Updated kenlm

6 files changed, 82 insertions, 78 deletions

diff --git a/klm/lm/binary_format.cc b/klm/lm/binary_format.cc
index efa67056..39c4a9b6 100644
--- a/klm/lm/binary_format.cc
+++ b/klm/lm/binary_format.cc
@@ -16,11 +16,11 @@ namespace ngram {
 namespace {
 const char kMagicBeforeVersion[] = "mmap lm http://kheafield.com/code format version";
 const char kMagicBytes[] = "mmap lm http://kheafield.com/code format version 5\n\0";
-// This must be shorter than kMagicBytes and indicates an incomplete binary file (i.e. build failed). 
+// This must be shorter than kMagicBytes and indicates an incomplete binary file (i.e. build failed).
 const char kMagicIncomplete[] = "mmap lm http://kheafield.com/code incomplete\n";
 const long int kMagicVersion = 5;
 
-// Old binary files built on 32-bit machines have this header.  
+// Old binary files built on 32-bit machines have this header.
 // TODO: eliminate with next binary release.
 struct OldSanity {
   char magic[sizeof(kMagicBytes)];
@@ -39,7 +39,7 @@ struct OldSanity {
 };
 
 
-// Test values aligned to 8 bytes.    
+// Test values aligned to 8 bytes.
 struct Sanity {
   char magic[ALIGN8(sizeof(kMagicBytes))];
   float zero_f, one_f, minus_half_f;
@@ -101,7 +101,7 @@ uint8_t *SetupJustVocab(const Config &config, uint8_t order, std::size_t memory_
 uint8_t *GrowForSearch(const Config &config, std::size_t vocab_pad, std::size_t memory_size, Backing &backing) {
   std::size_t adjusted_vocab = backing.vocab.size() + vocab_pad;
   if (config.write_mmap) {
-    // Grow the file to accomodate the search, using zeros.  
+    // Grow the file to accomodate the search, using zeros.
     try {
       util::ResizeOrThrow(backing.file.get(), adjusted_vocab + memory_size);
     } catch (util::ErrnoException &e) {
@@ -114,7 +114,7 @@ uint8_t *GrowForSearch(const Config &config, std::size_t vocab_pad, std::size_t
       return reinterpret_cast<uint8_t*>(backing.search.get());
     }
     // mmap it now.
-    // We're skipping over the header and vocab for the search space mmap.  mmap likes page aligned offsets, so some arithmetic to round the offset down.  
+    // We're skipping over the header and vocab for the search space mmap.  mmap likes page aligned offsets, so some arithmetic to round the offset down.
     std::size_t page_size = util::SizePage();
     std::size_t alignment_cruft = adjusted_vocab % page_size;
     backing.search.reset(util::MapOrThrow(alignment_cruft + memory_size, true, util::kFileFlags, false, backing.file.get(), adjusted_vocab - alignment_cruft), alignment_cruft + memory_size, util::scoped_memory::MMAP_ALLOCATED);
@@ -122,7 +122,7 @@ uint8_t *GrowForSearch(const Config &config, std::size_t vocab_pad, std::size_t
   } else {
     util::MapAnonymous(memory_size, backing.search);
     return reinterpret_cast<uint8_t*>(backing.search.get());
-  } 
+  }
 }
 
 void FinishFile(const Config &config, ModelType model_type, unsigned int search_version, const std::vector<uint64_t> &counts, std::size_t vocab_pad, Backing &backing) {
@@ -140,7 +140,7 @@ void FinishFile(const Config &config, ModelType model_type, unsigned int search_
       util::FSyncOrThrow(backing.file.get());
       break;
   }
-  // header and vocab share the same mmap.  The header is written here because we know the counts.  
+  // header and vocab share the same mmap.  The header is written here because we know the counts.
   Parameters params = Parameters();
   params.counts = counts;
   params.fixed.order = counts.size();
@@ -160,7 +160,7 @@ namespace detail {
 bool IsBinaryFormat(int fd) {
   const uint64_t size = util::SizeFile(fd);
   if (size == util::kBadSize || (size <= static_cast<uint64_t>(sizeof(Sanity)))) return false;
-  // Try reading the header.  
+  // Try reading the header.
   util::scoped_memory memory;
   try {
     util::MapRead(util::LAZY, fd, 0, sizeof(Sanity), memory);
@@ -214,7 +214,7 @@ void SeekPastHeader(int fd, const Parameters &params) {
 
