Merge branch 'master' of git://github.com/redpony/cdec

1 files changed, 17 insertions, 16 deletions

diff --git a/klm/lm/model.cc b/klm/lm/model.cc
index 2fd20481..a40fd2fb 100644
--- a/klm/lm/model.cc
+++ b/klm/lm/model.cc
@@ -37,7 +37,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
 template <class Search, class VocabularyT> GenericModel<Search, VocabularyT>::GenericModel(const char *file, const Config &config) {
   LoadLM(file, config, *this);
 
-  // g++ prints warnings unless these are fully initialized.  
+  // g++ prints warnings unless these are fully initialized.
   State begin_sentence = State();
   begin_sentence.length = 1;
   begin_sentence.words[0] = vocab_.BeginSentence();
@@ -69,8 +69,8 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
 }
 
 template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::InitializeFromARPA(const char *file, const Config &config) {
-  // Backing file is the ARPA.  Steal it so we can make the backing file the mmap output if any.  
-  util::FilePiece f(backing_.file.release(), file, config.messages);
+  // Backing file is the ARPA.  Steal it so we can make the backing file the mmap output if any.
+  util::FilePiece f(backing_.file.release(), file, config.ProgressMessages());
   try {
     std::vector<uint64_t> counts;
     // File counts do not include pruned trigrams that extend to quadgrams etc.   These will be fixed by search_.
@@ -80,14 +80,14 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
     if (config.probing_multiplier <= 1.0) UTIL_THROW(ConfigException, "probing multiplier must be > 1.0");
 
     std::size_t vocab_size = util::CheckOverflow(VocabularyT::Size(counts[0], config));
-    // Setup the binary file for writing the vocab lookup table.  The search_ is responsible for growing the binary file to its needs.  
+    // Setup the binary file for writing the vocab lookup table.  The search_ is responsible for growing the binary file to its needs.
     vocab_.SetupMemory(SetupJustVocab(config, counts.size(), vocab_size, backing_), vocab_size, counts[0], config);
 
     if (config.write_mmap) {
       WriteWordsWrapper wrap(config.enumerate_vocab);
       vocab_.ConfigureEnumerate(&wrap, counts[0]);
       search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_);
-      wrap.Write(backing_.file.get(), backing_.vocab.size() + vocab_.UnkCountChangePadding() + backing_.search.size());
+      wrap.Write(backing_.file.get(), backing_.vocab.size() + vocab_.UnkCountChangePadding() + Search::Size(counts, config));
     } else {
       vocab_.ConfigureEnumerate(config.enumerate_vocab, counts[0]);
       search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_);
@@ -95,7 +95,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
 
     if (!vocab_.SawUnk()) {
       assert(config.unknown_missing != THROW_UP);
-      // Default probabilities for unknown.  
+      // Default probabilities for unknown.
       search_.UnknownUnigram().backoff = 0.0;
       search_.UnknownUnigram().prob = config.unknown_missing_logprob;
     }
@@ -147,7 +147,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
 }
 
 template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::GetState(const WordIndex *context_rbegin, const WordIndex *context_rend, State &out_state) const {
-  // Generate a state from context.  
+  // Generate a state from context.
   context_rend = std::min(context_rend, context_rbegin + P::Order() - 1);
   if (context_rend == context_rbegin) {
     out_state.length = 0;
@@ -191,7 +191,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
     ret.rest = ptr.Rest();
     ret.prob = ptr.Prob();
     ret.extend_left = extend_pointer;
-    // If this function is called, then it does depend on left words.   
+    // If this function is called, then it does depend on left words.
     ret.independent_left = false;
   }
   float subtract_me = ret.rest;
@@ -199,7 +199,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
   next_use = extend_length;
   ResumeScore(add_rbegin, add_rend, extend_length - 1, node, backoff_out, next_use, ret);
   next_use -= extend_length;
-  // Charge backoffs.  
+  // Charge backoffs.
   for (const float *b = backoff_in + ret.ngram_length - extend_length; b < backoff_in + (add_rend - add_rbegin); ++b) ret.prob += *b;
   ret.prob -= subtract_me;
   ret.rest -= subtract_me;
@@ -209,7 +209,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
 namespace {
 // Do a paraonoid copy of history, assuming new_word has already been copied
 // (hence the -1).  out_state.length could be zero so I avoided using
-// std::copy.   
+// std::copy.
 void CopyRemainingHistory(const WordIndex *from, State &out_state) {
   WordIndex *out = out_state.words + 1;
   const WordIndex *in_end = from + static_cast<ptrdiff_t>(out_state.length) - 1;
@@ -217,18 +217,19 @@ void CopyRemainingHistory(const WordIndex *from, State &out_state) {
 }
 } // namespace
 
-/* Ugly optimized function.  Produce a score excluding backoff.  
- * The search goes in increasing order of ngram length.  
+/* Ugly optimized function.  Produce a score excluding backoff.
+ * The search goes in increasing order of ngram length.
  * Context goes backward, so context_begin is the word immediately preceeding
- * new_word.  
+ * new_word.
  */
 template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search, VocabularyT>::ScoreExceptBackoff(
     const WordIndex *const context_rbegin,
     const WordIndex *const context_rend,
     const WordIndex new_word,
     State &out_state) const {
+  assert(new_word < vocab_.Bound());
   FullScoreReturn ret;
-  // ret.ngram_length contains the last known non-blank ngram length.  
+  // ret.ngram_length contains the last known non-blank ngram length.
   ret.ngram_length = 1;
 
   typename Search::Node node;
@@ -237,9 +238,9 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
   ret.prob = uni.Prob();
   ret.rest = uni.Rest();
 
-  // This is the length of the context that should be used for continuation to the right.  
+  // This is the length of the context that should be used for continuation to the right.
   out_state.length = HasExtension(out_state.backoff[0]) ? 1 : 0;
-  // We'll write the word anyway since it will probably be used and does no harm being there.  
+  // We'll write the word anyway since it will probably be used and does no harm being there.
   out_state.words[0] = new_word;
   if (context_rbegin == context_rend) return ret;