From 44b023d165402406fc20bb5fa240cb9a9ebf32ea Mon Sep 17 00:00:00 2001
From: Kenneth Heafield <kenlm@kheafield.com>
Date: Sun, 26 Jun 2011 18:40:15 -0400
Subject: Quantization

---
 klm/lm/model.cc | 25 +++++++++++--------------
 1 file changed, 11 insertions(+), 14 deletions(-)

(limited to 'klm/lm/model.cc')

diff --git a/klm/lm/model.cc b/klm/lm/model.cc
index f0579c0c..a1d10b3d 100644
--- a/klm/lm/model.cc
+++ b/klm/lm/model.cc
@@ -44,17 +44,13 @@ template <class Search, class VocabularyT> GenericModel<Search, VocabularyT>::Ge
   begin_sentence.backoff_[0] = search_.unigram.Lookup(begin_sentence.history_[0]).backoff;
   State null_context = State();
   null_context.valid_length_ = 0;
-  P::Init(begin_sentence, null_context, vocab_, search_.middle.size() + 2);
+  P::Init(begin_sentence, null_context, vocab_, search_.MiddleEnd() - search_.MiddleBegin() + 2);
 }
 
 template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::InitializeFromBinary(void *start, const Parameters &params, const Config &config, int fd) {
   SetupMemory(start, params.counts, config);
   vocab_.LoadedBinary(fd, config.enumerate_vocab);
-  search_.unigram.LoadedBinary();
-  for (typename std::vector<Middle>::iterator i = search_.middle.begin(); i != search_.middle.end(); ++i) {
-    i->LoadedBinary();
-  }
-  search_.longest.LoadedBinary();
+  search_.LoadedBinary();
 }
 
 template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::InitializeFromARPA(const char *file, const Config &config) {
@@ -116,8 +112,9 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
   }
   float backoff;
   // i is the order of the backoff we're looking for.
-  for (const WordIndex *i = context_rbegin + start - 1; i < context_rend; ++i) {
-    if (!search_.LookupMiddleNoProb(search_.middle[i - context_rbegin - 1], *i, backoff, node)) break;
+  const Middle *mid_iter = search_.MiddleBegin() + start - 2;
+  for (const WordIndex *i = context_rbegin + start - 1; i < context_rend; ++i, ++mid_iter) {
+    if (!search_.LookupMiddleNoProb(*mid_iter, *i, backoff, node)) break;
     ret.prob += backoff;
   }
   return ret;
@@ -135,7 +132,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
   search_.LookupUnigram(*context_rbegin, ignored_prob, out_state.backoff_[0], node);
   out_state.valid_length_ = HasExtension(out_state.backoff_[0]) ? 1 : 0;
   float *backoff_out = out_state.backoff_ + 1;
-  const typename Search::Middle *mid = &*search_.middle.begin();
+  const typename Search::Middle *mid = search_.MiddleBegin();
   for (const WordIndex *i = context_rbegin + 1; i < context_rend; ++i, ++backoff_out, ++mid) {
     if (!search_.LookupMiddleNoProb(*mid, *i, *backoff_out, node)) {
       std::copy(context_rbegin, context_rbegin + out_state.valid_length_, out_state.history_);
@@ -183,7 +180,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
 
   // Ok now we now that the bigram contains known words.  Start by looking it up.
   const WordIndex *hist_iter = context_rbegin;
-  typename std::vector<Middle>::const_iterator mid_iter = search_.middle.begin();
+  const typename Search::Middle *mid_iter = search_.MiddleBegin();
   for (; ; ++mid_iter, ++hist_iter, ++backoff_out) {
     if (hist_iter == context_rend) {
       // Ran out of history.  Typically no backoff, but this could be a blank.  
@@ -192,7 +189,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
       return ret;
     }
 
-    if (mid_iter == search_.middle.end()) break;
+    if (mid_iter == search_.MiddleEnd()) break;
 
     float revert = ret.prob;
     if (!search_.LookupMiddle(*mid_iter, *hist_iter, ret.prob, *backoff_out, node)) {
@@ -227,9 +224,9 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
   return ret;
 }
 
-template class GenericModel<ProbingHashedSearch, ProbingVocabulary>;
-template class GenericModel<SortedHashedSearch, SortedVocabulary>;
-template class GenericModel<trie::TrieSearch, SortedVocabulary>;
+template class GenericModel<ProbingHashedSearch, ProbingVocabulary>;  // HASH_PROBING
+template class GenericModel<trie::TrieSearch<DontQuantize>, SortedVocabulary>; // TRIE_SORTED
+template class GenericModel<trie::TrieSearch<SeparatelyQuantize>, SortedVocabulary>; // TRIE_SORTED_QUANT
 
 } // namespace detail
 } // namespace ngram
-- 
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