format C++ source code

deep_speech_2/deploy/ctc_decoders.h

 #ifndef CTC_BEAM_SEARCH_DECODER_H_
 #define CTC_BEAM_SEARCH_DECODER_H_
 
-#include <vector>
 #include <string>
 #include <utility>
+#include <vector>
 #include "scorer.h"
 
 /* CTC Best Path Decoder
@@ -16,8 +16,8 @@
  *     A vector that each element is a pair of score  and decoding result,
  *     in desending order.
  */
-std::string ctc_best_path_decoder(std::vector<std::vector<double> > probs_seq,
-                                     std::vector<std::string> vocabulary);
+std::string ctc_best_path_decoder(std::vector<std::vector<double>> probs_seq,
+                                  std::vector<std::string> vocabulary);
 
 /* CTC Beam Search Decoder
 
@@ -34,15 +34,14 @@ std::string ctc_best_path_decoder(std::vector<std::vector<double> > probs_seq,
  *     A vector that each element is a pair of score  and decoding result,
  *     in desending order.
 */
-std::vector<std::pair<double, std::string> >
-    ctc_beam_search_decoder(std::vector<std::vector<double> > probs_seq,
-                            int beam_size,
-                            std::vector<std::string> vocabulary,
-                            int blank_id,
-                            double cutoff_prob=1.0,
-                            int cutoff_top_n=40,
-                            Scorer *ext_scorer=NULL
-                            );
+std::vector<std::pair<double, std::string>> ctc_beam_search_decoder(
+    std::vector<std::vector<double>> probs_seq,
+    int beam_size,
+    std::vector<std::string> vocabulary,
+    int blank_id,
+    double cutoff_prob = 1.0,
+    int cutoff_top_n = 40,
+    Scorer *ext_scorer = NULL);
 
 /* CTC Beam Search Decoder for batch data, the interface is consistent with the
  * original decoder in Python version.
@@ -63,15 +62,14 @@ std::vector<std::pair<double, std::string> >
  *     sample.
 */
 std::vector<std::vector<std::pair<double, std::string>>>
-    ctc_beam_search_decoder_batch(std::vector<std::vector<std::vector<double>>> probs_split,
-                            int beam_size,
-                            std::vector<std::string> vocabulary,
-                            int blank_id,
-                            int num_processes,
-                            double cutoff_prob=1.0,
-                            int cutoff_top_n=40,
-                            Scorer *ext_scorer=NULL
-                            );
-
+ctc_beam_search_decoder_batch(
+    std::vector<std::vector<std::vector<double>>> probs_split,
+    int beam_size,
+    std::vector<std::string> vocabulary,
+    int blank_id,
+    int num_processes,
+    double cutoff_prob = 1.0,
+    int cutoff_top_n = 40,
+    Scorer *ext_scorer = NULL);
 
-#endif // CTC_BEAM_SEARCH_DECODER_H_
+#endif  // CTC_BEAM_SEARCH_DECODER_H_

deep_speech_2/deploy/decoder_utils.cpp

-#include <limits>
+#include "decoder_utils.h"
 #include <algorithm>
 #include <cmath>
-#include "decoder_utils.h"
+#include <limits>
 
 size_t get_utf8_str_len(const std::string& str) {
-    size_t str_len = 0;
-    for (char c : str) {
-        str_len += ((c & 0xc0) != 0x80);
-    }
-    return str_len;
+  size_t str_len = 0;
+  for (char c : str) {
+    str_len += ((c & 0xc0) != 0x80);
+  }
+  return str_len;
 }
 
-std::vector<std::string> split_utf8_str(const std::string& str)
-{
+std::vector<std::string> split_utf8_str(const std::string& str) {
   std::vector<std::string> result;
   std::string out_str;
 
-  for (char c : str)
+  for (char c : str) {
+    if ((c & 0xc0) != 0x80)  // new UTF-8 character
     {
-      if ((c & 0xc0) != 0x80)  //new UTF-8 character
-        {
-          if (!out_str.empty())
-            {
-              result.push_back(out_str);
-              out_str.clear();
-            }
-        }
-
-      out_str.append(1, c);
+      if (!out_str.empty()) {
+        result.push_back(out_str);
+        out_str.clear();
+      }
     }
+
+    out_str.append(1, c);
+  }
   result.push_back(out_str);
   return result;
 }
 
-std::vector<std::string> split_str(const std::string &s,
-                                   const std::string &delim) {
-    std::vector<std::string> result;
-    std::size_t start = 0, delim_len = delim.size();
-    while (true) {
-        std::size_t end = s.find(delim, start);
-        if (end == std::string::npos) {
-            if (start < s.size()) {
-                result.push_back(s.substr(start));
-            }
-            break;
-        }
-        if (end > start) {
-            result.push_back(s.substr(start, end - start));
-        }
-        start = end + delim_len;
+std::vector<std::string> split_str(const std::string& s,
+                                   const std::string& delim) {
+  std::vector<std::string> result;
+  std::size_t start = 0, delim_len = delim.size();
+  while (true) {
+    std::size_t end = s.find(delim, start);
+    if (end == std::string::npos) {
+      if (start < s.size()) {
+        result.push_back(s.substr(start));
+      }
+      break;
+    }
+    if (end > start) {
+      result.push_back(s.substr(start, end - start));
     }
-    return result;
+    start = end + delim_len;
+  }
+  return result;
 }
 