 uint8_t *SetupBinary(const Config &config, const Parameters &params, uint64_t memory_size, Backing &backing) {
   const uint64_t file_size = util::SizeFile(backing.file.get());
-  // The header is smaller than a page, so we have to map the whole header as well.  
+  // The header is smaller than a page, so we have to map the whole header as well.
   std::size_t total_map = util::CheckOverflow(TotalHeaderSize(params.counts.size()) + memory_size);
   if (file_size != util::kBadSize && static_cast<uint64_t>(file_size) < total_map)
     UTIL_THROW(FormatLoadException, "Binary file has size " << file_size << " but the headers say it should be at least " << total_map);
@@ -233,7 +233,8 @@ void ComplainAboutARPA(const Config &config, ModelType model_type) {
   if (config.write_mmap || !config.messages) return;
   if (config.arpa_complain == Config::ALL) {
     *config.messages << "Loading the LM will be faster if you build a binary file." << std::endl;
-  } else if (config.arpa_complain == Config::EXPENSIVE && model_type == TRIE_SORTED) {
+  } else if (config.arpa_complain == Config::EXPENSIVE &&
+             (model_type == TRIE || model_type == QUANT_TRIE || model_type == ARRAY_TRIE || model_type == QUANT_ARRAY_TRIE)) {
     *config.messages << "Building " << kModelNames[model_type] << " from ARPA is expensive.  Save time by building a binary format." << std::endl;
   }
 }
diff --git a/klm/lm/config.cc b/klm/lm/config.cc
index f9d988ca..9520c41c 100644
--- a/klm/lm/config.cc
+++ b/klm/lm/config.cc
@@ -6,6 +6,7 @@ namespace lm {
 namespace ngram {
 
 Config::Config() :
+  show_progress(true),
   messages(&std::cerr),
   enumerate_vocab(NULL),
   unknown_missing(COMPLAIN),
diff --git a/klm/lm/config.hh b/klm/lm/config.hh
index 739cee9c..0de7b7c6 100644
--- a/klm/lm/config.hh
+++ b/klm/lm/config.hh
@@ -11,46 +11,52 @@
 /* Configuration for ngram model.  Separate header to reduce pollution. */
 
 namespace lm {
-  
+
 class EnumerateVocab;
 
 namespace ngram {
 
 struct Config {
-  // EFFECTIVE FOR BOTH ARPA AND BINARY READS 
+  // EFFECTIVE FOR BOTH ARPA AND BINARY READS
+
+  // (default true) print progress bar to messages
+  bool show_progress;
 
   // Where to log messages including the progress bar.  Set to NULL for
   // silence.
   std::ostream *messages;
 
+  std::ostream *ProgressMessages() const {
+    return show_progress ? messages : 0;
+  }
+
   // This will be called with every string in the vocabulary.  See
   // enumerate_vocab.hh for more detail.  Config does not take ownership; you
-  // are still responsible for deleting it (or stack allocating).  
+  // are still responsible for deleting it (or stack allocating).
   EnumerateVocab *enumerate_vocab;
 
 
-
   // ONLY EFFECTIVE WHEN READING ARPA
 
-  // What to do when <unk> isn't in the provided model. 
+  // What to do when <unk> isn't in the provided model.
   WarningAction unknown_missing;
-  // What to do when <s> or </s> is missing from the model. 
-  // If THROW_UP, the exception will be of type util::SpecialWordMissingException.  
+  // What to do when <s> or </s> is missing from the model.
+  // If THROW_UP, the exception will be of type util::SpecialWordMissingException.
   WarningAction sentence_marker_missing;
 
   // What to do with a positive log probability.  For COMPLAIN and SILENT, map
-  // to 0.  
+  // to 0.
   WarningAction positive_log_probability;
 
-  // The probability to substitute for <unk> if it's missing from the model.  
+  // The probability to substitute for <unk> if it's missing from the model.
   // No effect if the model has <unk> or unknown_missing == THROW_UP.
   float unknown_missing_logprob;
 
   // Size multiplier for probing hash table.  Must be > 1.  Space is linear in
   // this.  Time is probing_multiplier / (probing_multiplier - 1).  No effect
-  // for sorted variant.  
+  // for sorted variant.
   // If you find yourself setting this to a low number, consider using the
-  // TrieModel which has lower memory consumption.  
+  // TrieModel which has lower memory consumption.
   float probing_multiplier;
 
   // Amount of memory to use for building.  The actual memory usage will be
@@ -58,10 +64,10 @@ struct Config {
   // models.
   std::size_t building_memory;
 
