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#ifndef _POISSON_UNIFORM_WORD_MODEL_H_
#define _POISSON_UNIFORM_WORD_MODEL_H_
#include <cmath>
#include <vector>
#include "prob.h"
#include "m.h"
// len ~ Poisson(lambda)
// for (1..len)
// e_i ~ Uniform({Vocabulary})
struct PoissonUniformWordModel {
explicit PoissonUniformWordModel(const unsigned vocab_size,
const unsigned alphabet_size,
const double mean_len = 5) :
lh(prob_t::One()),
v0(-std::log(vocab_size)),
u0(-std::log(alphabet_size)),
mean_length(mean_len) {}
void ResampleHyperparameters(MT19937*) {}
inline prob_t operator()(const std::vector<WordID>& s) const {
prob_t p;
p.logeq(Md::log_poisson(s.size(), mean_length) + s.size() * u0);
//p.logeq(v0);
return p;
}
inline void Increment(const std::vector<WordID>& w, MT19937*) {
lh *= (*this)(w);
}
inline void Decrement(const std::vector<WordID>& w, MT19937 *) {
lh /= (*this)(w);
}
inline prob_t Likelihood() const { return lh; }
void Summary() const {}
private:
prob_t lh; // keeps track of the draws from the base distribution
const double v0; // uniform log prob of generating a word
const double u0; // uniform log prob of generating a letter
const double mean_length; // mean length of a word in the base distribution
};
#endif
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