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Adding unit tests to Backward LM
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@ -115,7 +115,7 @@ project : requirements
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;
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#Add directories here if you want their incidental targets too (i.e. tests).
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build-projects lm util phrase-extract search moses mert moses-cmd moses-chart-cmd mira scripts regression-testing ;
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build-projects lm util phrase-extract search moses moses/LM mert moses-cmd moses-chart-cmd mira scripts regression-testing ;
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alias programs : lm//programs moses-chart-cmd//moses_chart moses-cmd//programs OnDiskPt//CreateOnDiskPt OnDiskPt//queryOnDiskPt mert//programs misc//programs symal phrase-extract phrase-extract//lexical-reordering phrase-extract//extract-ghkm phrase-extract//pcfg-extract phrase-extract//pcfg-score biconcor mira//mira contrib/server//mosesserver ;
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@ -25,33 +25,35 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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#include "lm/model.hh"
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#include "moses/FFState.h"
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#include "moses/Hypothesis.h"
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#include "moses/Phrase.h"
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#include "moses/LM/Ken.h"
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#include "moses/LM/Backward.h"
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//#include <iostream>
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namespace Moses {
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// By placing BackwardLMState inside an anonymous namespace,
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// it is visible *only* within this file
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namespace {
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struct BackwardLMState : public FFState {
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lm::ngram::ChartState state;
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int Compare(const FFState &o) const {
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const BackwardLMState &other = static_cast<const BackwardLMState &>(o);
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return state.left.Compare(other.state.left);
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}
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};
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}
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/** Constructs a new backward language model. */
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template <class Model> BackwardLanguageModel<Model>::BackwardLanguageModel(const std::string &file, FactorType factorType, bool lazy) : LanguageModelKen<Model>(file,factorType,lazy) {
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//
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// This space intentionally left blank
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//
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}
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/**
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* Constructs an empty backward language model state.
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*
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* This state will correspond with a translation hypothesis
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* where no source words have been translated.
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*
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* In a forward language model, the language model state of an empty hypothesis
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* would store the beginning of sentence marker <s>.
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*
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* Because this is a backward language model, the language model state returned by this method
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* instead stores the end of sentence marker </s>.
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*/
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template <class Model> const FFState *BackwardLanguageModel<Model>::EmptyHypothesisState(const InputType &/*input*/) const {
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BackwardLMState *ret = new BackwardLMState();
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lm::ngram::RuleScore<Model> ruleScore(*m_ngram, ret->state);
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@ -59,7 +61,56 @@ namespace Moses {
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ruleScore.Finish();
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return ret;
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}
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/*
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template <class Model> double BackwardLanguageModel<Model>::Score(FFState *ffState) {
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BackwardLMState *lmState = static_cast< BackwardLMState* >(ffState);
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lm::ngram::ChartState &state = lmState->state;
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lm::ngram::RuleScore<Model> ruleScore(*m_ngram, lmState);
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return ruleScore.Finish();
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}
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*/
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/**
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* Pre-calculate the n-gram probabilities for the words in the specified phrase.
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*
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* Note that when this method is called, we do not have access to the context
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* in which this phrase will eventually be applied.
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*
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* In other words, we know what words are in this phrase,
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* but we do not know what words will come before or after this phrase.
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*
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* The parameters fullScore, ngramScore, and oovCount are all output parameters.
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*
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* The value stored in oovCount is the number of words in the phrase
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* that are not in the language model's vocabulary.
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*
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* The sum of the ngram scores for all words in this phrase are stored in fullScore.
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*
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* The value stored in ngramScore is similar, but only full-order ngram scores are included.
