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);
}