-bool prefix_compare(const PathTrie* x,  const PathTrie* y) {
-    if (x->_score == y->_score) {
-        if (x->_character == y->_character) {
-            return false;
-        } else {
-            return (x->_character < y->_character);
-        }
+bool prefix_compare(const PathTrie* x, const PathTrie* y) {
+  if (x->score == y->score) {
+    if (x->character == y->character) {
+      return false;
     } else {
-        return x->_score > y->_score;
+      return (x->character < y->character);
     }
+  } else {
+    return x->score > y->score;
+  }
 }
 
 void add_word_to_fst(const std::vector<int>& word,
                      fst::StdVectorFst* dictionary) {
-    if (dictionary->NumStates() == 0) {
-        fst::StdVectorFst::StateId start = dictionary->AddState();
-        assert(start == 0);
-        dictionary->SetStart(start);
-    }
-    fst::StdVectorFst::StateId src = dictionary->Start();
-    fst::StdVectorFst::StateId dst;
-    for (auto c : word) {
-        dst = dictionary->AddState();
-        dictionary->AddArc(src, fst::StdArc(c, c, 0, dst));
-        src = dst;
-    }
-    dictionary->SetFinal(dst, fst::StdArc::Weight::One());
+  if (dictionary->NumStates() == 0) {
+    fst::StdVectorFst::StateId start = dictionary->AddState();
+    assert(start == 0);
+    dictionary->SetStart(start);
+  }
+  fst::StdVectorFst::StateId src = dictionary->Start();
+  fst::StdVectorFst::StateId dst;
+  for (auto c : word) {
+    dst = dictionary->AddState();
+    dictionary->AddArc(src, fst::StdArc(c, c, 0, dst));
+    src = dst;
+  }
+  dictionary->SetFinal(dst, fst::StdArc::Weight::One());
 }
 
-bool add_word_to_dictionary(const std::string& word,
-                         const std::unordered_map<std::string, int>& char_map,
-                         bool add_space,
-                         int SPACE_ID,
-                         fst::StdVectorFst* dictionary) {
-    auto characters = split_utf8_str(word);
+bool add_word_to_dictionary(
+    const std::string& word,
+    const std::unordered_map<std::string, int>& char_map,
+    bool add_space,
+    int SPACE_ID,
+    fst::StdVectorFst* dictionary) {
+  auto characters = split_utf8_str(word);
 
-    std::vector<int> int_word;
+  std::vector<int> int_word;
 
-    for (auto& c : characters) {
-        if (c == " ") {
-            int_word.push_back(SPACE_ID);
-        } else {
-            auto int_c = char_map.find(c);
-            if (int_c != char_map.end()) {
-                int_word.push_back(int_c->second);
-            } else {
-                return false;  // return without adding
-            }
-        }
+  for (auto& c : characters) {
+    if (c == " ") {
+      int_word.push_back(SPACE_ID);
+    } else {
+      auto int_c = char_map.find(c);
+      if (int_c != char_map.end()) {
+        int_word.push_back(int_c->second);
+      } else {
+        return false;  // return without adding
+      }
     }
+  }
 
-    if (add_space) {
-        int_word.push_back(SPACE_ID);
-    }
+  if (add_space) {
+    int_word.push_back(SPACE_ID);
+  }
 
-    add_word_to_fst(int_word, dictionary);
-    return true;
+  add_word_to_fst(int_word, dictionary);
+  return true;
 }

deep_speech_2/deploy/decoder_utils.h

@@ -10,34 +10,31 @@ const float NUM_FLT_MIN = std::numeric_limits<float>::min();
 // Function template for comparing two pairs
 template <typename T1, typename T2>
 bool pair_comp_first_rev(const std::pair<T1, T2> &a,
-                         const std::pair<T1, T2> &b)
-{
-    return a.first > b.first;
+                         const std::pair<T1, T2> &b) {
+  return a.first > b.first;
 }
 
 template <typename T1, typename T2>
 bool pair_comp_second_rev(const std::pair<T1, T2> &a,
-                          const std::pair<T1, T2> &b)
-{
-    return a.second > b.second;
+                          const std::pair<T1, T2> &b) {
+  return a.second > b.second;
 }
 
 template <typename T>
-T log_sum_exp(const T &x, const T &y)
-{
-    static T num_min = -std::numeric_limits<T>::max();
-    if (x <= num_min) return y;
-    if (y <= num_min) return x;
-    T xmax = std::max(x, y);
-    return std::log(std::exp(x-xmax) + std::exp(y-xmax)) + xmax;
+T log_sum_exp(const T &x, const T &y) {
+  static T num_min = -std::numeric_limits<T>::max();
+  if (x <= num_min) return y;
+  if (y <= num_min) return x;
+  T xmax = std::max(x, y);
+  return std::log(std::exp(x - xmax) + std::exp(y - xmax)) + xmax;
 }
 
 // Functor for prefix comparsion
-bool prefix_compare(const PathTrie* x,  const PathTrie* y);
+bool prefix_compare(const PathTrie *x, const PathTrie *y);
 
 // Get length of utf8 encoding string
 // See: http://stackoverflow.com/a/4063229
-size_t get_utf8_str_len(const std::string& str);
+size_t get_utf8_str_len(const std::string &str);
 