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*
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* This is best shown by example:
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*
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* Assume a trigram backward language model and a phrase "a b c d e f g"
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*
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* fullScore would represent the sum of the logprob scores for the following values:
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*
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* p(g)
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* p(f | g)
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* p(e | g f)
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* p(d | f e)
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* p(c | e d)
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* p(b | d c)
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* p(a | c b)
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*
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* ngramScore would represent the sum of the logprob scores for the following values:
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*
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* p(g)
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* p(f | g)
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* p(e | g f)
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* p(d | f e)
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* p(c | e d)
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* p(b | d c)
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* p(a | c b)
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*/
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template <class Model> void BackwardLanguageModel<Model>::CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, size_t &oovCount) const {
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fullScore = 0;
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ngramScore = 0;
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@ -77,7 +128,35 @@ namespace Moses {
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);
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float before_boundary = 0.0f;
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for (size_t position = phrase.GetSize() - 1,
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int lastWord = phrase.GetSize() - 1;
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int ngramBoundary = m_ngram->Order() - 1;
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int boundary = ( lastWord < ngramBoundary ) ? 0 : ngramBoundary;
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int position;
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for (position = lastWord; position >= 0; position-=1) {
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const Word &word = phrase.GetWord(position);
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UTIL_THROW_IF(
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(word.IsNonTerminal()),
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util::Exception,
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"BackwardLanguageModel does not currently support rules that include non-terminals "
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);
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lm::WordIndex index = TranslateID(word);
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scorer.Terminal(index);
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if (!index) ++oovCount;
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if (position==boundary) {
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before_boundary = scorer.Finish();
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}
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}
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/*
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before_boundary = scorer.Finish();
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for (int position = phrase.GetSize() - 1,
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ngramBoundary = m_ngram->Order() - 1; position >= 0; position-=1) {
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const Word &word = phrase.GetWord(position);
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@ -85,7 +164,7 @@ namespace Moses {
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UTIL_THROW_IF(
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(word.IsNonTerminal()),
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util::Exception,
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"BackwardLanguageModel does not currently support rules that include non-terminals"
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"BackwardLanguageModel does not currently support rules that include non-terminals "
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);
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lm::WordIndex index = TranslateID(word);
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@ -97,14 +176,90 @@ namespace Moses {
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}
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}
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fullScore += scorer.Finish();
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*/
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fullScore = scorer.Finish();
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ngramScore = TransformLMScore(fullScore - before_boundary);
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fullScore = TransformLMScore(fullScore);
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}
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/**
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* Calculate the ngram probabilities for the words at the beginning
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* (and under some circumstances, also at the end)
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* of the phrase represented by the provided hypothesis.
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*
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* Additionally, calculate a new language model state.
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*
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* This is best shown by example:
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*
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* Assume a trigram language model.
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*
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* Assume the previous phrase was "a b c d e f g",
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* which means the previous language model state is "g f".
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*
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* When the phrase corresponding to "a b c d e f g" was previously processed by CalcScore
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* the following full-order ngrams would have been calculated:
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*
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* p(a | c b)
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* p(b | d c)
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* p(c | e d)
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* p(d | f e)
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* p(e | g f)
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*
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* The following less-than-full-order ngrams would also have been calculated by CalcScore:
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*
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* p(f | g)
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* p(g)
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*
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* In this method, we now have access to additional context which may allow
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* us to compute the full-order ngrams for f and g.
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*
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* Assume the new provided hypothesis contains the new phrase "h i j k"
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*
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* Given these assumptions, this method is responsible
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* for calculating the scores for the following:
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*
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* p(f | h g)
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* p(g | i h)
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*
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* This method must also calculate and return a new language model state.
