Skip to content

D
DeepSpeech

PaddlePaddle / DeepSpeech
大约 2 年 前同步成功

通知 210
Star 8425
Fork 1598
D
DeepSpeech
提交 5208b8e4 编写于 作者: Y Yibing Liu
浏览文件
操作

format C++ source code

上级 a2ddfe8d
显示空白变更内容
内联 并排
Showing with 749 addition and 779 deletion
deploy/ctc_decoders.cpp
浏览文件 @ 5208b8e4
#include <iostream>
#include <map>
#include "ctc_decoders.h"
#include <algorithm>
#include <utility>
#include <cmath>
#include <iostream>
#include <limits>
#include "fst/fstlib.h"
#include "ctc_decoders.h"
#include <map>
#include <utility>
#include "ThreadPool.h"
#include "decoder_utils.h"
#include "fst/fstlib.h"
#include "path_trie.h"
#include "ThreadPool.h"
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) {
// dimension check
int num_time_steps = probs_seq.size();
for (int i=0; i<num_time_steps; i++) {
if (probs_seq[i].size() != vocabulary.size()+1) {
for (int i = 0; i < num_time_steps; i++) {
if (probs_seq[i].size() != vocabulary.size() + 1) {
std::cout << "The shape of probs_seq does not match"
<< " with the shape of the vocabulary!" << std::endl;
exit(1);
......@@ -42,7 +41,7 @@ std::string ctc_best_path_decoder(std::vector<std::vector<double> > probs_seq,
std::vector<int> idx_vec;
for (int i = 0; i < max_idx_vec.size(); i++) {
if ((i == 0) || ((i > 0) && max_idx_vec[i] != max_idx_vec[i-1])) {
if ((i == 0) || ((i > 0) && max_idx_vec[i] != max_idx_vec[i - 1])) {
idx_vec.push_back(max_idx_vec[i]);
}
}
......@@ -56,15 +55,14 @@ std::string ctc_best_path_decoder(std::vector<std::vector<double> > probs_seq,
return best_path_result;
}
std::vector<std::pair<double, std::string> >
ctc_beam_search_decoder(std::vector<std::vector<double> > probs_seq,
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,
int cutoff_top_n,
Scorer *ext_scorer)
{
Scorer *extscorer) {
// dimension check
int num_time_steps = probs_seq.size();
for (int i = 0; i < num_time_steps; i++) {
......@@ -82,35 +80,33 @@ std::vector<std::pair<double, std::string> >
}
// assign space ID
std::vector<std::string>::iterator it = std::find(vocabulary.begin(),
vocabulary.end(), " ");
std::vector<std::string>::iterator it =
std::find(vocabulary.begin(), vocabulary.end(), " ");
int space_id = it - vocabulary.begin();
// if no space in vocabulary
if(space_id >= vocabulary.size()) {
if (space_id >= vocabulary.size()) {
space_id = -2;
}
// init prefixes' root
PathTrie root;
root._score = root._log_prob_b_prev = 0.0;
std::vector<PathTrie*> prefixes;
root.score = root.log_prob_b_prev = 0.0;
std::vector<PathTrie *> prefixes;
prefixes.push_back(&root);
if ( ext_scorer != nullptr) {
if (ext_scorer->is_char_map_empty()) {
ext_scorer->set_char_map(vocabulary);
if (extscorer != nullptr) {
if (extscorer->is_char_map_empty()) {
extscorer->set_char_map(vocabulary);
}
if (!ext_scorer->is_character_based()) {
if (ext_scorer->dictionary == nullptr) {
if (!extscorer->is_character_based()) {
if (extscorer->dictionary == nullptr) {
// fill dictionary for fst
ext_scorer->fill_dictionary(true);
extscorer->fill_dictionary(true);
}
auto fst_dict = static_cast<fst::StdVectorFst*>
(ext_scorer->dictionary);
fst::StdVectorFst* dict_ptr = fst_dict->Copy(true);
auto fst_dict = static_cast<fst::StdVectorFst *>(extscorer->dictionary);
fst::StdVectorFst *dict_ptr = fst_dict->Copy(true);
root.set_dictionary(dict_ptr);
auto matcher = std::make_shared<FSTMATCH>
(*dict_ptr, fst::MATCH_INPUT);
auto matcher = std::make_shared<FSTMATCH>(*dict_ptr, fst::MATCH_INPUT);
root.set_matcher(matcher);
}
}
......@@ -118,45 +114,44 @@ std::vector<std::pair<double, std::string> >
// prefix search over time
for (int time_step = 0; time_step < num_time_steps; time_step++) {
std::vector<double> prob = probs_seq[time_step];
std::vector<std::pair<int, double> > prob_idx;
for (int i=0; i<prob.size(); i++) {
std::vector<std::pair<int, double>> prob_idx;
for (int i = 0; i < prob.size(); i++) {
prob_idx.push_back(std::pair<int, double>(i, prob[i]));
}
float min_cutoff = -NUM_FLT_INF;
bool full_beam = false;
if (ext_scorer != nullptr) {
if (extscorer != nullptr) {
int num_prefixes = std::min((int)prefixes.size(), beam_size);
