blob: 20040bf4548ca90c8be54f79dfee692d4ccc6da2 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
|
#pragma once
#include "lm/word_index.hh"
#include "search/applied.hh"
#include "search/nbest.hh"
#include "moses/ChartCellCollection.h"
#include "moses/ChartParser.h"
#include <vector>
#include <string>
namespace Moses
{
class ScoreComponentCollection;
class InputType;
class LanguageModel;
namespace Incremental
{
class Manager
{
public:
Manager(const InputType &source);
~Manager();
template <class Model> void LMCallback(const Model &model, const std::vector<lm::WordIndex> &words);
const std::vector<search::Applied> &ProcessSentence();
// Call to get the same value as ProcessSentence returned.
const std::vector<search::Applied> &Completed() const {
return *completed_nbest_;
}
private:
template <class Model, class Best> search::History PopulateBest(const Model &model, const std::vector<lm::WordIndex> &words, Best &out);
const InputType &source_;
ChartCellCollectionBase cells_;
ChartParser parser_;
// Only one of single_best_ or n_best_ will be used, but it was easier to do this than a template.
search::SingleBest single_best_;
// ProcessSentence returns a reference to a vector. ProcessSentence
// doesn't have one, so this is populated and returned.
std::vector<search::Applied> backing_for_single_;
search::NBest n_best_;
const std::vector<search::Applied> *completed_nbest_;
};
// Just get the phrase.
void ToPhrase(const search::Applied final, Phrase &out);
// Get the phrase and the features.
void PhraseAndFeatures(const search::Applied final, Phrase &phrase, ScoreComponentCollection &features);
} // namespace Incremental
} // namespace Moses
|