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*
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* In this example, the returned language model state would be "k j"
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*
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* If the provided hypothesis represents the end of a completed translation
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* (all source words have been translated)
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* then this method is additionally responsible for calculating the following:
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*
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* p(j | <s> k)
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* p(k | <s>)
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*
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*/
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template <class Model> FFState *BackwardLanguageModel<Model>::Evaluate(const Hypothesis &hypo, const FFState *ps, ScoreComponentCollection *out) const {
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const lm::ngram::ChartState &in_state = static_cast<const BackwardLMState&>(*ps).state;
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std::auto_ptr<BackwardLMState> ret(new BackwardLMState());
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// If the current hypothesis contains zero target words
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if (!hypo.GetCurrTargetLength()) {
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// reuse and return the previous state
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ret->state = in_state;
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return ret.release();
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}
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UTIL_THROW_IF(
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(1==1),
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util::Exception,
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"This method (BackwardLanguageModel<Model>::Evaluate) is not yet fully implemented"
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);
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return ret.release();
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}
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LanguageModel *ConstructBackwardLM(const std::string &file, FactorType factorType, bool lazy) {
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try {
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lm::ngram::ModelType model_type;
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@ -25,12 +25,19 @@ Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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#include <string>
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#include "moses/LM/Ken.h"
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#include "moses/LM/BackwardLMState.h"
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#include "lm/state.hh"
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namespace Moses {
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//! This will also load. Returns a templated backward LM.
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LanguageModel *ConstructBackwardLM(const std::string &file, FactorType factorType, bool lazy);
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class FFState;
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// template<typename M> class BackwardLanguageModelTest;
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class BackwardLanguageModelTest;
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/*
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* An implementation of single factor backward LM using Kenneth's code.
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*/
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@ -42,6 +49,8 @@ template <class Model> class BackwardLanguageModel : public LanguageModelKen<Mod
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virtual void CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, size_t &oovCount) const;
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virtual FFState *Evaluate(const Hypothesis &hypo, const FFState *ps, ScoreComponentCollection *out) const;
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private:
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// These lines are required to make the parent class's protected members visible to this class
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@ -50,6 +59,21 @@ template <class Model> class BackwardLanguageModel : public LanguageModelKen<Mod
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using LanguageModelKen<Model>::m_factorType;
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using LanguageModelKen<Model>::TranslateID;
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// friend class Moses::BackwardLanguageModelTest<Model>;
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friend class Moses::BackwardLanguageModelTest;
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/*
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lm::ngram::ChartState* GetState(FFState *ffState) {
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return NULL;
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}
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*/
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/*
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double Score(FFState *ffState) {
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BackwardLMState *lmState = static_cast< BackwardLMState* >(ffState);
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lm::ngram::ChartState &state = lmState->state;
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lm::ngram::RuleScore<Model> ruleScore(*m_ngram, lmState);
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return ruleScore.Finish();
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}
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*/
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};
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} // namespace Moses
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32
moses/LM/BackwardLMState.cpp
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32
moses/LM/BackwardLMState.cpp
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@ -0,0 +1,32 @@
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// $Id$
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/***********************************************************************
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Moses - factored phrase-based language decoder
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Copyright (C) 2006 University of Edinburgh
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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***********************************************************************/
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#include "moses/LM/BackwardLMState.h"
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#include "lm/state.hh"
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namespace Moses {
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int BackwardLMState::Compare(const FFState &o) const {
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const BackwardLMState &other = static_cast<const BackwardLMState &>(o);
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return state.left.Compare(other.state.left);
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}
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}
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69
moses/LM/BackwardLMState.h
Normal file
69
moses/LM/BackwardLMState.h
Normal file
@ -0,0 +1,69 @@
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// $Id$
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/***********************************************************************
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Moses - factored phrase-based language decoder
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Copyright (C) 2006 University of Edinburgh
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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***********************************************************************/
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#ifndef moses_BackwardLMState_h
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#define moses_BackwardLMState_h
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#include "moses/FFState.h"
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#include "moses/LM/Backward.h"
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#include "lm/state.hh"
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/*
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namespace lm {
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namespace ngram {
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class ChartState;
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}
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}
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*/
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//#include "lm/state.hh"
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namespace Moses {
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//template<typename M>
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class BackwardLanguageModelTest;
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class BackwardLMState : public FFState {
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public:
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/*
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int Compare(const FFState &o) const {
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const BackwardLMState &other = static_cast<const BackwardLMState &>(o);
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return state.left.Compare(other.state.left);
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}
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*/
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int Compare(const FFState &o) const;
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// Allow BackwardLanguageModel to access the private members of this class
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template <class Model> friend class BackwardLanguageModel;
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// template <class Model> friend class Moses::BackwardLanguageModelTest;
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friend class Moses::BackwardLanguageModelTest;
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private:
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lm::ngram::ChartState state;
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};
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}
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#endif
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190
moses/LM/BackwardTest.cpp
Normal file
190
moses/LM/BackwardTest.cpp
Normal file
@ -0,0 +1,190 @@
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/***********************************************************************
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Moses - factored phrase-based language decoder
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Copyright (C) 2010 University of Edinburgh
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This library is free software; you can redistribute it and/or
|
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modify it under the terms of the GNU Lesser General Public
|
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License as published by the Free Software Foundation; either
|
||||
version 2.1 of the License, or (at your option) any later version.