std::sort(prefixes.begin(), prefixes.begin() + num_prefixes,
prefix_compare);
min_cutoff = prefixes[num_prefixes-1]->_score + log(prob[blank_id])
- std::max(0.0, ext_scorer->beta);
std::sort(
prefixes.begin(), prefixes.begin() + num_prefixes, prefix_compare);
min_cutoff = prefixes[num_prefixes - 1]->score + log(prob[blank_id]) -
std::max(0.0, extscorer->beta);
full_beam = (num_prefixes == beam_size);
}
// pruning of vacobulary
int cutoff_len = prob.size();
if (cutoff_prob < 1.0 || cutoff_top_n < prob.size()) {
std::sort(prob_idx.begin(),
prob_idx.end(),
pair_comp_second_rev<int, double>);
std::sort(
prob_idx.begin(), prob_idx.end(), pair_comp_second_rev<int, double>);
if (cutoff_prob < 1.0) {
double cum_prob = 0.0;
cutoff_len = 0;
for (int i=0; i<prob_idx.size(); i++) {
for (int i = 0; i < prob_idx.size(); i++) {
cum_prob += prob_idx[i].second;
cutoff_len += 1;
if (cum_prob >= cutoff_prob) break;
}
}
cutoff_len = std::min(cutoff_len, cutoff_top_n);
prob_idx = std::vector<std::pair<int, double> >( prob_idx.begin(),
prob_idx.begin() + cutoff_len);
prob_idx = std::vector<std::pair<int, double>>(
prob_idx.begin(), prob_idx.begin() + cutoff_len);
}
std::vector<std::pair<int, float> > log_prob_idx;
std::vector<std::pair<int, float>> log_prob_idx;
for (int i = 0; i < cutoff_len; i++) {
log_prob_idx.push_back(std::pair<int, float>
(prob_idx[i].first, log(prob_idx[i].second + NUM_FLT_MIN)));
log_prob_idx.push_back(std::pair<int, float>(
prob_idx[i].first, log(prob_idx[i].second + NUM_FLT_MIN)));
}
// loop over chars
......@@ -164,24 +159,22 @@ std::vector<std::pair<double, std::string> >
auto c = log_prob_idx[index].first;
float log_prob_c = log_prob_idx[index].second;
for (int i = 0; i < prefixes.size() && i<beam_size; i++) {
for (int i = 0; i < prefixes.size() && i < beam_size; i++) {
auto prefix = prefixes[i];
if (full_beam && log_prob_c + prefix->_score < min_cutoff) {
if (full_beam && log_prob_c + prefix->score < min_cutoff) {
break;
}
// blank
if (c == blank_id) {
prefix->_log_prob_b_cur = log_sum_exp(
prefix->_log_prob_b_cur,
log_prob_c + prefix->_score);
prefix->log_prob_b_cur =
log_sum_exp(prefix->log_prob_b_cur, log_prob_c + prefix->score);
continue;
}
// repeated character
if (c == prefix->_character) {
prefix->_log_prob_nb_cur = log_sum_exp(
prefix->_log_prob_nb_cur,
log_prob_c + prefix->_log_prob_nb_prev);
if (c == prefix->character) {
prefix->log_prob_nb_cur = log_sum_exp(
prefix->log_prob_nb_cur, log_prob_c + prefix->log_prob_nb_prev);
}
// get new prefix
auto prefix_new = prefix->get_path_trie(c);
......@@ -189,36 +182,35 @@ std::vector<std::pair<double, std::string> >
if (prefix_new != nullptr) {
float log_p = -NUM_FLT_INF;
if (c == prefix->_character
&& prefix->_log_prob_b_prev > -NUM_FLT_INF) {
log_p = log_prob_c + prefix->_log_prob_b_prev;
} else if (c != prefix->_character) {
log_p = log_prob_c + prefix->_score;
if (c == prefix->character &&
prefix->log_prob_b_prev > -NUM_FLT_INF) {
log_p = log_prob_c + prefix->log_prob_b_prev;
} else if (c != prefix->character) {
log_p = log_prob_c + prefix->score;
}
// language model scoring
if (ext_scorer != nullptr &&
(c == space_id || ext_scorer->is_character_based()) ) {
PathTrie *prefix_to_score = nullptr;
if (extscorer != nullptr &&
(c == space_id || extscorer->is_character_based())) {
PathTrie *prefix_toscore = nullptr;
// skip scoring the space
if (ext_scorer->is_character_based()) {
prefix_to_score = prefix_new;
if (extscorer->is_character_based()) {
prefix_toscore = prefix_new;
} else {
prefix_to_score = prefix;
prefix_toscore = prefix;
}
double score = 0.0;
std::vector<std::string> ngram;
ngram = ext_scorer->make_ngram(prefix_to_score);
score = ext_scorer->get_log_cond_prob(ngram) *
ext_scorer->alpha;
ngram = extscorer->make_ngram(prefix_toscore);
score = extscorer->get_log_cond_prob(ngram) * extscorer->alpha;
log_p += score;
log_p += ext_scorer->beta;
log_p += extscorer->beta;
}
prefix_new->_log_prob_nb_cur = log_sum_exp(
prefix_new->_log_prob_nb_cur, log_p);
prefix_new->log_prob_nb_cur =
log_sum_exp(prefix_new->log_prob_nb_cur, log_p);
}
} // end of loop over prefix
