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#ifndef _UNIGRAMS_H_
#define _UNIGRAMS_H_
#include <vector>
#include <string>
#include <tr1/unordered_map>
#include <boost/functional.hpp>
#include "wordid.h"
#include "prob.h"
#include "tdict.h"
struct UnigramModel {
explicit UnigramModel(const std::string& fname, unsigned vocab_size) :
use_uniform_(fname.size() == 0),
uniform_(1.0 / vocab_size),
probs_() {
if (fname.size() > 0) {
probs_.resize(TD::NumWords() + 1);
LoadUnigrams(fname);
}
}
const prob_t& operator()(const WordID& w) const {
assert(w);
if (use_uniform_) return uniform_;
return probs_[w];
}
private:
void LoadUnigrams(const std::string& fname);
const bool use_uniform_;
const prob_t uniform_;
std::vector<prob_t> probs_;
};
// reads an ARPA unigram file and converts words like 'cat' into a string 'c a t'
struct UnigramWordModel {
explicit UnigramWordModel(const std::string& fname) :
use_uniform_(false),
uniform_(1.0),
probs_() {
LoadUnigrams(fname);
}
explicit UnigramWordModel(const unsigned vocab_size) :
use_uniform_(true),
uniform_(1.0 / vocab_size),
probs_() {}
const prob_t& operator()(const std::vector<WordID>& s) const {
if (use_uniform_) return uniform_;
const VectorProbHash::const_iterator it = probs_.find(s);
assert(it != probs_.end());
return it->second;
}
private:
void LoadUnigrams(const std::string& fname);
const bool use_uniform_;
const prob_t uniform_;
typedef std::tr1::unordered_map<std::vector<WordID>, prob_t, boost::hash<std::vector<WordID> > > VectorProbHash;
VectorProbHash probs_;
};
#endif
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