initial checkin

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@2 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 309 insertions, 0 deletions

diff --git a/decoder/tromble_loss.cc b/decoder/tromble_loss.cc
new file mode 100644
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--- /dev/null
+++ b/decoder/tromble_loss.cc
@@ -0,0 +1,309 @@
+#include "tromble_loss.h"
+
+#include <boost/algorithm/string/predicate.hpp>
+#include <boost/circular_buffer.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/lexical_cast.hpp>
+#include <boost/range/iterator_range.hpp>
+#include <boost/tokenizer.hpp>
+#include <boost/unordered_map.hpp>
+
+#include <cmath>
+#include <fstream>
+#include <vector>
+
+#include "sentence_metadata.h"
+#include "trule.h"
+#include "tdict.h"
+
+using namespace std;
+
+namespace {
+
+typedef unsigned char GramCount;
+
+struct RefCounts {
+  GramCount max;
+  std::vector<GramCount> refs;
+  size_t length;
+};
+
+typedef boost::unordered_map<std::vector<WordID>, size_t, boost::hash<std::vector<WordID> > > NGramMap;
+
+// Take all the n-grams in the references and stuff them into ngrams.
+void MakeNGramMapFromReferences(const vector<vector<WordID> > &references,
+                                int n,
+                                vector<RefCounts> *counts,
+                                NGramMap *ngrams) {
+  ngrams->clear();
+  std::pair<vector<WordID>, size_t> insert_me;
+  vector<WordID> &ngram = insert_me.first;
+  ngram.reserve(n);
+  size_t &id = insert_me.second;
+  id = 0;
+  for (int refi = 0; refi < references.size(); ++refi) {
+    const vector<WordID>& ref = references[refi];
+    const int s = ref.size();
+    for (int j=0; j<s; ++j) {
+      const int remaining = s-j;
+      const int k = (n < remaining ? n : remaining);
+      ngram.clear();
+      for (unsigned int i = 0; i < k; ++i) {
+        ngram.push_back(ref[j + i]);
+        std::pair<NGramMap::iterator, bool> ret(ngrams->insert(insert_me));
+        if (ret.second) {
+          counts->resize(id + 1);
+          RefCounts &ref_counts = counts->back();
+          ref_counts.max = 1;
+          ref_counts.refs.resize(references.size());
+          ref_counts.refs[refi] = 1;
+          ref_counts.length = ngram.size();
+          ++id;
+        } else {
+          RefCounts &ref_counts = (*counts)[ret.first->second];
+          ref_counts.max = std::max(ref_counts.max, ++ref_counts.refs[refi]);
+        }
+      }
+    }
+  }
+}
+
+struct MutableState {
+  MutableState(void *from, size_t n) : length(reinterpret_cast<size_t*>(from)), left(reinterpret_cast<WordID *>(length + 1)), right(left + n - 1), counts(reinterpret_cast<GramCount *>(right + n - 1)) {}
+  size_t *length;
+  WordID *left, *right;
+  GramCount *counts;
+  static size_t Size(size_t n, size_t bound_ngram_id) { return sizeof(size_t) + (n - 1) * 2 * sizeof(WordID) + bound_ngram_id * sizeof(GramCount); }
+};
+
+struct ConstState {
+  ConstState(const void *from, size_t n) : length(reinterpret_cast<const size_t*>(from)), left(reinterpret_cast<const WordID *>(length + 1)), right(left + n - 1), counts(reinterpret_cast<const GramCount *>(right + n - 1)) {}
+  const size_t *length;
+  const WordID *left, *right;
+  const GramCount *counts;
+  static size_t Size(size_t n, size_t bound_ngram_id) { return sizeof(size_t) + (n - 1) * 2 * sizeof(WordID) + bound_ngram_id * sizeof(GramCount); }
+};
+
+template <class T> struct CompatibleHashRange : public std::unary_function<const boost::iterator_range<T> &, size_t> {
+  size_t operator()(const boost::iterator_range<T> &range) const {
+    return boost::hash_range(range.begin(), range.end());
+  }
+};
+
+template <class T> struct CompatibleEqualsRange : public std::binary_function<const boost::iterator_range<T> &, const std::vector<WordID> &, size_t> {
+  size_t operator()(const boost::iterator_range<T> &range, const std::vector<WordID> &vec) const {
+    return boost::algorithm::equals(range, vec);
+  }
+  size_t operator()(const std::vector<WordID> &vec, const boost::iterator_range<T> &range) const {
+    return boost::algorithm::equals(range, vec);
+  }
+};
+
+void AddWord(const boost::circular_buffer<WordID> &segment, size_t min_length, const NGramMap &ref_grams, GramCount *counters) {
+  typedef boost::circular_buffer<WordID>::const_iterator BufferIt;
+  typedef boost::iterator_range<BufferIt> SegmentRange;
+  if (segment.size() < min_length) return;
+#if 0
+  CompatibleHashRange<BufferIt> hasher;
+  CompatibleEqualsRange<BufferIt> equals;