|
||||
|
||||
This library is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
||||
Lesser General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU Lesser General Public
|
||||
License along with this library; if not, write to the Free Software
|
||||
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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***********************************************************************/
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#define BOOST_TEST_MODULE BackwardTest
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#include <boost/test/unit_test.hpp>
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#include "lm/config.hh"
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#include "lm/left.hh"
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#include "lm/model.hh"
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#include "lm/state.hh"
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#include "moses/Sentence.h"
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#include "moses/TypeDef.h"
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#include "moses/StaticData.h"
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//#include "BackwardLMState.h"
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#include "moses/LM/Backward.h"
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#include "moses/LM/BackwardLMState.h"
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#include "moses/Util.h"
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#include "lm/state.hh"
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#include "lm/left.hh"
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#include <vector>
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using namespace Moses;
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//using namespace std;
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/*
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template <class M> void Foo() {
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Moses::BackwardLanguageModel<M> *backwardLM;
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// = new Moses::BackwardLanguageModel<M>( filename, factorType, lazy );
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}
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template <class M> void Everything() {
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// Foo<M>();
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}
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*/
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namespace Moses {
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// Apparently some Boost versions use templates and are pretty strict about types matching.
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#define SLOPPY_CHECK_CLOSE(ref, value, tol) BOOST_CHECK_CLOSE(static_cast<double>(ref), static_cast<double>(value), static_cast<double>(tol));
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class BackwardLanguageModelTest {
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public:
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BackwardLanguageModelTest() :
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dummyInput(new Sentence()),
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backwardLM(
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// BackwardLanguageModel
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// new Moses::BackwardLanguageModel<Model>(
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ConstructBackwardLM(
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boost::unit_test::framework::master_test_suite().argv[1],
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0,
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false)
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)
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||||
{
|
||||
// This space intentionally left blank
|
||||
}
|
||||
|
||||
~BackwardLanguageModelTest() {
|
||||
delete dummyInput;