} // end of loop over chars
......@@ -242,33 +234,32 @@ std::vector<std::pair<double, std::string> >
// compute aproximate ctc score as the return score
for (size_t i = 0; i < beam_size && i < prefixes.size(); i++) {
double approx_ctc = prefixes[i]->_score;
double approx_ctc = prefixes[i]->score;
if (ext_scorer != nullptr) {
if (extscorer != nullptr) {
std::vector<int> output;
prefixes[i]->get_path_vec(output);
size_t prefix_length = output.size();
auto words = ext_scorer->split_labels(output);
auto words = extscorer->split_labels(output);
// remove word insert
approx_ctc = approx_ctc - prefix_length * ext_scorer->beta;
approx_ctc = approx_ctc - prefix_length * extscorer->beta;
// remove language model weight:
approx_ctc -= (ext_scorer->get_sent_log_prob(words))
* ext_scorer->alpha;
approx_ctc -= (extscorer->get_sent_log_prob(words)) * extscorer->alpha;
}
prefixes[i]->_approx_ctc = approx_ctc;
prefixes[i]->approx_ctc = approx_ctc;
}
// allow for the post processing
std::vector<PathTrie*> space_prefixes;
std::vector<PathTrie *> space_prefixes;
if (space_prefixes.empty()) {
for (size_t i = 0; i < beam_size && i< prefixes.size(); i++) {
for (size_t i = 0; i < beam_size && i < prefixes.size(); i++) {
space_prefixes.push_back(prefixes[i]);
}
}
std::sort(space_prefixes.begin(), space_prefixes.end(), prefix_compare);
std::vector<std::pair<double, std::string> > output_vecs;
std::vector<std::pair<double, std::string>> output_vecs;
for (size_t i = 0; i < beam_size && i < space_prefixes.size(); i++) {
std::vector<int> output;
space_prefixes[i]->get_path_vec(output);
......@@ -277,17 +268,16 @@ std::vector<std::pair<double, std::string> >
for (int j = 0; j < output.size(); j++) {
output_str += vocabulary[output[j]];
}
std::pair<double, std::string>
output_pair(-space_prefixes[i]->_approx_ctc, output_str);
std::pair<double, std::string> output_pair(-space_prefixes[i]->approx_ctc,
output_str);
output_vecs.emplace_back(output_pair);
}
return output_vecs;
}
}
std::vector<std::vector<std::pair<double, std::string> > >
ctc_beam_search_decoder_batch(
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,
......@@ -295,8 +285,7 @@ std::vector<std::vector<std::pair<double, std::string> > >
int num_processes,
double cutoff_prob,
int cutoff_top_n,
Scorer *ext_scorer
) {
Scorer *extscorer) {
if (num_processes <= 0) {
std::cout << "num_processes must be nonnegative!" << std::endl;
exit(1);
......@@ -307,29 +296,32 @@ std::vector<std::vector<std::pair<double, std::string> > >
int batch_size = probs_split.size();
// scorer filling up
if ( ext_scorer != nullptr) {
if (ext_scorer->is_char_map_empty()) {
ext_scorer->set_char_map(vocabulary);
if (extscorer != nullptr) {
if (extscorer->is_char_map_empty()) {
extscorer->set_char_map(vocabulary);
}
if(!ext_scorer->is_character_based()
&& ext_scorer->dictionary == nullptr) {
if (!extscorer->is_character_based() &&
extscorer->dictionary == nullptr) {
// init dictionary
ext_scorer->fill_dictionary(true);
extscorer->fill_dictionary(true);
}
}
// enqueue the tasks of decoding
std::vector<std::future<std::vector<std::pair<double, std::string>>>> res;
for (int i = 0; i < batch_size; i++) {
res.emplace_back(
pool.enqueue(ctc_beam_search_decoder, probs_split[i],
beam_size, vocabulary, blank_id, cutoff_prob,
cutoff_top_n, ext_scorer)
);
res.emplace_back(pool.enqueue(ctc_beam_search_decoder,
probs_split[i],
beam_size,
vocabulary,
blank_id,
cutoff_prob,
cutoff_top_n,
extscorer));
}
// get decoding results
std::vector<std::vector<std::pair<double, std::string> > > batch_results;
std::vector<std::vector<std::pair<double, std::string>>> batch_results;
for (int i = 0; i < batch_size; i++) {
batch_results.emplace_back(res[i].get());
}
......
deploy/ctc_decoders.h
浏览文件 @ 5208b8e4
#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
......@@ -16,7 +16,7 @@
* 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::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,
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
);
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,