 // Split a string into a list of strings on a given string
 // delimiter. NB: delimiters on beginning / end of string are
@@ -50,13 +47,14 @@ std::vector<std::string> split_str(const std::string &s,
 std::vector<std::string> split_utf8_str(const std::string &str);
 
 // Add a word in index to the dicionary of fst
-void add_word_to_fst(const std::vector<int>& word,
-                     fst::StdVectorFst* dictionary);
+void add_word_to_fst(const std::vector<int> &word,
+                     fst::StdVectorFst *dictionary);
 
 // Add a word in string to dictionary
-bool add_word_to_dictionary(const std::string& word,
-                         const std::unordered_map<std::string, int>& char_map,
-                         bool add_space,
-                         int SPACE_ID,
-                         fst::StdVectorFst* dictionary);
-#endif // DECODER_UTILS_H
+bool add_word_to_dictionary(
+    const std::string &word,
+    const std::unordered_map<std::string, int> &char_map,
+    bool add_space,
+    int SPACE_ID,
+    fst::StdVectorFst *dictionary);
+#endif  // DECODER_UTILS_H

deep_speech_2/deploy/path_trie.cpp

@@ -4,145 +4,142 @@
 #include <utility>
 #include <vector>
 
-#include "path_trie.h"
 #include "decoder_utils.h"
+#include "path_trie.h"
 
 PathTrie::PathTrie() {
-    _log_prob_b_prev = -NUM_FLT_INF;
-    _log_prob_nb_prev = -NUM_FLT_INF;
-    _log_prob_b_cur = -NUM_FLT_INF;
-    _log_prob_nb_cur = -NUM_FLT_INF;
-    _score = -NUM_FLT_INF;
-
-    _ROOT = -1;
-    _character = _ROOT;
-    _exists = true;
-    _parent = nullptr;
-    _dictionary = nullptr;
-    _dictionary_state = 0;
-    _has_dictionary = false;
-    _matcher = nullptr;  // finds arcs in FST
+  log_prob_b_prev = -NUM_FLT_INF;
+  log_prob_nb_prev = -NUM_FLT_INF;
+  log_prob_b_cur = -NUM_FLT_INF;
+  log_prob_nb_cur = -NUM_FLT_INF;
+  score = -NUM_FLT_INF;
+
+  _ROOT = -1;
+  character = _ROOT;
+  _exists = true;
+  parent = nullptr;
+  _dictionary = nullptr;
+  _dictionary_state = 0;
+  _has_dictionary = false;
+  _matcher = nullptr;  // finds arcs in FST
 }
 
 PathTrie::~PathTrie() {
-    for (auto child : _children) {
-        delete child.second;
-    }
+  for (auto child : _children) {
+    delete child.second;
+  }
 }
 
 PathTrie* PathTrie::get_path_trie(int new_char, bool reset) {
-    auto child = _children.begin();
-    for (child = _children.begin(); child != _children.end(); ++child) {
-        if (child->first == new_char) {
-            break;
-        }
+  auto child = _children.begin();
+  for (child = _children.begin(); child != _children.end(); ++child) {
+    if (child->first == new_char) {
+      break;
     }
-    if ( child != _children.end() ) {
-        if (!child->second->_exists) {
-            child->second->_exists = true;
-            child->second->_log_prob_b_prev = -NUM_FLT_INF;
-            child->second->_log_prob_nb_prev = -NUM_FLT_INF;
-            child->second->_log_prob_b_cur = -NUM_FLT_INF;
-            child->second->_log_prob_nb_cur = -NUM_FLT_INF;
+  }
+  if (child != _children.end()) {
+    if (!child->second->_exists) {
+      child->second->_exists = true;
+      child->second->log_prob_b_prev = -NUM_FLT_INF;
+      child->second->log_prob_nb_prev = -NUM_FLT_INF;
+      child->second->log_prob_b_cur = -NUM_FLT_INF;
+      child->second->log_prob_nb_cur = -NUM_FLT_INF;
+    }
+    return (child->second);
+  } else {
+    if (_has_dictionary) {
+      _matcher->SetState(_dictionary_state);
+      bool found = _matcher->Find(new_char);
+      if (!found) {
+        // Adding this character causes word outside dictionary
+        auto FSTZERO = fst::TropicalWeight::Zero();
+        auto final_weight = _dictionary->Final(_dictionary_state);
+        bool is_final = (final_weight != FSTZERO);
+        if (is_final && reset) {
+          _dictionary_state = _dictionary->Start();
         }
-        return (child->second);
+        return nullptr;
+      } else {
+        PathTrie* new_path = new PathTrie;
+        new_path->character = new_char;
+        new_path->parent = this;
+        new_path->_dictionary = _dictionary;
+        new_path->_dictionary_state = _matcher->Value().nextstate;
+        new_path->_has_dictionary = true;
+        new_path->_matcher = _matcher;
+        _children.push_back(std::make_pair(new_char, new_path));
+        return new_path;
+      }
     } else {
-        if (_has_dictionary) {
-            _matcher->SetState(_dictionary_state);
-            bool found = _matcher->Find(new_char);
-            if (!found) {
-                // Adding this character causes word outside dictionary
-                auto FSTZERO = fst::TropicalWeight::Zero();
-                auto final_weight = _dictionary->Final(_dictionary_state);
-                bool is_final = (final_weight != FSTZERO);
-                if (is_final && reset) {
-                    _dictionary_state = _dictionary->Start();
-                }
-                return nullptr;
-            } else {
-                PathTrie* new_path = new PathTrie;
-                new_path->_character = new_char;
-                new_path->_parent = this;
-                new_path->_dictionary = _dictionary;
-                new_path->_dictionary_state = _matcher->Value().nextstate;
-                new_path->_has_dictionary = true;
-                new_path->_matcher = _matcher;
-                _children.push_back(std::make_pair(new_char, new_path));
-                return new_path;
-            }
-        } else {
-            PathTrie* new_path = new PathTrie;
-            new_path->_character = new_char;
-            new_path->_parent = this;
-            _children.push_back(std::make_pair(new_char, new_path));
-            return new_path;
-        }
+      PathTrie* new_path = new PathTrie;
+      new_path->character = new_char;
+      new_path->parent = this;
+      _children.push_back(std::make_pair(new_char, new_path));
+      return new_path;
     }
+  }
 }
 
