mirror of
https://github.com/moses-smt/mosesdecoder.git
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249c40ec74
Phrase.CreateFromString() and Sentence.CreateFromString(), as it was never used in those functions anyway --- Word.CreateFromString() retrieves the factor delimiter from StaticData directly.
381 lines
9.6 KiB
C++
381 lines
9.6 KiB
C++
/***********************************************************************
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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
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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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#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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{
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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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{
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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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static_cast< BackwardLanguageModel<lm::ngram::ProbingModel> * >(
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ConstructBackwardLM(
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"LM1=1.0",
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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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) {
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// This space intentionally left blank
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}
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~BackwardLanguageModelTest() {
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delete dummyInput;
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delete backwardLM;
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}
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void testEmptyHypothesis() {
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FFState *ffState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput ));
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BOOST_CHECK( ffState != NULL );
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delete ffState;
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}
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void testCalcScore() {
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double p_the = -1.383059;
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double p_licenses = -2.360783;
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double p_for = -1.661813;
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double p_most = -2.360783;
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// double p_software = -1.62042;
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double p_the_licenses = -0.9625873;
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double p_licenses_for = -1.661557;
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double p_for_most = -0.4526253;
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// double p_most_software = -1.70295;
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double p_the_licenses_for = p_the_licenses + p_licenses_for;
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// double p_licenses_for_most = p_licenses_for + p_for_most;
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// the
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"the",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 1 );
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float fullScore;
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float ngramScore;
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size_t oovCount;
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backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);
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BOOST_CHECK( oovCount == 0 );
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SLOPPY_CHECK_CLOSE( TransformLMScore(p_the), fullScore, 0.01);
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SLOPPY_CHECK_CLOSE( TransformLMScore( 0.0 ), ngramScore, 0.01);
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}
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// the licenses
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"the licenses",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 2 );
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float fullScore;
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float ngramScore;
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size_t oovCount;
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backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);
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BOOST_CHECK( oovCount == 0 );
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SLOPPY_CHECK_CLOSE( TransformLMScore(p_licenses + p_the_licenses), fullScore, 0.01);
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// Check ngramScore is 0.0
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BOOST_CHECK_GT(0.0001, ngramScore);
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BOOST_CHECK_LT(-0.0001, ngramScore);
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}
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// the licenses for
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"the licenses for",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 3 );
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float fullScore;
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float ngramScore;
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size_t oovCount;
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backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);
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BOOST_CHECK( oovCount == 0 );
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SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses_for ), ngramScore, 0.01);
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SLOPPY_CHECK_CLOSE( TransformLMScore(p_for + p_licenses_for + p_the_licenses), fullScore, 0.01);
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}
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// the licenses for most
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"the licenses for most",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 4 );
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float fullScore;
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float ngramScore;
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size_t oovCount;
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backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount);
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BOOST_CHECK( oovCount == 0 );
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SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses + p_licenses_for ), ngramScore, 0.01);
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SLOPPY_CHECK_CLOSE( TransformLMScore(p_most + p_for_most + p_licenses_for + p_the_licenses), fullScore, 0.01);
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}
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}
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void testEvaluate() {
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FFState *nextState;
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FFState *prevState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput ));
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double p_most = -2.360783;
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double p_for = -1.661813;
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double p_licenses = -2.360783;
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double p_the = -1.383059;
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double p_eos = -1.457693;
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double p_most_for = -0.4526253;
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double p_for_licenses = -1.661557;
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double p_licenses_the = -0.9625873;
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double p_the_eos = -1.940311;
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// the
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"the",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 1 );
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float score;
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nextState = backwardLM->Evaluate(phrase, prevState, score);
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// p(the) * p(</s> | the) / p(</s>)
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SLOPPY_CHECK_CLOSE( (p_the + p_the_eos - p_eos), score, 0.01);
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delete prevState;
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prevState = nextState;
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}
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// the licenses
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"licenses",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 1 );
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float score;
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nextState = backwardLM->Evaluate(phrase, prevState, score);
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// p(licenses) * p(licenses | the) / p(the)
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SLOPPY_CHECK_CLOSE( (p_licenses + p_licenses_the - p_the), score, 0.01);
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delete prevState;
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prevState = nextState;
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}
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// the licenses for
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"for",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 1 );
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float score;
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nextState = backwardLM->Evaluate(phrase, prevState, score);
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// p(for) * p(for | licenses) / p(licenses)
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SLOPPY_CHECK_CLOSE( (p_for + p_for_licenses - p_licenses), score, 0.01);
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delete prevState;
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prevState = nextState;
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}
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// the licenses for most
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{
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Phrase phrase;
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BOOST_CHECK( phrase.GetSize() == 0 );
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std::vector<FactorType> outputFactorOrder;
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outputFactorOrder.push_back(0);
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phrase.CreateFromString(
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Input,
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outputFactorOrder,
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"most",
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// StaticData::Instance().GetFactorDelimiter(),
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NULL);
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BOOST_CHECK( phrase.GetSize() == 1 );
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float score;
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nextState = backwardLM->Evaluate(phrase, prevState, score);
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// p(most) * p(most | for) / p(for)
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SLOPPY_CHECK_CLOSE( (p_most + p_most_for - p_for), score, 0.01);
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delete prevState;
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prevState = nextState;
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}
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delete prevState;
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}
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private:
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const Sentence *dummyInput;
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BackwardLanguageModel<lm::ngram::ProbingModel> *backwardLM;
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};
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}
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const char *FileLocation()
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{
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if (boost::unit_test::framework::master_test_suite().argc < 2) {
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BOOST_FAIL("Jamfile must specify arpa file for this test, but did not");
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}
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return boost::unit_test::framework::master_test_suite().argv[1];
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}
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BOOST_AUTO_TEST_CASE(ProbingAll)
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{
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BackwardLanguageModelTest test;
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test.testEmptyHypothesis();
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test.testCalcScore();
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test.testEvaluate();
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}
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