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
);
double cutoff_prob = 1.0,
int cutoff_top_n = 40,
Scorer *ext_scorer = NULL);
#endif // CTC_BEAM_SEARCH_DECODER_H_
deploy/decoder_utils.cpp
浏览文件 @ 5208b8e4
#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;
......@@ -11,17 +11,14 @@ size_t get_utf8_str_len(const std::string& str) {
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)
{
if ((c & 0xc0) != 0x80) //new UTF-8 character
{
if (!out_str.empty())
for (char c : str) {
if ((c & 0xc0) != 0x80) // new UTF-8 character
{
if (!out_str.empty()) {
result.push_back(out_str);
out_str.clear();
}
......@@ -33,8 +30,8 @@ std::vector<std::string> split_utf8_str(const std::string& str)
return result;
}
std::vector<std::string> split_str(const std::string &s,
const std::string &delim) {
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) {
......@@ -54,14 +51,14 @@ std::vector<std::string> split_str(const std::string &s,
}
bool prefix_compare(const PathTrie* x, const PathTrie* y) {
if (x->_score == y->_score) {
if (x->_character == y->_character) {
if (x->score == y->score) {
if (x->character == y->character) {
return false;
} else {
return (x->_character < y->_character);
return (x->character < y->character);
}
} else {
return x->_score > y->_score;
return x->score > y->score;
}
}
......@@ -82,7 +79,8 @@ void add_word_to_fst(const std::vector<int>& word,
dictionary->SetFinal(dst, fst::StdArc::Weight::One());
}
bool add_word_to_dictionary(const std::string& 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,
......
deploy/decoder_utils.h
浏览文件 @ 5208b8e4
......@@ -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)
{
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)
{
const std::pair<T1, T2> &b) {
return a.second > b.second;
}
template <typename T>
T log_sum_exp(const T &x, const T &y)
{
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;
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_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);
fst::StdVectorFst *dictionary);
#endif // DECODER_UTILS_H
deploy/path_trie.cpp
浏览文件 @ 5208b8e4
......@@ -4,20 +4,20 @@
#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;
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;
character = _ROOT;
_exists = true;
_parent = nullptr;
parent = nullptr;
_dictionary = nullptr;
_dictionary_state = 0;
_has_dictionary = false;
......@@ -37,13 +37,13 @@ PathTrie* PathTrie::get_path_trie(int new_char, bool reset) {
break;
}
}
if ( child != _children.end() ) {
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;
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 {
......@@ -61,8 +61,8 @@ PathTrie* PathTrie::get_path_trie(int new_char, bool reset) {
return nullptr;
} else {
PathTrie* new_path = new PathTrie;
new_path->_character = new_char;
new_path->_parent = this;
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;
......@@ -72,8 +72,8 @@ PathTrie* PathTrie::get_path_trie(int new_char, bool reset) {
}
} else {
PathTrie* new_path = new PathTrie;
new_path->_character = new_char;
new_path->_parent = this;
new_path->character = new_char;
new_path->parent = this;
_children.push_back(std::make_pair(new_char, new_path));
return new_path;
}
......@@ -87,27 +87,24 @@ PathTrie* PathTrie::get_path_vec(std::vector<int>& output) {
PathTrie* PathTrie::get_path_vec(std::vector<int>& output,
int stop,
size_t max_steps) {
if (_character == stop ||
_character == _ROOT ||
output.size() == 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);
output.push_back(character);
return parent->get_path_vec(output, stop, max_steps);
}
}
void PathTrie::iterate_to_vec(
std::vector<PathTrie*>& output) {
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_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);
score = log_sum_exp(log_prob_b_prev, log_prob_nb_prev);
output.push_back(this);
}
for (auto child : _children) {
......@@ -119,17 +116,17 @@ 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);
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();
if (parent->_children.size() == 0 && !parent->_exists) {
parent->remove();
}
delete this;
......
