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
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
|
#ifndef _FF_H_
#define _FF_H_
#include <vector>
#include "fdict.h"
#include "hg.h"
class SentenceMetadata;
class FeatureFunction; // see definition below
// if you want to develop a new feature, inherit from this class and
// override TraversalFeaturesImpl(...). If it's a feature that returns /
// depends on context, you may also need to implement
// FinalTraversalFeatures(...)
class FeatureFunction {
public:
FeatureFunction() : state_size_() {}
explicit FeatureFunction(int state_size) : state_size_(state_size) {}
virtual ~FeatureFunction();
// override this. not virtual because we want to expose this to factory template for help before creating a FF
static std::string usage(bool show_params,bool show_details) {
return usage_helper("FIXME_feature_needs_name","[no parameters]","[no documentation yet]",show_params,show_details);
}
static std::string usage_helper(std::string const& name,std::string const& params,std::string const& details,bool show_params,bool show_details);
public:
typedef std::vector<WordID> Features;
virtual Features features() { return Features(); }
// returns the number of bytes of context that this feature function will
// (maximally) use. By default, 0 ("stateless" models in Hiero/Joshua).
// NOTE: this value is fixed for the instance of your class, you cannot
// use different amounts of memory for different nodes in the forest.
inline int NumBytesContext() const { return state_size_; }
// Compute the feature values and (if this applies) the estimates of the
// feature values when this edge is used incorporated into a larger context
inline void TraversalFeatures(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* out_state) const {
TraversalFeaturesImpl(smeta, edge, ant_contexts,
features, estimated_features, out_state);
// TODO it's easy for careless feature function developers to overwrite
// the end of their state and clobber someone else's memory. These bugs
// will be horrendously painful to track down. There should be some
// optional strict mode that's enforced here that adds some kind of
// barrier between the blocks reserved for the residual contexts
}
// if there's some state left when you transition to the goal state, score
// it here. For example, the language model computes the cost of adding
// <s> and </s>.
virtual void FinalTraversalFeatures(const void* residual_state,
SparseVector<double>* final_features) const;
protected:
// context is a pointer to a buffer of size NumBytesContext() that the
// feature function can write its state to. It's up to the feature function
// to determine how much space it needs and to determine how to encode its
// residual contextual information since it is OPAQUE to all clients outside
// of the particular FeatureFunction class. There is one exception:
// equality of the contents (i.e., memcmp) is required to determine whether
// two states can be combined.
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const = 0;
// !!! ONLY call this from subclass *CONSTRUCTORS* !!!
void SetStateSize(size_t state_size) {
state_size_ = state_size;
}
private:
int state_size_;
};
// word penalty feature, for each word on the E side of a rule,
// add value_
class WordPenalty : public FeatureFunction {
public:
WordPenalty(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
private:
const int fid_;
const double value_;
};
class SourceWordPenalty : public FeatureFunction {
public:
SourceWordPenalty(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
private:
const int fid_;
const double value_;
};
class ArityPenalty : public FeatureFunction {
public:
ArityPenalty(const std::string& param);
protected:
virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta,
const Hypergraph::Edge& edge,
const std::vector<const void*>& ant_contexts,
SparseVector<double>* features,
SparseVector<double>* estimated_features,
void* context) const;
private:
int fids_[10];
const double value_;
};
// this class is a set of FeatureFunctions that can be used to score, rescore,
// etc. a (translation?) forest
class ModelSet {
public:
ModelSet() : state_size_(0) {}
ModelSet(const std::vector<double>& weights,
const std::vector<const FeatureFunction*>& models);
// sets edge->feature_values_ and edge->edge_prob_
// NOTE: edge must not necessarily be in hg.edges_ but its TAIL nodes
// must be.
void AddFeaturesToEdge(const SentenceMetadata& smeta,
const Hypergraph& hg,
const std::vector<std::string>& node_states,
Hypergraph::Edge* edge,
std::string* residual_context,
prob_t* combination_cost_estimate = NULL) const;
void AddFinalFeatures(const std::string& residual_context,
Hypergraph::Edge* edge) const;
bool empty() const { return models_.empty(); }
private:
std::vector<const FeatureFunction*> models_;
std::vector<double> weights_;
int state_size_;
std::vector<int> model_state_pos_;
};
#endif
|