 PathTrie* PathTrie::get_path_vec(std::vector<int>& output) {
-    return get_path_vec(output, _ROOT);
+  return get_path_vec(output, _ROOT);
 }
 
 PathTrie* PathTrie::get_path_vec(std::vector<int>& output,
-        int stop,
-        size_t max_steps) {
-    if (_character == stop ||
-            _character == _ROOT ||
-            output.size() == max_steps) {
-        std::reverse(output.begin(), output.end());
-        return this;
-    } else {
-        output.push_back(_character);
-        return _parent->get_path_vec(output, stop, max_steps);
-    }
+                                 int stop,
+                                 size_t max_steps) {
+  if (character == stop || character == _ROOT || output.size() == max_steps) {
+    std::reverse(output.begin(), output.end());
+    return this;
+  } else {
+    output.push_back(character);
+    return parent->get_path_vec(output, stop, max_steps);
+  }
 }
 
-void PathTrie::iterate_to_vec(
-        std::vector<PathTrie*>& output) {
-    if (_exists) {
-        _log_prob_b_prev = _log_prob_b_cur;
-        _log_prob_nb_prev = _log_prob_nb_cur;
+void PathTrie::iterate_to_vec(std::vector<PathTrie*>& output) {
+  if (_exists) {
+    log_prob_b_prev = log_prob_b_cur;
+    log_prob_nb_prev = log_prob_nb_cur;
 
-        _log_prob_b_cur = -NUM_FLT_INF;
-        _log_prob_nb_cur = -NUM_FLT_INF;
+    log_prob_b_cur = -NUM_FLT_INF;
+    log_prob_nb_cur = -NUM_FLT_INF;
 
-        _score = log_sum_exp(_log_prob_b_prev, _log_prob_nb_prev);
-        output.push_back(this);
-    }
-    for (auto child : _children) {
-        child.second->iterate_to_vec(output);
-    }
+    score = log_sum_exp(log_prob_b_prev, log_prob_nb_prev);
+    output.push_back(this);
+  }
+  for (auto child : _children) {
+    child.second->iterate_to_vec(output);
+  }
 }
 
 void PathTrie::remove() {
-    _exists = false;
-
-    if (_children.size() == 0) {
-        auto child = _parent->_children.begin();
-        for (child = _parent->_children.begin();
-                child != _parent->_children.end(); ++child) {
-            if (child->first == _character) {
-                _parent->_children.erase(child);
-                break;
-            }
-        }
-
-        if ( _parent->_children.size() == 0 && !_parent->_exists ) {
-            _parent->remove();
-        }
+  _exists = false;
+
+  if (_children.size() == 0) {
+    auto child = parent->_children.begin();
+    for (child = parent->_children.begin(); child != parent->_children.end();
+         ++child) {
+      if (child->first == character) {
+        parent->_children.erase(child);
+        break;
+      }
+    }
 
-        delete this;
+    if (parent->_children.size() == 0 && !parent->_exists) {
+      parent->remove();
     }
+
+    delete this;
+  }
 }
 
 void PathTrie::set_dictionary(fst::StdVectorFst* dictionary) {
-    _dictionary = dictionary;
-    _dictionary_state = dictionary->Start();
-    _has_dictionary = true;
+  _dictionary = dictionary;
+  _dictionary_state = dictionary->Start();
+  _has_dictionary = true;
 }
 
 using FSTMATCH = fst::SortedMatcher<fst::StdVectorFst>;
 void PathTrie::set_matcher(std::shared_ptr<FSTMATCH> matcher) {
-    _matcher = matcher;
+  _matcher = matcher;
 }

deep_speech_2/deploy/path_trie.h

 #ifndef PATH_TRIE_H
 #define PATH_TRIE_H
 #pragma once
+#include <fst/fstlib.h>
 #include <algorithm>
 #include <limits>
 #include <memory>
 #include <utility>
 #include <vector>
-#include <fst/fstlib.h>
 
 using FSTMATCH = fst::SortedMatcher<fst::StdVectorFst>;
 
 class PathTrie {
 public:
-    PathTrie();
-    ~PathTrie();
-
-    PathTrie* get_path_trie(int new_char, bool reset = true);
+  PathTrie();
+  ~PathTrie();
 