-  // Template for temporary directory appropriate for passing to mkdtemp.  
+  // Template for temporary directory appropriate for passing to mkdtemp.
   // The characters XXXXXX are appended before passing to mkdtemp.  Only
   // applies to trie.  If NULL, defaults to write_mmap.  If that's NULL,
-  // defaults to input file name.  
+  // defaults to input file name.
   const char *temporary_directory_prefix;
 
   // Level of complaining to do when loading from ARPA instead of binary format.
@@ -69,49 +75,46 @@ struct Config {
   ARPALoadComplain arpa_complain;
 
   // While loading an ARPA file, also write out this binary format file.  Set
-  // to NULL to disable.  
+  // to NULL to disable.
   const char *write_mmap;
 
   enum WriteMethod {
-    WRITE_MMAP, // Map the file directly.  
-    WRITE_AFTER // Write after we're done.  
+    WRITE_MMAP, // Map the file directly.
+    WRITE_AFTER // Write after we're done.
   };
   WriteMethod write_method;
 
-  // Include the vocab in the binary file?  Only effective if write_mmap != NULL.  
+  // Include the vocab in the binary file?  Only effective if write_mmap != NULL.
   bool include_vocab;
 
 
-  // Left rest options.  Only used when the model includes rest costs.  
+  // Left rest options.  Only used when the model includes rest costs.
   enum RestFunction {
     REST_MAX,   // Maximum of any score to the left
-    REST_LOWER, // Use lower-order files given below.  
+    REST_LOWER, // Use lower-order files given below.
   };
   RestFunction rest_function;
-  // Only used for REST_LOWER.  
+  // Only used for REST_LOWER.
   std::vector<std::string> rest_lower_files;
 
 
-
   // Quantization options.  Only effective for QuantTrieModel.  One value is
   // reserved for each of prob and backoff, so 2^bits - 1 buckets will be used
-  // to quantize (and one of the remaining backoffs will be 0).  
+  // to quantize (and one of the remaining backoffs will be 0).
   uint8_t prob_bits, backoff_bits;
 
   // Bhiksha compression (simple form).  Only works with trie.
   uint8_t pointer_bhiksha_bits;
 
-  
-  
+
   // ONLY EFFECTIVE WHEN READING BINARY
-  
+
   // How to get the giant array into memory: lazy mmap, populate, read etc.
-  // See util/mmap.hh for details of MapMethod.  
+  // See util/mmap.hh for details of MapMethod.
   util::LoadMethod load_method;
 
 
-
-  // Set defaults. 
+  // Set defaults.
   Config();
 };
 
diff --git a/klm/lm/max_order.hh b/klm/lm/max_order.hh
index ea0dea46..3eb97ccd 100644
--- a/klm/lm/max_order.hh
+++ b/klm/lm/max_order.hh
@@ -7,5 +7,3 @@
 #ifndef KENLM_ORDER_MESSAGE
 #define KENLM_ORDER_MESSAGE "If your build system supports changing KENLM_MAX_ORDER, change it there and recompile.  In the KenLM tarball or Moses, use e.g. `bjam --max-kenlm-order=6 -a'.  Otherwise, edit lm/max_order.hh."
 #endif
-
-#define KENLM_MAX_ORDER 5
diff --git a/klm/lm/model.cc b/klm/lm/model.cc
index fc61efee..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_.
@@ -80,7 +80,7 @@ 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) {
@@ -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;
@@ -217,10 +217,10 @@ 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,
@@ -229,7 +229,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
     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;
@@ -238,9 +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;
 
diff --git a/klm/lm/search_trie.cc b/klm/lm/search_trie.cc
index debcfd07..1b0d9b26 100644
--- a/klm/lm/search_trie.cc
+++ b/klm/lm/search_trie.cc
@@ -55,7 +55,7 @@ struct ProbPointer {
   uint64_t index;
 };
 
