void execute(xmlrpc_c::paramList const& paramList, xmlrpc_c::value * const retvalP) { #ifdef WITH_DLIB const params_t params = paramList.getStruct(0); params_t::const_iterator si = params.find("model_name"); if (si == params.end()) { throw xmlrpc_c::fault( "Missing name of model to be optimized (e.g. PhraseDictionaryMultiModelCounts0)", xmlrpc_c::fault::CODE_PARSE); } const string model_name = xmlrpc_c::value_string(si->second); PhraseDictionaryMultiModel* pdmm = (PhraseDictionaryMultiModel*) FindPhraseDictionary(model_name); si = params.find("phrase_pairs"); if (si == params.end()) { throw xmlrpc_c::fault( "Missing list of phrase pairs", xmlrpc_c::fault::CODE_PARSE); } vector<pair<string, string> > phrase_pairs; xmlrpc_c::value_array phrase_pairs_array = xmlrpc_c::value_array(si->second); vector<xmlrpc_c::value> phrasePairValueVector(phrase_pairs_array.vectorValueValue()); for (size_t i=0; i < phrasePairValueVector.size(); i++) { xmlrpc_c::value_array phrasePairArray = xmlrpc_c::value_array(phrasePairValueVector[i]); vector<xmlrpc_c::value> phrasePair(phrasePairArray.vectorValueValue()); string L1 = xmlrpc_c::value_string(phrasePair[0]); string L2 = xmlrpc_c::value_string(phrasePair[1]); phrase_pairs.push_back(make_pair(L1,L2)); } vector<float> weight_vector; weight_vector = pdmm->MinimizePerplexity(phrase_pairs); vector<xmlrpc_c::value> weight_vector_ret; for (size_t i=0; i < weight_vector.size(); i++) { weight_vector_ret.push_back(xmlrpc_c::value_double(weight_vector[i])); } *retvalP = xmlrpc_c::value_array(weight_vector_ret); #else string errmsg = "Error: Perplexity minimization requires dlib (compilation option --with-dlib)"; cerr << errmsg << endl; *retvalP = xmlrpc_c::value_string(errmsg); #endif }
void breakOutParams(const params_t& params) { params_t::const_iterator si = params.find("source"); if(si == params.end()) throw xmlrpc_c::fault("Missing source sentence", xmlrpc_c::fault::CODE_PARSE); source_ = xmlrpc_c::value_string(si->second); cerr << "source = " << source_ << endl; si = params.find("target"); if(si == params.end()) throw xmlrpc_c::fault("Missing target sentence", xmlrpc_c::fault::CODE_PARSE); target_ = xmlrpc_c::value_string(si->second); cerr << "target = " << target_ << endl; si = params.find("alignment"); if(si == params.end()) throw xmlrpc_c::fault("Missing alignment", xmlrpc_c::fault::CODE_PARSE); alignment_ = xmlrpc_c::value_string(si->second); cerr << "alignment = " << alignment_ << endl; si = params.find("bounded"); bounded_ = (si != params.end()); si = params.find("updateORLM"); add2ORLM_ = (si != params.end()); }
void execute(xmlrpc_c::paramList const& paramList, xmlrpc_c::value * const retvalP) { const params_t params = paramList.getStruct(0); paramList.verifyEnd(1); params_t::const_iterator si = params.find("text"); if (si == params.end()) { throw xmlrpc_c::fault( "Missing source text", xmlrpc_c::fault::CODE_PARSE); } const string source( (xmlrpc_c::value_string(si->second))); cerr << "Input: " << source << endl; si = params.find("align"); bool addAlignInfo = (si != params.end()); si = params.find("sg"); bool addGraphInfo = (si != params.end()); si = params.find("topt"); bool addTopts = (si != params.end()); si = params.find("report-all-factors"); bool reportAllFactors = (si != params.end()); si = params.find("nbest"); int nbest_size = (si == params.end()) ? 0 : int(xmlrpc_c::value_int(si->second)); si = params.find("nbest-distinct"); bool nbest_distinct = (si != params.end()); vector<float> multiModelWeights; si = params.find("lambda"); if (si != params.end()) { xmlrpc_c::value_array multiModelArray = xmlrpc_c::value_array(si->second); vector<xmlrpc_c::value> multiModelValueVector(multiModelArray.vectorValueValue()); for (size_t i=0; i < multiModelValueVector.size(); i++) { multiModelWeights.push_back(xmlrpc_c::value_double(multiModelValueVector[i])); } } const StaticData &staticData = StaticData::Instance(); if (addGraphInfo) { (const_cast<StaticData&>(staticData)).SetOutputSearchGraph(true); } if (multiModelWeights.size() > 0) { PhraseDictionaryMultiModel* pdmm = (PhraseDictionaryMultiModel*) staticData.GetPhraseDictionaries()[0]; //TODO: only works if multimodel is first phrase table pdmm->SetTemporaryMultiModelWeightsVector(multiModelWeights); } stringstream out, graphInfo, transCollOpts; map<string, xmlrpc_c::value> retData; if (staticData.IsChart()) { TreeInput tinput; const vector<FactorType> &inputFactorOrder = staticData.GetInputFactorOrder(); stringstream in(source + "\n"); tinput.Read(in,inputFactorOrder); ChartManager manager(tinput); manager.ProcessSentence(); const ChartHypothesis *hypo = manager.GetBestHypothesis(); outputChartHypo(out,hypo); } else { Sentence sentence; const vector<FactorType> &inputFactorOrder = staticData.GetInputFactorOrder(); stringstream in(source + "\n"); sentence.Read(in,inputFactorOrder); size_t lineNumber = 0; // TODO: Include sentence request number here? Manager manager(lineNumber, sentence, staticData.GetSearchAlgorithm()); manager.ProcessSentence(); const Hypothesis* hypo = manager.GetBestHypothesis(); vector<xmlrpc_c::value> alignInfo; outputHypo(out,hypo,addAlignInfo,alignInfo,reportAllFactors); if (addAlignInfo) { retData.insert(pair<string, xmlrpc_c::value>("align", xmlrpc_c::value_array(alignInfo))); } if(addGraphInfo) { insertGraphInfo(manager,retData); (const_cast<StaticData&>(staticData)).SetOutputSearchGraph(false); } if (addTopts) { insertTranslationOptions(manager,retData); } if (nbest_size>0) { outputNBest(manager, retData, nbest_size, nbest_distinct, reportAllFactors); } } pair<string, xmlrpc_c::value> text("text", xmlrpc_c::value_string(out.str())); retData.insert(text); cerr << "Output: " << out.str() << endl; *retvalP = xmlrpc_c::value_struct(retData); }