|
||||
delete backwardLM;
|
||||
}
|
||||
|
||||
void testEmptyHypothesis() {
|
||||
FFState *ffState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput ));
|
||||
|
||||
BOOST_CHECK( ffState != NULL );
|
||||
/*
|
||||
// lm::ngram::ChartState &state = static_cast< const BackwardLMState >(*ffState).state;
|
||||
BackwardLMState *lmState = static_cast< BackwardLMState* >(ffState);
|
||||
//const lm::ngram::ChartState &state = static_cast< const BackwardLMState* >(ffState)->state;
|
||||
//lm::ngram::ChartState &state = lmState->state;
|
||||
|
||||
// BOOST_CHECK( state.left.length == 1 );
|
||||
// BOOST_CHECK( state.right.Length() == 0 );
|
||||
|
||||
BackwardLanguageModel<lm::ngram::ProbingModel> *lm = static_cast< BackwardLanguageModel<lm::ngram::ProbingModel> *>(backwardLM);
|
||||
lm::ngram::ChartState &state = lmState->state;
|
||||
lm::ngram::RuleScore<lm::ngram::ProbingModel> ruleScore(*(lm->m_ngram), state);
|
||||
double score = ruleScore.Finish();
|
||||
SLOPPY_CHECK_CLOSE(-1.457693, score, 0.001);
|
||||
*/
|
||||
delete ffState;
|
||||
}
|
||||
|
||||
void testCalcScore() {
|
||||
//std::vector<WordIndex> words
|
||||
|
||||
Phrase phrase;
|
||||
BOOST_CHECK( phrase.GetSize() == 0 );
|
||||
|
||||
std::vector<FactorType> outputFactorOrder;
|
||||
outputFactorOrder.push_back(0);
|
||||
|
||||
phrase.CreateFromString(
|
||||
//StaticData::Instance().GetOutputFactorOrder(),
|
||||
outputFactorOrder,
|
||||
"the",
|
||||
StaticData::Instance().GetFactorDelimiter());
|
||||
|
||||
BOOST_CHECK( phrase.GetSize() == 1 );
|
||||
|
||||
// BackwardLanguageModel<lm::ngram::ProbingModel> *lm = static_cast< BackwardLanguageModel<lm::ngram::ProbingModel> *>(backwardLM);
|
||||
|
||||
//Word &word = phrase.GetWord(0);
|
||||
//Word
|
||||
// BOOST_CHECK( word == lm->m_ngram->GetVocabulary().Index("the") );
|
||||
|
||||
|
||||
|
||||
float fullScore;
|
||||
float ngramScore;
|
||||
size_t oovCount;
|
||||
backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);
|
||||
|
||||
BOOST_CHECK( oovCount == 0 );
|
||||
SLOPPY_CHECK_CLOSE( TransformLMScore(-1.383059), fullScore, 0.01);
|
||||
SLOPPY_CHECK_CLOSE( TransformLMScore( 0.0 ), ngramScore, 0.01);
|
||||
|
||||
}
|
||||
|
||||
private:
|
||||
const Sentence *dummyInput;
|
||||
// BackwardLanguageModel<Model> *backwardLM;
|
||||
LanguageModel *backwardLM;
|
||||
/*
|
||||
void LookupVocab(const StringPiece &str, std::vector<WordIndex *> &out) {
|
||||
|
||||
out.clear();
|
||||
for (util::TokenIter<util::SingleCharacter, true> i(str, ' '); i; ++i) {
|
||||
out.push_back(lm->m_ngram.GetVocabulary().Index(*i));
|
||||
}
|
||||
}
|
||||
*/
|
||||
};
|
||||
|
||||
|
||||
}
|
||||
|
||||
const char *FileLocation() {
|
||||
if (boost::unit_test::framework::master_test_suite().argc < 2) {
|
||||
BOOST_FAIL("Jamfile must specify arpa file for this test, but did not");
|
||||
}
|
||||
return boost::unit_test::framework::master_test_suite().argv[1];
|
||||
}
|
||||
|
||||
BOOST_AUTO_TEST_CASE(ProbingAll) {
|
||||
// Everything<lm::ngram::Model>();
|
||||
/*
|
||||
const std::string filename( boost::unit_test::framework::master_test_suite().argv[1] );
|
||||
size_t factorType = 0;
|
||||
bool lazy = false;
|
||||
|
||||
LanguageModel *backwardLM = ConstructBackwardLM( filename, factorType, lazy );
|
||||
const Sentence *dummyInput = new Sentence();
|
||||
|
||||
const FFState *ffState = backwardLM->EmptyHypothesisState( *dummyInput );
|
||||
|
||||
//new BackwardLanguageModel<lm::ngram::Model>( filename, factorType, lazy );
|
||||
|
||||
delete dummyInput;
|
||||
delete backwardLM;
|
||||
*/
|
||||
//BackwardLanguageModelTest<lm::ngram::TrieModel> test;
|
||||
BackwardLanguageModelTest test;
|
||||
test.testEmptyHypothesis();
|
||||
test.testCalcScore();
|
||||
// test->testEmptyHypothesis();
|
||||
}
|
@ -88,11 +88,15 @@ if $(with-ldhtlm) {
|
||||
obj ORLM.o : ORLM.cpp ..//headers ../TranslationModel/DynSAInclude//dynsa : : : <include>../TranslationModel/DynSAInclude ;
|
||||
|
||||
#The factory needs the macros LM_IRST etc to know which ones to use.