-// Array of n-grams and float indices.  
+// Array of n-grams and float indices.
 class BackoffMessages {
   public:
     void Init(std::size_t entry_size) {
@@ -100,7 +100,7 @@ class BackoffMessages {
     void Apply(float *const *const base, RecordReader &reader) {
       FinishedAdding();
       if (current_ == allocated_) return;
-      // We'll also use the same buffer to record messages to blanks that they extend.  
+      // We'll also use the same buffer to record messages to blanks that they extend.
       WordIndex *extend_out = reinterpret_cast<WordIndex*>(current_);
       const unsigned char order = (entry_size_ - sizeof(ProbPointer)) / sizeof(WordIndex);
       for (reader.Rewind(); reader && (current_ != allocated_); ) {
@@ -109,7 +109,7 @@ class BackoffMessages {
             ++reader;
             break;
           case 1:
-            // Message but nobody to receive it.  Write it down at the beginning of the buffer so we can inform this blank that it extends.  
+            // Message but nobody to receive it.  Write it down at the beginning of the buffer so we can inform this blank that it extends.
             for (const WordIndex *w = reinterpret_cast<const WordIndex *>(current_); w != reinterpret_cast<const WordIndex *>(current_) + order; ++w, ++extend_out) *extend_out = *w;
             current_ += entry_size_;
             break;
@@ -126,7 +126,7 @@ class BackoffMessages {
             break;
         }
       }
-      // Now this is a list of blanks that extend right.  
+      // Now this is a list of blanks that extend right.
       entry_size_ = sizeof(WordIndex) * order;
       Resize(sizeof(WordIndex) * (extend_out - (const WordIndex*)backing_.get()));
       current_ = (uint8_t*)backing_.get();
@@ -153,7 +153,7 @@ class BackoffMessages {
   private:
     void FinishedAdding() {
       Resize(current_ - (uint8_t*)backing_.get());
-      // Sort requests in same order as files.  
+      // Sort requests in same order as files.
       std::sort(
           util::SizedIterator(util::SizedProxy(backing_.get(), entry_size_)),
           util::SizedIterator(util::SizedProxy(current_, entry_size_)),
@@ -220,7 +220,7 @@ class SRISucks {
     }
 
   private:
-    // This used to be one array.  Then I needed to separate it by order for quantization to work.  
+    // This used to be one array.  Then I needed to separate it by order for quantization to work.
     std::vector<float> values_[KENLM_MAX_ORDER - 1];
     BackoffMessages messages_[KENLM_MAX_ORDER - 1];
 
@@ -253,7 +253,7 @@ class FindBlanks {
       ++counts_.back();
     }
 
-    // Unigrams wrote one past.  
+    // Unigrams wrote one past.
     void Cleanup() {
       --counts_[0];
     }
@@ -270,15 +270,15 @@ class FindBlanks {
     SRISucks &sri_;
 };
 
-// Phase to actually write n-grams to the trie.  
+// Phase to actually write n-grams to the trie.
 template <class Quant, class Bhiksha> class WriteEntries {
   public:
-    WriteEntries(RecordReader *contexts, const Quant &quant, UnigramValue *unigrams, BitPackedMiddle<Bhiksha> *middle, BitPackedLongest &longest, unsigned char order, SRISucks &sri) : 
+    WriteEntries(RecordReader *contexts, const Quant &quant, UnigramValue *unigrams, BitPackedMiddle<Bhiksha> *middle, BitPackedLongest &longest, unsigned char order, SRISucks &sri) :
       contexts_(contexts),
       quant_(quant),
       unigrams_(unigrams),
       middle_(middle),
-      longest_(longest), 
+      longest_(longest),
       bigram_pack_((order == 2) ? static_cast<BitPacked&>(longest_) : static_cast<BitPacked&>(*middle_)),
       order_(order),
       sri_(sri) {}
@@ -328,7 +328,7 @@ struct Gram {
 
   const WordIndex *begin, *end;
 
-  // For queue, this is the direction we want.  
+  // For queue, this is the direction we want.
   bool operator<(const Gram &other) const {
     return std::lexicographical_compare(other.begin, other.end, begin, end);
   }
@@ -353,7 +353,7 @@ template <class Doing> class BlankManager {
         been_length_ = length;
         return;
       }
-      // There are blanks to insert starting with order blank.  
+      // There are blanks to insert starting with order blank.
       unsigned char blank = cur - to + 1;
       UTIL_THROW_IF(blank == 1, FormatLoadException, "Missing a unigram that appears as context.");
       const float *lower_basis;
@@ -363,7 +363,7 @@ template <class Doing> class BlankManager {
         assert(*lower_basis != kBadProb);
         doing_.MiddleBlank(blank, to, based_on, *lower_basis);
         *pre = *cur;
-        // Mark that the probability is a blank so it shouldn't be used as the basis for a later n-gram.  
+        // Mark that the probability is a blank so it shouldn't be used as the basis for a later n-gram.
         basis_[blank - 1] = kBadProb;
       }
       *pre = *cur;
@@ -377,7 +377,7 @@ template <class Doing> class BlankManager {
     unsigned char been_length_;
 
     float basis_[KENLM_MAX_ORDER];
-    
+
     Doing &doing_;
 };
 
