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333 lines
10 KiB
333 lines
10 KiB
#include "ctc_decoders.h"
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#include <algorithm>
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#include <cmath>
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#include <iostream>
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#include <limits>
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#include <map>
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#include <utility>
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#include "ThreadPool.h"
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#include "fst/fstlib.h"
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#include "decoder_utils.h"
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#include "path_trie.h"
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std::string ctc_greedy_decoder(
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const std::vector<std::vector<double>> &probs_seq,
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const std::vector<std::string> &vocabulary) {
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// dimension check
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int num_time_steps = probs_seq.size();
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for (int i = 0; i < num_time_steps; i++) {
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if (probs_seq[i].size() != vocabulary.size() + 1) {
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std::cout << "The shape of probs_seq does not match"
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<< " with the shape of the vocabulary!" << std::endl;
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exit(1);
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}
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}
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int blank_id = vocabulary.size();
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std::vector<int> max_idx_vec;
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double max_prob = 0.0;
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int max_idx = 0;
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for (int i = 0; i < num_time_steps; i++) {
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for (int j = 0; j < probs_seq[i].size(); j++) {
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if (max_prob < probs_seq[i][j]) {
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max_idx = j;
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max_prob = probs_seq[i][j];
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}
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}
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max_idx_vec.push_back(max_idx);
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max_prob = 0.0;
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max_idx = 0;
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}
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std::vector<int> idx_vec;
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for (int i = 0; i < max_idx_vec.size(); i++) {
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if ((i == 0) || ((i > 0) && max_idx_vec[i] != max_idx_vec[i - 1])) {
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idx_vec.push_back(max_idx_vec[i]);
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}
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}
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std::string best_path_result;
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for (int i = 0; i < idx_vec.size(); i++) {
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if (idx_vec[i] != blank_id) {
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best_path_result += vocabulary[idx_vec[i]];
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}
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}
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return best_path_result;
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}
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std::vector<std::pair<double, std::string>> ctc_beam_search_decoder(
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const std::vector<std::vector<double>> &probs_seq,
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int beam_size,
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std::vector<std::string> vocabulary,
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int blank_id,
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double cutoff_prob,
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int cutoff_top_n,
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Scorer *extscorer) {
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// dimension check
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size_t num_time_steps = probs_seq.size();
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for (int i = 0; i < num_time_steps; i++) {
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if (probs_seq[i].size() != vocabulary.size() + 1) {
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std::cout << " The shape of probs_seq does not match"
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<< " with the shape of the vocabulary!" << std::endl;
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exit(1);
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}
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}
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// blank_id check
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if (blank_id > vocabulary.size()) {
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std::cout << " Invalid blank_id! " << std::endl;
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exit(1);
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}
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// assign space ID
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std::vector<std::string>::iterator it =
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std::find(vocabulary.begin(), vocabulary.end(), " ");
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int space_id = it - vocabulary.begin();
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// if no space in vocabulary
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if (space_id >= vocabulary.size()) {
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space_id = -2;
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}
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// init prefixes' root
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PathTrie root;
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root.score = root.log_prob_b_prev = 0.0;
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std::vector<PathTrie *> prefixes;
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prefixes.push_back(&root);
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if (extscorer != nullptr) {
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if (extscorer->is_char_map_empty()) {
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extscorer->set_char_map(vocabulary);
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}
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if (!extscorer->is_character_based()) {
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if (extscorer->dictionary == nullptr) {
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// fill dictionary for fst with space
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extscorer->fill_dictionary(true);
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}
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auto fst_dict = static_cast<fst::StdVectorFst *>(extscorer->dictionary);
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fst::StdVectorFst *dict_ptr = fst_dict->Copy(true);
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root.set_dictionary(dict_ptr);
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auto matcher = std::make_shared<FSTMATCH>(*dict_ptr, fst::MATCH_INPUT);
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root.set_matcher(matcher);
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}
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}
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// prefix search over time
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for (int time_step = 0; time_step < num_time_steps; time_step++) {
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std::vector<double> prob = probs_seq[time_step];
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std::vector<std::pair<int, double>> prob_idx;
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for (int i = 0; i < prob.size(); i++) {
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prob_idx.push_back(std::pair<int, double>(i, prob[i]));
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}
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float min_cutoff = -NUM_FLT_INF;
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bool full_beam = false;
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if (extscorer != nullptr) {
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int num_prefixes = std::min((int)prefixes.size(), beam_size);
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std::sort(
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prefixes.begin(), prefixes.begin() + num_prefixes, prefix_compare);
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min_cutoff = prefixes[num_prefixes - 1]->score + log(prob[blank_id]) -
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std::max(0.0, extscorer->beta);
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full_beam = (num_prefixes == beam_size);
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}
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// pruning of vacobulary
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int cutoff_len = prob.size();
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if (cutoff_prob < 1.0 || cutoff_top_n < prob.size()) {
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std::sort(
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prob_idx.begin(), prob_idx.end(), pair_comp_second_rev<int, double>);
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if (cutoff_prob < 1.0) {
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double cum_prob = 0.0;
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cutoff_len = 0;
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for (int i = 0; i < prob_idx.size(); i++) {
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cum_prob += prob_idx[i].second;
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cutoff_len += 1;
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if (cum_prob >= cutoff_prob) break;
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}
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}
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cutoff_len = std::min(cutoff_len, cutoff_top_n);
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prob_idx = std::vector<std::pair<int, double>>(
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prob_idx.begin(), prob_idx.begin() + cutoff_len);
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}
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std::vector<std::pair<int, float>> log_prob_idx;
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for (int i = 0; i < cutoff_len; i++) {
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log_prob_idx.push_back(std::pair<int, float>(
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prob_idx[i].first, log(prob_idx[i].second + NUM_FLT_MIN)));
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}
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// loop over chars
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for (int index = 0; index < log_prob_idx.size(); index++) {
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auto c = log_prob_idx[index].first;
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float log_prob_c = log_prob_idx[index].second;