+  for (BufferIt seg_start(segment.end() - min_length); ; --seg_start) {
+    NGramMap::const_iterator found = ref_grams.find(SegmentRange(seg_start, segment.end()));
+    if (found == ref_grams.end()) break;
+    ++counters[found->second];
+    if (seg_start == segment.begin()) break;
+  }
+#endif
+}
+
+} // namespace
+
+class TrombleLossComputerImpl {
+ public:
+  explicit TrombleLossComputerImpl(const std::string &params) : star_(TD::Convert("<{STAR}>")) {
+    typedef boost::tokenizer<boost::char_separator<char> > Tokenizer;
+    // Argument parsing
+    std::string ref_file_name;
+    Tokenizer tok(params, boost::char_separator<char>(" "));
+    Tokenizer::iterator i = tok.begin();
+    if (i == tok.end()) {
+      std::cerr << "TrombleLossComputer needs a reference file name." << std::endl;
+      exit(1);
+    }
+    ref_file_name = *i++;
+    if (i == tok.end()) {
+      std::cerr << "TrombleLossComputer needs to know how many references." << std::endl;
+      exit(1);
+    }
+    num_refs_ = boost::lexical_cast<unsigned int>(*i++);
+    for (; i != tok.end(); ++i) {
+     thetas_.push_back(boost::lexical_cast<double>(*i));
+    }
+    if (thetas_.empty()) {
+      std::cerr << "TrombleLossComputer is pointless with no weight on n-grams." << std::endl;
+      exit(1);
+    }
+
+    // Read references file.
+    std::ifstream ref_file(ref_file_name.c_str());
+    if (!ref_file) {
+      std::cerr << "Could not open TrombleLossComputer file " << ref_file_name << std::endl;
+      exit(1);
+    }
+    std::string ref;
+    vector<vector<WordID> > references(num_refs_);
+    bound_ngram_id_ = 0;
+    for (unsigned int sentence = 0; ref_file; ++sentence) {
+      for (unsigned int refidx = 0; refidx < num_refs_; ++refidx) {
+        if (!getline(ref_file, ref)) {
+          if (refidx == 0) break;
+          std::cerr << "Short read of " << refidx << " references for sentence " << sentence << std::endl;
+          exit(1);
+        }
+        TD::ConvertSentence(ref, &references[refidx]);
+      }
+      ref_ids_.resize(sentence + 1);
+      ref_counts_.resize(sentence + 1);
+      MakeNGramMapFromReferences(references, thetas_.size(), &ref_counts_.back(), &ref_ids_.back());
+      bound_ngram_id_ = std::max(bound_ngram_id_, ref_ids_.back().size());
+    }
+  }
+
+  size_t StateSize() const {
+    // n-1 boundary words plus counts for n-grams currently rendered as bytes even though most would fit in bits.
+    // Also, this is cached by higher up classes so no need to cache here.  
+    return MutableState::Size(thetas_.size(), bound_ngram_id_);
+  }
+
+  double Traversal(
+      const SentenceMetadata &smeta,
+      const TRule &rule,
+      const vector<const void*> &ant_contexts,
+      void *out_context) const {
+    // TODO: get refs from sentence metadata.  
+    // This will require resizable features.  
+    if (smeta.GetSentenceID() >= ref_ids_.size()) {
+      std::cerr << "Sentence ID " << smeta.GetSentenceID() << " doesn't have references; there are only " << ref_ids_.size() << " references." << std::endl;
+      exit(1);
+    }
+    const NGramMap &ngrams = ref_ids_[smeta.GetSentenceID()];
+    MutableState out_state(out_context, thetas_.size());
+    memset(out_state.counts, 0, bound_ngram_id_ * sizeof(GramCount));
+    boost::circular_buffer<WordID> history(thetas_.size());
+    std::vector<const void*>::const_iterator ant_context = ant_contexts.begin();
+    *out_state.length = 0;
+    size_t pushed = 0;
+    const size_t keep = thetas_.size() - 1;
+    for (vector<WordID>::const_iterator rhs = rule.e().begin(); rhs != rule.e().end(); ++rhs) {
+      if (*rhs < 1) {
+        assert(ant_context != ant_contexts.end());
+        // Constituent
+        ConstState rhs_state(*ant_context, thetas_.size());
+        *out_state.length += *rhs_state.length;
+        {
+          GramCount *accum = out_state.counts;
+          for (const GramCount *c = rhs_state.counts; c != rhs_state.counts + ngrams.size(); ++c, ++accum) {
+            *accum += *c;
+          }
+        }
+        const WordID *w = rhs_state.left;
+        bool long_constit = true;
+        for (size_t i = 1; i <= keep; ++i, ++w) {
+          if (*w == star_) {
+            long_constit = false;
+            break;
+          }
+          history.push_back(*w);
+          if (++pushed == keep) {
+            std::copy(history.begin(), history.end(), out_state.left);
+          }
+          // Now i is the length of the history coming from this constituent.  So it needs at least i+1 words to have a cross-child add.  
