本文整理汇总了C++中FVector::inner_product方法的典型用法代码示例。如果您正苦于以下问题：C++ FVector::inner_product方法的具体用法？C++ FVector::inner_product怎么用？C++ FVector::inner_product使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类FVector的用法示例。
在下文中一共展示了FVector::inner_product方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: inner_product
FValue inner_product(const FVector& lhs, const FVector& rhs)
{
if (lhs.size() >= rhs.size()) {
return rhs.inner_product(lhs);
} else {
return lhs.inner_product(rhs);
}
}示例2: OutputSparseFeatureScores
void IOWrapper::OutputSparseFeatureScores( std::ostream& out, const ChartTrellisPath &path, const FeatureFunction *ff, std::string &lastName )
{
const StaticData &staticData = StaticData::Instance();
bool labeledOutput = staticData.IsLabeledNBestList();
const FVector scores = path.GetScoreBreakdown().GetVectorForProducer( ff );
// report weighted aggregate
if (! ff->GetSparseFeatureReporting()) {
const FVector &weights = staticData.GetAllWeights().GetScoresVector();
if (labeledOutput && !boost::contains(ff->GetScoreProducerDescription(), ":"))
out << " " << ff->GetScoreProducerWeightShortName() << ":";
out << " " << scores.inner_product(weights);
}
// report each feature
else {
for(FVector::FNVmap::const_iterator i = scores.cbegin(); i != scores.cend(); i++) {
if (i->second != 0) { // do not report zero-valued features
if (labeledOutput)
out << " " << i->first << ":";
out << " " << i->second;
}
}
}
}示例3: OutputFeatureScores
void OutputFeatureScores( std::ostream& out, const TrellisPath &path, const FeatureFunction *ff, std::string &lastName )
{
const StaticData &staticData = StaticData::Instance();
bool labeledOutput = staticData.IsLabeledNBestList();
// regular features (not sparse)
if (ff->GetNumScoreComponents() != ScoreProducer::unlimited) {
if( labeledOutput && lastName != ff->GetScoreProducerWeightShortName() ) {
lastName = ff->GetScoreProducerWeightShortName();
out << " " << lastName << ":";
}
vector<float> scores = path.GetScoreBreakdown().GetScoresForProducer( ff );
for (size_t j = 0; j<scores.size(); ++j) {
out << " " << scores[j];
}
}
// sparse features
else {
const FVector scores = path.GetScoreBreakdown().GetVectorForProducer( ff );
// report weighted aggregate
if (! ff->GetSparseFeatureReporting()) {
const FVector &weights = staticData.GetAllWeights().GetScoresVector();
if (labeledOutput && !boost::contains(ff->GetScoreProducerDescription(), ":"))
out << " " << ff->GetScoreProducerWeightShortName() << ":";
out << " " << scores.inner_product(weights);
}
// report each feature
else {
for(FVector::FNVmap::const_iterator i = scores.cbegin(); i != scores.cend(); i++)
out << " " << i->first << ": " << i->second;
/* if (i->second != 0) { // do not report zero-valued features
float weight = staticData.GetSparseWeight(i->first);
if (weight != 0)
out << " " << i->first << "=" << weight;
}*/
}
}
}