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author | Avneesh Saluja <asaluja@gmail.com> | 2013-03-28 18:28:16 -0700 |
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committer | Avneesh Saluja <asaluja@gmail.com> | 2013-03-28 18:28:16 -0700 |
commit | 3d8d656fa7911524e0e6885647173474524e0784 (patch) | |
tree | 81b1ee2fcb67980376d03f0aa48e42e53abff222 /gi/pf/pyp_tm.h | |
parent | be7f57fdd484e063775d7abf083b9fa4c403b610 (diff) | |
parent | 96fedabebafe7a38a6d5928be8fff767e411d705 (diff) |
fixed conflicts
Diffstat (limited to 'gi/pf/pyp_tm.h')
-rw-r--r-- | gi/pf/pyp_tm.h | 36 |
1 files changed, 0 insertions, 36 deletions
diff --git a/gi/pf/pyp_tm.h b/gi/pf/pyp_tm.h deleted file mode 100644 index 2b076a25..00000000 --- a/gi/pf/pyp_tm.h +++ /dev/null @@ -1,36 +0,0 @@ -#ifndef PYP_LEX_TRANS -#define PYP_LEX_TRANS - -#include <vector> -#include "wordid.h" -#include "prob.h" -#include "sampler.h" -#include "freqdict.h" -#include "poisson_uniform_word_model.h" - -struct FreqBinner; -template <typename T, class B> struct ConditionalPYPWordModel; - -struct PYPLexicalTranslation { - explicit PYPLexicalTranslation(const std::vector<std::vector<WordID> >& lets, - const unsigned vocab_size, - const unsigned num_letters); - - prob_t Likelihood() const; - - void ResampleHyperparameters(MT19937* rng); - prob_t Prob(WordID src, WordID trg) const; // return p(trg | src) - void Summary() const; - void Increment(WordID src, WordID trg, MT19937* rng); - void Decrement(WordID src, WordID trg, MT19937* rng); - unsigned UniqueConditioningContexts() const; - - private: - const std::vector<std::vector<WordID> >& letters; // spelling dictionary - PoissonUniformWordModel base; // "generator" of English types - ConditionalPYPWordModel<PoissonUniformWordModel, FreqBinner>* tmodel; // translation distributions - // (model English word | French word) - const WordID kX; -}; - -#endif |