deploy/path_trie.h
浏览文件 @ 5208b8e4
#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>;
......@@ -17,38 +17,36 @@ public:
PathTrie* get_path_trie(int new_char, bool reset = true);
PathTrie* get_path_vec(std::vector<int> &output);
PathTrie* get_path_vec(std::vector<int>& output);
PathTrie* get_path_vec(std::vector<int>& output,
int stop,
size_t max_steps = std::numeric_limits<size_t>::max());
void iterate_to_vec(std::vector<PathTrie*> &output);
void iterate_to_vec(std::vector<PathTrie*>& output);
void set_dictionary(fst::StdVectorFst* dictionary);
void set_matcher(std::shared_ptr<FSTMATCH> matcher);
bool is_empty() {
return _ROOT == _character;
}
bool is_empty() { return _ROOT == character; }
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;
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;
private:
int _ROOT;
int _character;
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;
......
deploy/scorer.cpp
浏览文件 @ 5208b8e4
#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;
......@@ -25,8 +25,7 @@ Scorer::Scorer(double alpha, double beta, const std::string& lm_path) {
Scorer::~Scorer() {
if (_language_model != nullptr)
delete static_cast<lm::base::Model*>(_language_model);
if (dictionary != nullptr)
delete static_cast<fst::StdVectorFst*>(dictionary);
if (dictionary != nullptr) delete static_cast<fst::StdVectorFst*>(dictionary);
}
void Scorer::load_LM(const char* filename) {
......@@ -41,11 +40,9 @@ void Scorer::load_LM(const char* filename) {
_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) {
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;
}
}
......@@ -112,10 +109,8 @@ std::string Scorer::vec2str(const std::vector<int>& input) {
return word;
}
std::vector<std::string>
Scorer::split_labels(const std::vector<int> &labels) {
if (labels.empty())
return {};
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;
......@@ -131,12 +126,11 @@ 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++)
{
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){
} else if (_char_list[i].size() == 1) {
_char_map[_char_list[i][0]] = i;
}
}
......@@ -155,14 +149,14 @@ std::vector<std::string> Scorer::make_ngram(PathTrie* prefix) {
current_node = new_node;
} else {
new_node = current_node->get_path_vec(prefix_vec, _SPACE_ID);
current_node = new_node->_parent; // Skipping spaces
current_node = new_node->parent; // Skipping spaces
}
// reconstruct word
std::string word = vec2str(prefix_vec);
ngram.push_back(word);
if (new_node->_character == -1) {
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);
......@@ -175,7 +169,6 @@ std::vector<std::string> Scorer::make_ngram(PathTrie* prefix) {
}
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;
......@@ -186,11 +179,8 @@ void Scorer::fill_dictionary(bool add_space) {
// 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);
bool added = add_word_to_dictionary(
word, char_map, add_space, _SPACE_ID, &dictionary);
vocab_size += added ? 1 : 0;
}
......@@ -215,5 +205,4 @@ void Scorer::fill_dictionary(bool add_space) {
// memory usage of the dictionary
fst::Minimize(new_dict);
this->dictionary = new_dict;
}
deploy/scorer.h
浏览文件 @ 5208b8e4
#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() {}
......@@ -33,7 +33,7 @@ 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();
......@@ -44,7 +44,7 @@ public:
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; }
......@@ -60,7 +60,7 @@ public:
// 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;
......@@ -74,7 +74,7 @@ protected:
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;
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或