-    PathTrie* get_path_vec(std::vector<int> &output);
+  PathTrie* get_path_trie(int new_char, bool reset = true);
 
-    PathTrie* get_path_vec(std::vector<int>& output,
-                        int stop,
-                        size_t max_steps = std::numeric_limits<size_t>::max());
+  PathTrie* get_path_vec(std::vector<int>& output);
 
-    void iterate_to_vec(std::vector<PathTrie*> &output);
+  PathTrie* get_path_vec(std::vector<int>& output,
+                         int stop,
+                         size_t max_steps = std::numeric_limits<size_t>::max());
 
-    void set_dictionary(fst::StdVectorFst* dictionary);
+  void iterate_to_vec(std::vector<PathTrie*>& output);
 
-    void set_matcher(std::shared_ptr<FSTMATCH> matcher);
+  void set_dictionary(fst::StdVectorFst* dictionary);
 
-    bool is_empty() {
-        return _ROOT == _character;
-    }
+  void set_matcher(std::shared_ptr<FSTMATCH> matcher);
 
-    void remove();
+  bool is_empty() { return _ROOT == character; }
 
-    float _log_prob_b_prev;
-    float _log_prob_nb_prev;
-    float _log_prob_b_cur;
-    float _log_prob_nb_cur;
-    float _score;
-    float _approx_ctc;
+  void remove();
 
+  float log_prob_b_prev;
+  float log_prob_nb_prev;
+  float log_prob_b_cur;
+  float log_prob_nb_cur;
+  float score;
+  float approx_ctc;
+  int character;
+  PathTrie* parent;
 
-    int  _ROOT;
-    int  _character;
-    bool _exists;
+private:
+  int _ROOT;
+  bool _exists;
 
-    PathTrie *_parent;
-    std::vector<std::pair<int, PathTrie*> > _children;
+  std::vector<std::pair<int, PathTrie*>> _children;
 
-    fst::StdVectorFst* _dictionary;
-    fst::StdVectorFst::StateId _dictionary_state;
-    bool _has_dictionary;
-    std::shared_ptr<FSTMATCH> _matcher;
+  fst::StdVectorFst* _dictionary;
+  fst::StdVectorFst::StateId _dictionary_state;
+  bool _has_dictionary;
+  std::shared_ptr<FSTMATCH> _matcher;
 };
 
-#endif // PATH_TRIE_H
+#endif  // PATH_TRIE_H

deep_speech_2/deploy/scorer.cpp

-#include <iostream>
+#include "scorer.h"
 #include <unistd.h>
+#include <iostream>
+#include "decoder_utils.h"
 #include "lm/config.hh"
-#include "lm/state.hh"
 #include "lm/model.hh"
-#include "util/tokenize_piece.hh"
+#include "lm/state.hh"
 #include "util/string_piece.hh"
-#include "scorer.h"
-#include "decoder_utils.h"
+#include "util/tokenize_piece.hh"
 
 using namespace lm::ngram;
 
 Scorer::Scorer(double alpha, double beta, const std::string& lm_path) {
-    this->alpha = alpha;
-    this->beta = beta;
-    _is_character_based = true;
-    _language_model = nullptr;
-    dictionary = nullptr;
-    _max_order = 0;
-    _SPACE_ID = -1;
-    // load language model
-    load_LM(lm_path.c_str());
+  this->alpha = alpha;
+  this->beta = beta;
+  _is_character_based = true;
+  _language_model = nullptr;
+  dictionary = nullptr;
+  _max_order = 0;
+  _SPACE_ID = -1;
+  // load language model
+  load_LM(lm_path.c_str());
 }
 
 Scorer::~Scorer() {
-    if (_language_model != nullptr)
-        delete static_cast<lm::base::Model*>(_language_model);
-    if (dictionary != nullptr)
-        delete static_cast<fst::StdVectorFst*>(dictionary);
+  if (_language_model != nullptr)
+    delete static_cast<lm::base::Model*>(_language_model);
+  if (dictionary != nullptr) delete static_cast<fst::StdVectorFst*>(dictionary);
 }
 
 void Scorer::load_LM(const char* filename) {
-    if (access(filename, F_OK) != 0) {
-        std::cerr << "Invalid language model file !!!" << std::endl;
-        exit(1);
-    }
-    RetriveStrEnumerateVocab enumerate;
-    lm::ngram::Config config;
-    config.enumerate_vocab = &enumerate;
-    _language_model = lm::ngram::LoadVirtual(filename, config);
-    _max_order = static_cast<lm::base::Model*>(_language_model)->Order();
-    _vocabulary = enumerate.vocabulary;
-    for (size_t i = 0; i < _vocabulary.size(); ++i) {
-        if (_is_character_based
-            && _vocabulary[i] != UNK_TOKEN
-            && _vocabulary[i] != START_TOKEN
-            && _vocabulary[i] != END_TOKEN
-            && get_utf8_str_len(enumerate.vocabulary[i]) > 1) {
-                _is_character_based = false;
-        }
+  if (access(filename, F_OK) != 0) {
+    std::cerr << "Invalid language model file !!!" << std::endl;
+    exit(1);
+  }
+  RetriveStrEnumerateVocab enumerate;
+  lm::ngram::Config config;
+  config.enumerate_vocab = &enumerate;
+  _language_model = lm::ngram::LoadVirtual(filename, config);
+  _max_order = static_cast<lm::base::Model*>(_language_model)->Order();
+  _vocabulary = enumerate.vocabulary;
+  for (size_t i = 0; i < _vocabulary.size(); ++i) {
+    if (_is_character_based && _vocabulary[i] != UNK_TOKEN &&
+        _vocabulary[i] != START_TOKEN && _vocabulary[i] != END_TOKEN &&
+        get_utf8_str_len(enumerate.vocabulary[i]) > 1) {
+      _is_character_based = false;
     }
+  }
 }
 
