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| /*********************************************************************** | |
| Moses - factored phrase-based language decoder | |
| Copyright (C) 2010 University of Edinburgh | |
| This library is free software; you can redistribute it and/or | |
| modify it under the terms of the GNU Lesser General Public | |
| 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 | |
| ***********************************************************************/ | |
| //#include "BackwardLMState.h" | |
| using namespace Moses; | |
| //using namespace std; | |
| /* | |
| template <class M> void Foo() { | |
| Moses::BackwardLanguageModel<M> *backwardLM; | |
| // = new Moses::BackwardLanguageModel<M>( filename, factorType, lazy ); | |
| } | |
| template <class M> void Everything() { | |
| // Foo<M>(); | |
| } | |
| */ | |
| namespace Moses | |
| { | |
| // Apparently some Boost versions use templates and are pretty strict about types matching. | |
| AllOptions::ptr DefaultOptions(new AllOptions); | |
| class BackwardLanguageModelTest | |
| { | |
| public: | |
| BackwardLanguageModelTest() : | |
| dummyInput(new Sentence(DefaultOptions)), | |
| backwardLM( | |
| static_cast< BackwardLanguageModel<lm::ngram::ProbingModel> * >( | |
| ConstructBackwardLM( | |
| "LM1=1.0", | |
| boost::unit_test::framework::master_test_suite().argv[1], | |
| 0, | |
| false) | |
| ) | |
| ) { | |
| // This space intentionally left blank | |
| } | |
| ~BackwardLanguageModelTest() { | |
| delete dummyInput; | |
| delete backwardLM; | |
| } | |
| void testEmptyHypothesis() { | |
| FFState *ffState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput )); | |
| BOOST_CHECK( ffState != NULL ); | |
| delete ffState; | |
| } | |
| void testCalcScore() { | |
| double p_the = -1.383059; | |
| double p_licenses = -2.360783; | |
| double p_for = -1.661813; | |
| double p_most = -2.360783; | |
| // double p_software = -1.62042; | |
| double p_the_licenses = -0.9625873; | |
| double p_licenses_for = -1.661557; | |
| double p_for_most = -0.4526253; | |
| // double p_most_software = -1.70295; | |
| double p_the_licenses_for = p_the_licenses + p_licenses_for; | |
| // double p_licenses_for_most = p_licenses_for + p_for_most; | |
| // the | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "the", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 1 ); | |
| float fullScore; | |
| float ngramScore; | |
| size_t oovCount; | |
| backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount); | |
| BOOST_CHECK( oovCount == 0 ); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore(p_the), fullScore, 0.01); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore( 0.0 ), ngramScore, 0.01); | |
| } | |
| // the licenses | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "the licenses", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 2 ); | |
| float fullScore; | |
| float ngramScore; | |
| size_t oovCount; | |
| backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount); | |
| BOOST_CHECK( oovCount == 0 ); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore(p_licenses + p_the_licenses), fullScore, 0.01); | |
| // Check ngramScore is 0.0 | |
| BOOST_CHECK_GT(0.0001, ngramScore); | |
| BOOST_CHECK_LT(-0.0001, ngramScore); | |
| } | |
| // the licenses for | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "the licenses for", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 3 ); | |
| float fullScore; | |
| float ngramScore; | |
| size_t oovCount; | |
| backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount); | |
| BOOST_CHECK( oovCount == 0 ); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses_for ), ngramScore, 0.01); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore(p_for + p_licenses_for + p_the_licenses), fullScore, 0.01); | |
| } | |
| // the licenses for most | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "the licenses for most", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 4 ); | |
| float fullScore; | |
| float ngramScore; | |
| size_t oovCount; | |
| backwardLM->CalcScore(phrase, fullScore, ngramScore, oovCount); | |
| BOOST_CHECK( oovCount == 0 ); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore( p_the_licenses + p_licenses_for ), ngramScore, 0.01); | |
| SLOPPY_CHECK_CLOSE( TransformLMScore(p_most + p_for_most + p_licenses_for + p_the_licenses), fullScore, 0.01); | |
| } | |
| } | |
| void testEvaluate() { | |
| FFState *nextState; | |
| FFState *prevState = const_cast< FFState * >(backwardLM->EmptyHypothesisState( *dummyInput )); | |
| double p_most = -2.360783; | |
| double p_for = -1.661813; | |
| double p_licenses = -2.360783; | |
| double p_the = -1.383059; | |
| double p_eos = -1.457693; | |
| double p_most_for = -0.4526253; | |
| double p_for_licenses = -1.661557; | |
| double p_licenses_the = -0.9625873; | |
| double p_the_eos = -1.940311; | |
| // the | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "the", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 1 ); | |
| float score; | |
| nextState = backwardLM->Evaluate(phrase, prevState, score); | |
| // p(the) * p(</s> | the) / p(</s>) | |
| SLOPPY_CHECK_CLOSE( (p_the + p_the_eos - p_eos), score, 0.01); | |
| delete prevState; | |
| prevState = nextState; | |
| } | |
| // the licenses | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "licenses", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 1 ); | |
| float score; | |
| nextState = backwardLM->Evaluate(phrase, prevState, score); | |
| // p(licenses) * p(licenses | the) / p(the) | |
| SLOPPY_CHECK_CLOSE( (p_licenses + p_licenses_the - p_the), score, 0.01); | |
| delete prevState; | |
| prevState = nextState; | |
| } | |
| // the licenses for | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "for", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 1 ); | |
| float score; | |
| nextState = backwardLM->Evaluate(phrase, prevState, score); | |
| // p(for) * p(for | licenses) / p(licenses) | |
| SLOPPY_CHECK_CLOSE( (p_for + p_for_licenses - p_licenses), score, 0.01); | |
| delete prevState; | |
| prevState = nextState; | |
| } | |
| // the licenses for most | |
| { | |
| Phrase phrase; | |
| BOOST_CHECK( phrase.GetSize() == 0 ); | |
| std::vector<FactorType> outputFactorOrder; | |
| outputFactorOrder.push_back(0); | |
| phrase.CreateFromString( | |
| Input, | |
| outputFactorOrder, | |
| "most", | |
| NULL); | |
| BOOST_CHECK( phrase.GetSize() == 1 ); | |
| float score; | |
| nextState = backwardLM->Evaluate(phrase, prevState, score); | |
| // p(most) * p(most | for) / p(for) | |
| SLOPPY_CHECK_CLOSE( (p_most + p_most_for - p_for), score, 0.01); | |
| delete prevState; | |
| prevState = nextState; | |
| } | |
| delete prevState; | |
| } | |
| private: | |
| const Sentence *dummyInput; | |
| BackwardLanguageModel<lm::ngram::ProbingModel> *backwardLM; | |
| }; | |
| } | |
| 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) | |
| { | |
| BackwardLanguageModelTest test; | |
| test.testEmptyHypothesis(); | |
| test.testCalcScore(); | |
| test.testEvaluate(); | |
| } | |