+          AddWord(history, i + 1, ngrams, out_state.counts);
+        }
+        // If the consituent is shorter than thetas_.size(), then the
+        // constituent's left is the entire constituent, so history is already
+        // correct.  Otherwise, the entire right hand side is the entire
+        // history.
+        if (long_constit) {
+          history.assign(thetas_.size(), rhs_state.right, rhs_state.right + keep);
+        }
+        ++ant_context;
+      } else {
+        // Word
+        ++*out_state.length;
+        history.push_back(*rhs);
+        if (++pushed == keep) {
+          std::copy(history.begin(), history.end(), out_state.left);
+        }
+        AddWord(history, 1, ngrams, out_state.counts);
+      }
+    }
+    // Fill in left and right constituents.
+    if (pushed < keep) {
+      std::copy(history.begin(), history.end(), out_state.left);
+      for (WordID *i = out_state.left + pushed; i != out_state.left + keep; ++i) {
+        *i = star_;
+      }
+      std::copy(out_state.left, out_state.left + keep, out_state.right);
+    } else if(pushed == keep) {
+      std::copy(history.begin(), history.end(), out_state.right);
+    } else if ((pushed > keep) && !history.empty()) {
+      std::copy(history.begin() + 1, history.end(), out_state.right);
+    }
+    std::vector<RefCounts>::const_iterator ref_info = ref_counts_[smeta.GetSentenceID()].begin();
+    // Clip the counts and count matches.
+    // Indexed by reference then by length.
+    std::vector<std::vector<unsigned int> > matches(num_refs_, std::vector<unsigned int>(thetas_.size()));
+    for (GramCount *c = out_state.counts; c != out_state.counts + ngrams.size(); ++c, ++ref_info) {
+      *c = std::min(*c, ref_info->max);
+      if (*c) {
+        for (unsigned int refidx = 0; refidx < num_refs_; ++refidx) {
+          assert(ref_info->length >= 1);
+          assert(ref_info->length - 1 < thetas_.size());
+          matches[refidx][ref_info->length - 1] += std::min(*c, ref_info->refs[refidx]);
+        }
+      }
+    }
+    double best_score = 0.0;
+    for (unsigned int refidx = 0; refidx < num_refs_; ++refidx) {
+      double score = 0.0;
+      for (unsigned int j = 0; j < std::min(*out_state.length, thetas_.size()); ++j) {
+        score += thetas_[j] * static_cast<double>(matches[refidx][j]) / static_cast<double>(*out_state.length - j);
+      }
+      best_score = std::max(best_score, score);
+    }
+    return best_score;
+  }
+
+ private:
+  unsigned int num_refs_;
+  // Indexed by sentence id.
+  std::vector<NGramMap> ref_ids_;
+  // Then by id from ref_ids_.
+  std::vector<std::vector<RefCounts> > ref_counts_;
+
+  // thetas_[0] is the weight for 1-grams
+  std::vector<double> thetas_;
+
+  // All ngram ids in ref_ids_ are < this value.
+  size_t bound_ngram_id_;
+
+  const WordID star_;
+};
+
+TrombleLossComputer::TrombleLossComputer(const std::string &params) :
+    boost::base_from_member<PImpl>(new TrombleLossComputerImpl(params)),
+    FeatureFunction(boost::base_from_member<PImpl>::member->StateSize()),
+    fid_(FD::Convert("TrombleLossComputer")) {}
+
+TrombleLossComputer::~TrombleLossComputer() {}
+
+void TrombleLossComputer::TraversalFeaturesImpl(const SentenceMetadata& smeta,
+                                     const Hypergraph::Edge& edge,
+                                     const vector<const void*>& ant_contexts,
+                                     SparseVector<double>* features,
+                                     SparseVector<double>* estimated_features,
+                                     void* out_context) const {
+  (void) estimated_features;
+  const double loss = boost::base_from_member<PImpl>::member->Traversal(smeta, *edge.rule_, ant_contexts, out_context);
+  features->set_value(fid_, loss);
+}