
+  SpanningTree() : roots(1, -1) {}
+  std::vector<short> roots; // unless multiroot trees are supported, this
+                            // will have a single member
+  std::vector<std::pair<short, short> > h_m_pairs;
+};
+
+class ArcFactoredForest {
+ public:
+  explicit ArcFactoredForest(short num_words) :
+      num_words_(num_words),
+      root_edges_(num_words),
+      edges_(num_words, num_words) {
+    for (int h = 0; h < num_words; ++h) {
+      for (int m = 0; m < num_words; ++m) {
+        edges_(h, m).h = h + 1;
+        edges_(h, m).m = m + 1;
+      }
+      root_edges_[h].h = 0;
+      root_edges_[h].m = h + 1;
+    }
+  }
+
+  // compute the maximum spanning tree based on the current weighting
+  // using the O(n^2) CLE algorithm
+  void MaximumSpanningTree(SpanningTree* st) const;
+
+  struct Edge {
+    Edge() : h(), m(), features(), edge_prob(prob_t::Zero()) {}
+    short h;
+    short m;
+    SparseVector<weight_t> features;
+    prob_t edge_prob;
+  };
+
+  const Edge& operator()(short h, short m) const {
+    assert(m > 0);
+    assert(m <= num_words_);
+    assert(h >= 0);
+    assert(h <= num_words_);
+    return h ? edges_(h - 1, m - 1) : root_edges_[m - 1];
+  }
+
+  Edge& operator()(short h, short m) {
+    assert(m > 0);
+    assert(m <= num_words_);
+    assert(h >= 0);
+    assert(h <= num_words_);
+    return h ? edges_(h - 1, m - 1) : root_edges_[m - 1];
+  }
+
+  template <class V>
+  void Reweight(const V& weights) {
+    for (int m = 0; m < num_words_; ++m) {
+      for (int h = 0; h < num_words_; ++h) {
+        if (h != m) {
+          Edge& e = edges_(h, m);
+          e.edge_prob.logeq(e.features.dot(weights));
+        }
+      }
+      Edge& e = root_edges_[m];
+      e.edge_prob.logeq(e.features.dot(weights));
+    }
+  }
+
+ private:
+  unsigned num_words_;
+  std::vector<Edge> root_edges_;
+  Array2D<Edge> edges_;
+};
+
+inline std::ostream& operator<<(std::ostream& os, const ArcFactoredForest::Edge& edge) {
+  return os << "(" << edge.h << " < " << edge.m << ")";
+}
+
+#endif
diff --git a/rst_parser/mst_train.cc b/rst_parser/mst_train.cc
new file mode 100644
index 00000000..7b5af4c1
--- /dev/null
+++ b/rst_parser/mst_train.cc
@@ -0,0 +1,12 @@
+#include "arc_factored.h"
+
+#include <iostream>
+
+using namespace std;
+
+int main(int argc, char** argv) {
+  ArcFactoredForest af(5);
+  cerr << af(0,3) << endl;
+  return 0;
+}
+
diff --git a/rst_parser/rst.cc b/rst_parser/rst.cc
new file mode 100644
index 00000000..f6b295b3
--- /dev/null
+++ b/rst_parser/rst.cc
@@ -0,0 +1,7 @@
+#include "rst.h"
+
+using namespace std;
+
+StochasticForest::StochasticForest(const ArcFactoredForest& af) {
+}
+
diff --git a/rst_parser/rst.h b/rst_parser/rst.h
new file mode 100644
index 00000000..865871eb
--- /dev/null
+++ b/rst_parser/rst.h
@@ -0,0 +1,10 @@
+#ifndef _RST_H_
+#define _RST_H_
+
+#include "arc_factored.h"
+
+struct StochasticForest {
+  explicit StochasticForest(const ArcFactoredForest& af);
+};
+
+#endif
diff --git a/rst_parser/rst_test.cc b/rst_parser/rst_test.cc
new file mode 100644
index 00000000..e8fe706e
--- /dev/null
+++ b/rst_parser/rst_test.cc
@@ -0,0 +1,33 @@
+#include "arc_factored.h"
+
+#include <iostream>
+
+using namespace std;
+
+int main(int argc, char** argv) {
+  // John saw Mary
+  //   (H -> M)
+  //   (1 -> 2) 20
+  //   (1 -> 3) 3
+  //   (2 -> 1) 20
+  //   (2 -> 3) 30
+  //   (3 -> 2) 0
+  //   (3 -> 1) 11
+  //   (0, 2) 10
+  //   (0, 1) 9
+  //   (0, 3) 9
+  ArcFactoredForest af(3);
+  af(1,2).edge_prob.logeq(20);
+  af(1,3).edge_prob.logeq(3);
+  af(2,1).edge_prob.logeq(20);
+  af(2,3).edge_prob.logeq(30);
+  af(3,2).edge_prob.logeq(0);
+  af(3,1).edge_prob.logeq(11);
+  af(0,2).edge_prob.logeq(10);
+  af(0,1).edge_prob.logeq(9);
+  af(0,3).edge_prob.logeq(9);
+  SpanningTree tree;
+  af.MaximumSpanningTree(&tree);
+  return 0;
+}
+