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for (int i = 0; i < prefixes.size() && i < beam_size; i++) {
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auto prefix = prefixes[i];
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if (full_beam && log_prob_c + prefix->score < min_cutoff) {
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break;
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}
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// blank
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if (c == blank_id) {
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prefix->log_prob_b_cur =
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log_sum_exp(prefix->log_prob_b_cur, log_prob_c + prefix->score);
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continue;
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}
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// repeated character
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if (c == prefix->character) {
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prefix->log_prob_nb_cur = log_sum_exp(
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prefix->log_prob_nb_cur, log_prob_c + prefix->log_prob_nb_prev);
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}
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// get new prefix
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auto prefix_new = prefix->get_path_trie(c);
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if (prefix_new != nullptr) {
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float log_p = -NUM_FLT_INF;
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if (c == prefix->character &&
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prefix->log_prob_b_prev > -NUM_FLT_INF) {
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log_p = log_prob_c + prefix->log_prob_b_prev;
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} else if (c != prefix->character) {
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log_p = log_prob_c + prefix->score;
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}
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// language model scoring
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if (extscorer != nullptr &&
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(c == space_id || extscorer->is_character_based())) {
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PathTrie *prefix_toscore = nullptr;
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// skip scoring the space
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if (extscorer->is_character_based()) {
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prefix_toscore = prefix_new;
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} else {
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prefix_toscore = prefix;
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}
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double score = 0.0;
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std::vector<std::string> ngram;
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ngram = extscorer->make_ngram(prefix_toscore);
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score = extscorer->get_log_cond_prob(ngram) * extscorer->alpha;
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log_p += score;
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log_p += extscorer->beta;
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}
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prefix_new->log_prob_nb_cur =
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log_sum_exp(prefix_new->log_prob_nb_cur, log_p);
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}
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} // end of loop over prefix
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} // end of loop over chars
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prefixes.clear();
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// update log probs
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root.iterate_to_vec(prefixes);
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// only preserve top beam_size prefixes
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if (prefixes.size() >= beam_size) {
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std::nth_element(prefixes.begin(),
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prefixes.begin() + beam_size,
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prefixes.end(),
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prefix_compare);
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for (size_t i = beam_size; i < prefixes.size(); i++) {
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prefixes[i]->remove();
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}
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}
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} // end of loop over time
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// compute aproximate ctc score as the return score
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for (size_t i = 0; i < beam_size && i < prefixes.size(); i++) {
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double approx_ctc = prefixes[i]->score;
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if (extscorer != nullptr) {
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std::vector<int> output;
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prefixes[i]->get_path_vec(output);
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size_t prefix_length = output.size();
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auto words = extscorer->split_labels(output);
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// remove word insert
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approx_ctc = approx_ctc - prefix_length * extscorer->beta;
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// remove language model weight:
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approx_ctc -= (extscorer->get_sent_log_prob(words)) * extscorer->alpha;
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}
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prefixes[i]->approx_ctc = approx_ctc;
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}
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// allow for the post processing
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std::vector<PathTrie *> space_prefixes;
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if (space_prefixes.empty()) {
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for (size_t i = 0; i < beam_size && i < prefixes.size(); i++) {
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space_prefixes.push_back(prefixes[i]);
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}
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}
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std::sort(space_prefixes.begin(), space_prefixes.end(), prefix_compare);
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std::vector<std::pair<double, std::string>> output_vecs;
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for (size_t i = 0; i < beam_size && i < space_prefixes.size(); i++) {
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std::vector<int> output;
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space_prefixes[i]->get_path_vec(output);
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// convert index to string
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std::string output_str;
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for (int j = 0; j < output.size(); j++) {
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output_str += vocabulary[output[j]];
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}
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std::pair<double, std::string> output_pair(-space_prefixes[i]->approx_ctc,
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output_str);
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output_vecs.emplace_back(output_pair);
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}
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return output_vecs;
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}
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std::vector<std::vector<std::pair<double, std::string>>>
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ctc_beam_search_decoder_batch(
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const std::vector<std::vector<std::vector<double>>> &probs_split,
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int beam_size,
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const std::vector<std::string> &vocabulary,
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int blank_id,
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int num_processes,
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double cutoff_prob,
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int cutoff_top_n,
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Scorer *extscorer) {
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if (num_processes <= 0) {
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std::cout << "num_processes must be nonnegative!" << std::endl;
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exit(1);
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}
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// thread pool
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ThreadPool pool(num_processes);
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// number of samples
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int batch_size = probs_split.size();
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// scorer filling up
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if (extscorer != nullptr) {
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if (extscorer->is_char_map_empty()) {
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extscorer->set_char_map(vocabulary);
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}
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if (!extscorer->is_character_based() && extscorer->dictionary == nullptr) {
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// init dictionary
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extscorer->fill_dictionary(true);
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}
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}
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// enqueue the tasks of decoding
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std::vector<std::future<std::vector<std::pair<double, std::string>>>> res;
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for (int i = 0; i < batch_size; i++) {
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res.emplace_back(pool.enqueue(ctc_beam_search_decoder,
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probs_split[i],
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beam_size,
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vocabulary,
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blank_id,
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cutoff_prob,
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cutoff_top_n,
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extscorer));
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}
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// get decoding results
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std::vector<std::vector<std::pair<double, std::string>>> batch_results;
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for (int i = 0; i < batch_size; i++) {
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batch_results.emplace_back(res[i].get());
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}
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return batch_results;
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}
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