 double Scorer::get_log_cond_prob(const std::vector<std::string>& words) {
-    lm::base::Model* model = static_cast<lm::base::Model*>(_language_model);
-    double cond_prob;
-    lm::ngram::State state, tmp_state, out_state;
-    // avoid to inserting <s> in begin
-    model->NullContextWrite(&state);
-    for (size_t i = 0; i < words.size(); ++i) {
-        lm::WordIndex word_index = model->BaseVocabulary().Index(words[i]);
-        // encounter OOV
-        if (word_index == 0) {
-            return OOV_SCORE;
-        }
-        cond_prob = model->BaseScore(&state, word_index, &out_state);
-        tmp_state = state;
-        state = out_state;
-        out_state = tmp_state;
+  lm::base::Model* model = static_cast<lm::base::Model*>(_language_model);
+  double cond_prob;
+  lm::ngram::State state, tmp_state, out_state;
+  // avoid to inserting <s> in begin
+  model->NullContextWrite(&state);
+  for (size_t i = 0; i < words.size(); ++i) {
+    lm::WordIndex word_index = model->BaseVocabulary().Index(words[i]);
+    // encounter OOV
+    if (word_index == 0) {
+      return OOV_SCORE;
     }
-    // log10 prob
-    return cond_prob;
+    cond_prob = model->BaseScore(&state, word_index, &out_state);
+    tmp_state = state;
+    state = out_state;
+    out_state = tmp_state;
+  }
+  // log10 prob
+  return cond_prob;
 }
 
 double Scorer::get_sent_log_prob(const std::vector<std::string>& words) {
-    std::vector<std::string> sentence;
-    if (words.size() == 0) {
-        for (size_t i = 0; i < _max_order; ++i) {
-            sentence.push_back(START_TOKEN);
-        }
-    } else {
-        for (size_t i = 0; i < _max_order - 1; ++i) {
-            sentence.push_back(START_TOKEN);
-        }
-        sentence.insert(sentence.end(), words.begin(), words.end());
+  std::vector<std::string> sentence;
+  if (words.size() == 0) {
+    for (size_t i = 0; i < _max_order; ++i) {
+      sentence.push_back(START_TOKEN);
     }
-    sentence.push_back(END_TOKEN);
-    return get_log_prob(sentence);
+  } else {
+    for (size_t i = 0; i < _max_order - 1; ++i) {
+      sentence.push_back(START_TOKEN);
+    }
+    sentence.insert(sentence.end(), words.begin(), words.end());
+  }
+  sentence.push_back(END_TOKEN);
+  return get_log_prob(sentence);
 }
 
 double Scorer::get_log_prob(const std::vector<std::string>& words) {
-    assert(words.size() > _max_order);
-    double score = 0.0;
-    for (size_t i = 0; i < words.size() - _max_order + 1; ++i) {
-        std::vector<std::string> ngram(words.begin() + i,
-                                       words.begin() + i + _max_order);
-        score += get_log_cond_prob(ngram);
-    }
-    return score;
+  assert(words.size() > _max_order);
+  double score = 0.0;
+  for (size_t i = 0; i < words.size() - _max_order + 1; ++i) {
+    std::vector<std::string> ngram(words.begin() + i,
+                                   words.begin() + i + _max_order);
+    score += get_log_cond_prob(ngram);
+  }
+  return score;
 }
 
 void Scorer::reset_params(float alpha, float beta) {
-    this->alpha = alpha;
-    this->beta = beta;
+  this->alpha = alpha;
+  this->beta = beta;
 }
 
 std::string Scorer::vec2str(const std::vector<int>& input) {
-    std::string word;
-    for (auto ind : input) {
-        word += _char_list[ind];
-    }
-    return word;
+  std::string word;
+  for (auto ind : input) {
+    word += _char_list[ind];
+  }
+  return word;
 }
 
-std::vector<std::string>
-Scorer::split_labels(const std::vector<int> &labels) {
-    if (labels.empty())
-        return {};
-
-    std::string s = vec2str(labels);
-    std::vector<std::string> words;
-    if (_is_character_based) {
-        words = split_utf8_str(s);
-    } else {
-        words = split_str(s, " ");
-    }
-    return words;
+std::vector<std::string> Scorer::split_labels(const std::vector<int>& labels) {
+  if (labels.empty()) return {};
+
+  std::string s = vec2str(labels);
+  std::vector<std::string> words;
+  if (_is_character_based) {
+    words = split_utf8_str(s);
+  } else {
+    words = split_str(s, " ");
+  }
+  return words;
 }
 
