Sha256: 893f12dc5cee2e5851cd33cd7b2cee1bc8c02259baa80451efdf7e1643b243ab
Contents?: true
Size: 1.78 KB
Versions: 9
Compression:
Stored size: 1.78 KB
Contents
#pragma once
#include "DMR.h"
namespace tomoto
{
template<TermWeight _tw>
struct DocumentGDMR : public DocumentDMR<_tw>
{
using BaseDocument = DocumentDMR<_tw>;
using DocumentDMR<_tw>::DocumentDMR;
std::vector<Float> metadataOrg, metadataNormalized;
RawDoc::MiscType makeMisc(const ITopicModel* tm) const override
{
RawDoc::MiscType ret = DocumentDMR<_tw>::makeMisc(tm);
ret["numeric_metadata"] = metadataOrg;
return ret;
}
DEFINE_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 0, metadataOrg);
DEFINE_TAGGED_SERIALIZER_AFTER_BASE_WITH_VERSION(BaseDocument, 1, 0x00010001, metadataOrg, metadataNormalized);
};
struct GDMRArgs : public DMRArgs
{
std::vector<uint64_t> degrees;
Float sigma0 = 3.0;
Float orderDecay = 0;
};
class IGDMRModel : public IDMRModel
{
public:
using DefaultDocType = DocumentDMR<TermWeight::one>;
static IGDMRModel* create(TermWeight _weight, const GDMRArgs& args,
bool scalarRng = false);
virtual Float getSigma0() const = 0;
virtual Float getOrderDecay() const = 0;
virtual void setSigma0(Float) = 0;
virtual const std::vector<uint64_t>& getFs() const = 0;
virtual std::vector<Float> getLambdaByTopic(Tid tid) const = 0;
virtual std::vector<Float> getTDF(
const Float* metadata,
const std::string& metadataCat,
const std::vector<std::string>& multiMetadataCat,
bool normalize
) const = 0;
virtual std::vector<Float> getTDFBatch(
const Float* metadata,
const std::string& metadataCat,
const std::vector<std::string>& multiMetadataCat,
size_t stride,
size_t cnt,
bool normalize
) const = 0;
virtual void setMdRange(const std::vector<Float>& vMin, const std::vector<Float>& vMax) = 0;
virtual void getMdRange(std::vector<Float>& vMin, std::vector<Float>& vMax) const = 0;
};
}
Version data entries
9 entries across 9 versions & 1 rubygems