@@ -451,7 +451,7 @@ template <class Quant> void TrainProbQuantizer(uint8_t order, uint64_t count, Re
 }
 
 void PopulateUnigramWeights(FILE *file, WordIndex unigram_count, RecordReader &contexts, UnigramValue *unigrams) {
-  // Fill unigram probabilities.  
+  // Fill unigram probabilities.
   try {
     rewind(file);
     for (WordIndex i = 0; i < unigram_count; ++i) {
@@ -486,7 +486,7 @@ template <class Quant, class Bhiksha> void BuildTrie(SortedFiles &files, std::ve
     util::scoped_memory unigrams;
     MapRead(util::POPULATE_OR_READ, unigram_fd.get(), 0, counts[0] * sizeof(ProbBackoff), unigrams);
     FindBlanks finder(counts.size(), reinterpret_cast<const ProbBackoff*>(unigrams.get()), sri);
-    RecursiveInsert(counts.size(), counts[0], inputs, config.messages, "Identifying n-grams omitted by SRI", finder);
+    RecursiveInsert(counts.size(), counts[0], inputs, config.ProgressMessages(), "Identifying n-grams omitted by SRI", finder);
     fixed_counts = finder.Counts();
   }
   unigram_file.reset(util::FDOpenOrThrow(unigram_fd));
@@ -504,7 +504,8 @@ template <class Quant, class Bhiksha> void BuildTrie(SortedFiles &files, std::ve
     inputs[i-2].Rewind();
   }
   if (Quant::kTrain) {
-    util::ErsatzProgress progress(std::accumulate(counts.begin() + 1, counts.end(), 0), config.messages, "Quantizing");
+    util::ErsatzProgress progress(std::accumulate(counts.begin() + 1, counts.end(), 0),
+                                  config.ProgressMessages(), "Quantizing");
     for (unsigned char i = 2; i < counts.size(); ++i) {
       TrainQuantizer(i, counts[i-1], sri.Values(i), inputs[i-2], progress, quant);
     }
@@ -519,13 +520,13 @@ template <class Quant, class Bhiksha> void BuildTrie(SortedFiles &files, std::ve
   for (unsigned char i = 2; i <= counts.size(); ++i) {
     inputs[i-2].Rewind();
   }
-  // Fill entries except unigram probabilities.  
+  // Fill entries except unigram probabilities.
   {
     WriteEntries<Quant, Bhiksha> writer(contexts, quant, unigrams, out.middle_begin_, out.longest_, counts.size(), sri);
-    RecursiveInsert(counts.size(), counts[0], inputs, config.messages, "Writing trie", writer);
+    RecursiveInsert(counts.size(), counts[0], inputs, config.ProgressMessages(), "Writing trie", writer);
   }
 
-  // Do not disable this error message or else too little state will be returned.  Both WriteEntries::Middle and returning state based on found n-grams will need to be fixed to handle this situation.   
+  // Do not disable this error message or else too little state will be returned.  Both WriteEntries::Middle and returning state based on found n-grams will need to be fixed to handle this situation.
   for (unsigned char order = 2; order <= counts.size(); ++order) {
     const RecordReader &context = contexts[order - 2];
     if (context) {
@@ -541,13 +542,13 @@ template <class Quant, class Bhiksha> void BuildTrie(SortedFiles &files, std::ve
   }
 
   /* Set ending offsets so the last entry will be sized properly */
-  // Last entry for unigrams was already set.  
+  // Last entry for unigrams was already set.
   if (out.middle_begin_ != out.middle_end_) {
     for (typename TrieSearch<Quant, Bhiksha>::Middle *i = out.middle_begin_; i != out.middle_end_ - 1; ++i) {
       i->FinishedLoading((i+1)->InsertIndex(), config);
     }
     (out.middle_end_ - 1)->FinishedLoading(out.longest_.InsertIndex(), config);
-  }  
+  }
 }
 
 template <class Quant, class Bhiksha> uint8_t *TrieSearch<Quant, Bhiksha>::SetupMemory(uint8_t *start, const std::vector<uint64_t> &counts, const Config &config) {
@@ -595,7 +596,7 @@ template <class Quant, class Bhiksha> void TrieSearch<Quant, Bhiksha>::Initializ
   } else {
     temporary_prefix = file;
   }
-  // At least 1MB sorting memory.  
+  // At least 1MB sorting memory.
   SortedFiles sorted(config, f, counts, std::max<size_t>(config.building_memory, 1048576), temporary_prefix, vocab);
 
   BuildTrie(sorted, counts, config, *this, quant_, vocab, backing);