 void Scorer::set_char_map(std::vector<std::string> char_list) {
-    _char_list = char_list;
-    _char_map.clear();
-
-    for(unsigned int i = 0; i < _char_list.size(); i++)
-    {
-        if (_char_list[i] == " ") {
-            _SPACE_ID = i;
-            _char_map[' '] = i;
-        } else if(_char_list[i].size() == 1){
-            _char_map[_char_list[i][0]] = i;
-        }
+  _char_list = char_list;
+  _char_map.clear();
+
+  for (unsigned int i = 0; i < _char_list.size(); i++) {
+    if (_char_list[i] == " ") {
+      _SPACE_ID = i;
+      _char_map[' '] = i;
+    } else if (_char_list[i].size() == 1) {
+      _char_map[_char_list[i][0]] = i;
     }
+  }
 }
 
 std::vector<std::string> Scorer::make_ngram(PathTrie* prefix) {
-    std::vector<std::string> ngram;
-    PathTrie* current_node = prefix;
-    PathTrie* new_node = nullptr;
-
-    for (int order = 0; order < _max_order; order++) {
-        std::vector<int> prefix_vec;
-
-        if (_is_character_based) {
-            new_node = current_node->get_path_vec(prefix_vec, _SPACE_ID, 1);
-            current_node = new_node;
-        } else {
-            new_node = current_node->get_path_vec(prefix_vec, _SPACE_ID);
-            current_node = new_node->_parent;  // Skipping spaces
-        }
-
-        // reconstruct word
-        std::string word = vec2str(prefix_vec);
-        ngram.push_back(word);
-
-        if (new_node->_character == -1) {
-            // No more spaces, but still need order
-            for (int i = 0; i < _max_order - order - 1; i++) {
-                ngram.push_back(START_TOKEN);
-            }
-            break;
-        }
-    }
-    std::reverse(ngram.begin(), ngram.end());
-    return ngram;
-}
-
-void Scorer::fill_dictionary(bool add_space) {
+  std::vector<std::string> ngram;
+  PathTrie* current_node = prefix;
+  PathTrie* new_node = nullptr;
 
-    fst::StdVectorFst dictionary;
-    // First reverse char_list so ints can be accessed by chars
-    std::unordered_map<std::string, int> char_map;
-    for (unsigned int i = 0; i < _char_list.size(); i++) {
-        char_map[_char_list[i]] = i;
-    }
+  for (int order = 0; order < _max_order; order++) {
+    std::vector<int> prefix_vec;
 
-    // For each unigram convert to ints and put in trie
-    int vocab_size = 0;
-    for (const auto& word : _vocabulary) {
-        bool added = add_word_to_dictionary(word,
-                                            char_map,
-                                            add_space,
-                                            _SPACE_ID,
-                                            &dictionary);
-        vocab_size += added ? 1 : 0;
+    if (_is_character_based) {
+      new_node = current_node->get_path_vec(prefix_vec, _SPACE_ID, 1);
+      current_node = new_node;
+    } else {
+      new_node = current_node->get_path_vec(prefix_vec, _SPACE_ID);
+      current_node = new_node->parent;  // Skipping spaces
     }
 
-    std::cerr << "Vocab Size " << vocab_size << std::endl;
-
-    // Simplify FST
-
-    // This gets rid of "epsilon" transitions in the FST.
-    // These are transitions that don't require a string input to be taken.
-    // Getting rid of them is necessary to make the FST determinisitc, but
-    // can greatly increase the size of the FST
-    fst::RmEpsilon(&dictionary);
-    fst::StdVectorFst* new_dict = new fst::StdVectorFst;
+    // reconstruct word
+    std::string word = vec2str(prefix_vec);
+    ngram.push_back(word);
 
-    // This makes the FST deterministic, meaning for any string input there's
-    // only one possible state the FST could be in.  It is assumed our
-    // dictionary is deterministic when using it.
-    // (lest we'd have to check for multiple transitions at each state)
-    fst::Determinize(dictionary, new_dict);
-
-    // Finds the simplest equivalent fst.  This is unnecessary but decreases
-    // memory usage of the dictionary
-    fst::Minimize(new_dict);
-    this->dictionary = new_dict;
+    if (new_node->character == -1) {
+      // No more spaces, but still need order
+      for (int i = 0; i < _max_order - order - 1; i++) {
+        ngram.push_back(START_TOKEN);
+      }
+      break;
+    }
+  }
+  std::reverse(ngram.begin(), ngram.end());
+  return ngram;
+}
 
+void Scorer::fill_dictionary(bool add_space) {
+  fst::StdVectorFst dictionary;
+  // First reverse char_list so ints can be accessed by chars
+  std::unordered_map<std::string, int> char_map;
+  for (unsigned int i = 0; i < _char_list.size(); i++) {
+    char_map[_char_list[i]] = i;
+  }
+
+  // For each unigram convert to ints and put in trie
+  int vocab_size = 0;
+  for (const auto& word : _vocabulary) {
+    bool added = add_word_to_dictionary(
+        word, char_map, add_space, _SPACE_ID, &dictionary);
+    vocab_size += added ? 1 : 0;
+  }
+
+  std::cerr << "Vocab Size " << vocab_size << std::endl;
+
+  // Simplify FST
+
+  // This gets rid of "epsilon" transitions in the FST.
+  // These are transitions that don't require a string input to be taken.
+  // Getting rid of them is necessary to make the FST determinisitc, but
+  // can greatly increase the size of the FST
+  fst::RmEpsilon(&dictionary);
+  fst::StdVectorFst* new_dict = new fst::StdVectorFst;
+
+  // This makes the FST deterministic, meaning for any string input there's
+  // only one possible state the FST could be in.  It is assumed our
+  // dictionary is deterministic when using it.
+  // (lest we'd have to check for multiple transitions at each state)
+  fst::Determinize(dictionary, new_dict);
+
+  // Finds the simplest equivalent fst.  This is unnecessary but decreases
+  // memory usage of the dictionary
+  fst::Minimize(new_dict);
+  this->dictionary = new_dict;
 }