|
||||
obj Factory.o : Factory.cpp ..//headers $(dependencies) : <include>../DynSAInclude <dependency>$(LM-LOG) ;
|
||||
obj Factory.o : Factory.cpp ..//headers $(dependencies) ../../lm//kenlm : <include>../DynSAInclude <dependency>$(LM-LOG) ;
|
||||
|
||||
#Top-level LM library. If you've added a file that doesn't depend on external
|
||||
#libraries, put it here.
|
||||
alias LM : Backward.cpp Base.cpp Factory.o Implementation.cpp Joint.cpp Ken.cpp MultiFactor.cpp Remote.cpp SingleFactor.cpp ORLM.o
|
||||
alias LM : Backward.cpp BackwardLMState.cpp Base.cpp Factory.o Implementation.cpp Joint.cpp Ken.cpp MultiFactor.cpp Remote.cpp SingleFactor.cpp ORLM.o
|
||||
../../lm//kenlm ..//headers $(dependencies) ;
|
||||
|
||||
import testing ;
|
||||
|
||||
#unit-test moses_lm_test : [ glob *Test.cpp ] ..//moses LM /top//boost_unit_test_framework ;
|
||||
|
||||
run BackwardTest.cpp ..//moses LM ../../lm//kenlm /top//boost_unit_test_framework : : backward.arpa ;
|
@ -160,6 +160,46 @@ template <class Model> LanguageModelKen<Model>::LanguageModelKen(const LanguageM
|
||||
m_lmIdLookup(copy_from.m_lmIdLookup) {
|
||||
}
|
||||
|
||||
/**
|
||||
* Pre-calculate the n-gram probabilities for the words in the specified phrase.
|
||||
*
|
||||
* Note that when this method is called, we do not have access to the context
|
||||
* in which this phrase will eventually be applied.
|
||||
*
|
||||
* In other words, we know what words are in this phrase,
|
||||
* but we do not know what words will come before or after this phrase.
|
||||
*
|
||||
* The parameters fullScore, ngramScore, and oovCount are all output parameters.
|
||||
*
|
||||
* The value stored in oovCount is the number of words in the phrase
|
||||
* that are not in the language model's vocabulary.
|
||||
*
|
||||
* The sum of the ngram scores for all words in this phrase are stored in fullScore.
|
||||
*
|
||||
* The value stored in ngramScore is similar, but only full-order ngram scores are included.
|
||||
*
|
||||
* This is best shown by example:
|
||||
*
|
||||
* Assume a trigram language model and a phrase "a b c d e f g"
|
||||
*
|
||||
* fullScore would represent the sum of the logprob scores for the following values:
|
||||
*
|
||||
* p(a)
|
||||
* p(b | a)
|
||||
* p(c | a b)
|
||||
* p(d | b c)
|
||||
* p(e | c d)
|
||||
* p(f | d e)
|
||||
* p(g | e f)
|
||||
*
|
||||
* ngramScore would represent the sum of the logprob scores for the following values:
|
||||
*
|
||||
* p(c | a b)
|
||||
* p(d | b c)
|
||||
* p(e | c d)
|
||||
* p(f | d e)
|
||||
* p(g | e f)
|
||||
*/
|
||||
template <class Model> void LanguageModelKen<Model>::CalcScore(const Phrase &phrase, float &fullScore, float &ngramScore, size_t &oovCount) const {
|
||||
fullScore = 0;
|
||||
ngramScore = 0;
|
||||
@ -210,6 +250,39 @@ template <class Model> void LanguageModelKen<Model>::CalcScore(const Phrase &phr
|
||||
fullScore = TransformLMScore(fullScore);
|
||||
}
|
||||
|
||||
/**
|
||||
* Calculate the ngram probabilities for the words at the beginning
|
||||
* (and under some circumstances, also at the end)
|
||||
* of the phrase represented by the provided hypothesis.
|
||||
*
|
||||
* Additionally, calculate a new language model state.
|
||||
*
|
||||
* This is best shown by example:
|
||||
*
|
||||
* Assume a trigram language model.
|
||||
*
|
||||
* Assume the previous phrase was "w x y z",
|
||||
* which means the previous language model state is "y z".
|
||||
*
|
||||
* Assume the provided hypothesis contains the new phrase "a b c d e f g"
|
||||
*
|
||||
* Given these assumptions, this method is responsible
|
||||
* for calculating the scores for the following:
|
||||
*
|
||||
* p(a | y z)
|
||||
* p(b | z a)
|
||||
*
|
||||
* This method must also calculate and return a new language model state.
|
||||
*
|
||||
* In this example, the returned language model state would be "f g"
|
||||
*
|
||||
* If the provided hypothesis represents the end of a completed translation
|
||||
* (all source words have been translated)
|
||||
* then this method is additionally responsible for calculating the following:
|
||||
*
|
||||
* p(</s> | f g)
|
||||
*
|
||||
*/
|
||||
template <class Model> FFState *LanguageModelKen<Model>::Evaluate(const Hypothesis &hypo, const FFState *ps, ScoreComponentCollection *out) const {
|
||||
const lm::ngram::State &in_state = static_cast<const KenLMState&>(*ps).state;
|
||||
|
||||
|
566
moses/LM/backward.arpa
Normal file
566
moses/LM/backward.arpa
Normal file
@ -0,0 +1,566 @@
|
||||
|
||||
\data\
|
||||
ngram 1=167
|
||||
ngram 2=361
|
||||
ngram 3=25
|
||||
|
||||
\1-grams:
|
||||
-2.059753 ' -0.1382608
|
||||
-2.184691 ( -0.08246645
|
||||
-2.184691 ) -0.1039416
|
||||
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|
||||
-1.457693 . -0.07898764
|
||||
-2.661813 / -0.09528423
|
||||
-2.661813 1 -0.1039416
|
||||
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|
||||
-2.360783 : -0.09722306
|
||||
-2.661813 ; -0.09625472
|
||||
-1.457693 </s>
|
||||
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|
||||
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|
||||
-2.360783 all -0.09431157
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
|
||||
\2-grams:
|
||||
-0.7536553 ' authors -0.04826907
|
||||
-1.263617 ' developers
|
||||
-1.263617 ' users
|
||||
-1.138679 ( :
|
||||
-1.138679 ( and
|
||||
-1.138679 ( software
|
||||
-1.138679 ) 1
|
||||
-1.138679 ) 2
|
||||
-1.138679 ) wish
|
||||
-2.041769 , )
|
||||
-2.041769 , changed
|
||||
-2.041769 , contrast
|
||||
-2.041769 , copy
|
||||
-2.041769 , document
|
||||
-2.041769 , example
|
||||
-2.041769 , fee
|
||||
-2.041769 , foundation
|
||||
-2.041769 , free
|
||||
-2.041769 , freedom
|
||||
-2.041769 , it
|
||||
-2.041769 , program
|
||||
-1.531807 , programs
|
||||
-2.041769 , protection
|
||||
-2.041769 , rights
|
||||
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\end\
|
Loading…
Reference in New Issue
Block a user