deep_speech_2/deploy/scorer.h

 #ifndef SCORER_H_
 #define SCORER_H_
 
-#include <string>
 #include <memory>
-#include <vector>
+#include <string>
 #include <unordered_map>
+#include <vector>
 #include "lm/enumerate_vocab.hh"
-#include "lm/word_index.hh"
 #include "lm/virtual_interface.hh"
-#include "util/string_piece.hh"
+#include "lm/word_index.hh"
 #include "path_trie.h"
+#include "util/string_piece.hh"
 
 const double OOV_SCORE = -1000.0;
 const std::string START_TOKEN = "<s>";
 const std::string UNK_TOKEN = "<unk>";
 const std::string END_TOKEN = "</s>";
 
- // Implement a callback to retrive string vocabulary.
+// Implement a callback to retrive string vocabulary.
 class RetriveStrEnumerateVocab : public lm::EnumerateVocab {
 public:
-    RetriveStrEnumerateVocab() {}
+  RetriveStrEnumerateVocab() {}
 
-    void Add(lm::WordIndex index, const StringPiece& str) {
-        vocabulary.push_back(std::string(str.data(), str.length()));
-    }
+  void Add(lm::WordIndex index, const StringPiece& str) {
+    vocabulary.push_back(std::string(str.data(), str.length()));
+  }
 
-    std::vector<std::string> vocabulary;
+  std::vector<std::string> vocabulary;
 };
 
 // External scorer to query languange score for n-gram or sentence.
@@ -33,59 +33,59 @@ public:
 //     Scorer scorer(alpha, beta, "path_of_language_model");
 //     scorer.get_log_cond_prob({ "WORD1", "WORD2", "WORD3" });
 //     scorer.get_sent_log_prob({ "WORD1", "WORD2", "WORD3" });
-class Scorer{
+class Scorer {
 public:
-    Scorer(double alpha, double beta, const std::string& lm_path);
-    ~Scorer();
+  Scorer(double alpha, double beta, const std::string& lm_path);
+  ~Scorer();
 
-    double get_log_cond_prob(const std::vector<std::string>& words);
+  double get_log_cond_prob(const std::vector<std::string>& words);
 
-    double get_sent_log_prob(const std::vector<std::string>& words);
+  double get_sent_log_prob(const std::vector<std::string>& words);
 
-    size_t get_max_order() { return _max_order; }
+  size_t get_max_order() { return _max_order; }
 
-    bool is_char_map_empty() {return _char_map.size() == 0; }
+  bool is_char_map_empty() { return _char_map.size() == 0; }
 
-    bool is_character_based() { return _is_character_based; }
+  bool is_character_based() { return _is_character_based; }
 
-    // reset params alpha & beta
-    void reset_params(float alpha, float beta);
+  // reset params alpha & beta
+  void reset_params(float alpha, float beta);
 
-    // make ngram
-    std::vector<std::string> make_ngram(PathTrie* prefix);
+  // make ngram
+  std::vector<std::string> make_ngram(PathTrie* prefix);
 
-    // fill dictionary for fst
-    void fill_dictionary(bool add_space);
+  // fill dictionary for fst
+  void fill_dictionary(bool add_space);
 
-    // set char map
-    void set_char_map(std::vector<std::string> char_list);
+  // set char map
+  void set_char_map(std::vector<std::string> char_list);
 
-    std::vector<std::string> split_labels(const std::vector<int> &labels);
+  std::vector<std::string> split_labels(const std::vector<int>& labels);
 
-    // expose to decoder
-    double alpha;
-    double beta;
+  // expose to decoder
+  double alpha;
+  double beta;
 
-    // fst dictionary
-    void* dictionary;
+  // fst dictionary
+  void* dictionary;
 
 protected:
-    void load_LM(const char* filename);
+  void load_LM(const char* filename);
 
-    double get_log_prob(const std::vector<std::string>& words);
+  double get_log_prob(const std::vector<std::string>& words);
 
-    std::string vec2str(const std::vector<int> &input);
+  std::string vec2str(const std::vector<int>& input);
 
 private:
-    void* _language_model;
-    bool _is_character_based;
-    size_t _max_order;
+  void* _language_model;
+  bool _is_character_based;
+  size_t _max_order;
 
-    int _SPACE_ID;
-    std::vector<std::string> _char_list;
-    std::unordered_map<char, int> _char_map;
+  int _SPACE_ID;
+  std::vector<std::string> _char_list;
+  std::unordered_map<char, int> _char_map;
 
-    std::vector<std::string> _vocabulary;
+  std::vector<std::string> _vocabulary;
 };
 
-#endif // SCORER_H_
+#endif  // SCORER_H_