sh::KeywordRanker Class Reference

#include <keyword-ranker.h>

Inheritance diagram for sh::KeywordRanker:

Collaboration diagram for sh::KeywordRanker:

Public Member Functions
	KeywordRanker (const Settings &config, const DatasetFrames &_dataset_frames)
	KeywordRanker (const KeywordRanker &)=delete
KeywordRanker &	operator= (const KeywordRanker &)=delete
	KeywordRanker (KeywordRanker &&)=default
KeywordRanker &	operator= (KeywordRanker &&)=default
	~KeywordRanker () noexcept=default
StdVector< float >	embedd_text_queries (const StdVector< KeywordId > &kws) const
const Keyword &	operator[] (KeywordId idx) const
	Gets all string representants of this keyword. More...
KwSearchIds	find (const std::string &search, size_t num_limit) const
void	rank_sentence_query (const std::string &sentence_query_raw, ScoreModel &model, const PrimaryFrameFeatures &_dataset_features, size_t temporal) const
StdVector< float >	get_text_query_feature (const std::string &query)
std::vector< std::string >	tokenize_textual_query (const std::string &sentence_query_raw) const
std::vector< KeywordId >	decode_keywords (const std::vector< std::string > &query) const
Public Member Functions inherited from sh::EmbeddingRanker< PrimaryFrameFeatures >
virtual	~EmbeddingRanker () noexcept

Static Public Member Functions
static std::vector< Keyword >	parse_kw_classes_text_file (const std::string &filepath, const DatasetFrames &_dataset_frames)
static FeatureMatrix	parse_float_matrix (const std::string &filepath, size_t row_dim, size_t begin_offset=0)
	Parses float matrix from a binary file that is written in row-major format and starts at begin_offset offset.k FORMAT: Matrix of 4B floats, row - major: More...
static FeatureVector	parse_float_vector (const std::string &filepath, size_t dim, size_t begin_offset=0)
	FORMAT: Matrix of 4B floats: More...
static void	report_results (const StdVector< std::pair< FrameId, float >> &sorted_results, const DatasetFrames &_dataset_frames, size_t num=10)

Private Attributes
std::vector< Keyword >	_keyword_ranker
FeatureMatrix	kw_features
FeatureVector	kw_features_bias_vec
FeatureMatrix	kw_pca_mat
FeatureVector	kw_pca_mean_vec

Additional Inherited Members
Protected Member Functions inherited from sh::EmbeddingRanker< PrimaryFrameFeatures >
std::vector< float >	inverse_score_vector (const std::vector< float > &query_vecs, const PrimaryFrameFeatures &_features) const
std::vector< float >	inverse_score_vector (const float *query_vecs, const PrimaryFrameFeatures &_features) const

Constructor & Destructor Documentation

KeywordRanker() [1/3]

sh::KeywordRanker::KeywordRanker ( const Settings &  config, const DatasetFrames &  _dataset_frames  )

inline

KeywordRanker() [2/3]

sh::KeywordRanker::KeywordRanker ( const KeywordRanker &  )

delete

KeywordRanker() [3/3]

sh::KeywordRanker::KeywordRanker ( KeywordRanker &&  )

default

~KeywordRanker()

sh::KeywordRanker::~KeywordRanker ( )

defaultnoexcept

Member Function Documentation

decode_keywords()

std::vector< KeywordId > KeywordRanker::decode_keywords

(

const std::vector< std::string > &

query

)

const

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embedd_text_queries()

StdVector< float > KeywordRanker::embedd_text_queries

(

const StdVector< KeywordId > &

kws

)

const

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find()

KwSearchIds KeywordRanker::find	(	const std::string &	search,
		size_t	num_limit
	)		const

get_text_query_feature()

StdVector< float > KeywordRanker::get_text_query_feature

(

const std::string &

query

)

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operator=() [1/2]

KeywordRanker& sh::KeywordRanker::operator= ( const KeywordRanker &  )

delete

operator=() [2/2]

KeywordRanker& sh::KeywordRanker::operator= ( KeywordRanker &&  )

default

operator[]()

const Keyword& sh::KeywordRanker::operator[] ( KeywordId  idx ) const

inline

Gets all string representants of this keyword.

parse_float_matrix()

FeatureMatrix KeywordRanker::parse_float_matrix ( const std::string &  filepath, size_t  row_dim, size_t  begin_offset = 0  )

static

Parses float matrix from a binary file that is written in row-major format and starts at begin_offset offset.k FORMAT: Matrix of 4B floats, row - major:

• each line is dim_N * 4B floats
• number of lines is number of selected frames

parse_float_vector()

FeatureVector KeywordRanker::parse_float_vector ( const std::string &  filepath, size_t  dim, size_t  begin_offset = 0  )

static

FORMAT: Matrix of 4B floats:

• each line is dim * 4B floats
• number of lines is number of selected frames

parse_kw_classes_text_file()

std::vector< Keyword > KeywordRanker::parse_kw_classes_text_file ( const std::string &  filepath, const DatasetFrames &  _dataset_frames  )

static

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rank_sentence_query()

void KeywordRanker::rank_sentence_query	(	const std::string &	sentence_query_raw,
		ScoreModel &	model,
		const PrimaryFrameFeatures &	_dataset_features,
		size_t	temporal
	)		const

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report_results()

void KeywordRanker::report_results ( const StdVector< std::pair< FrameId, float >> &  sorted_results, const DatasetFrames &  _dataset_frames, size_t  num = 10  )

static

tokenize_textual_query()

std::vector< std::string > KeywordRanker::tokenize_textual_query

(

const std::string &

sentence_query_raw

)

const

Member Data Documentation

_keyword_ranker

std::vector<Keyword> sh::KeywordRanker::_keyword_ranker

private

kw_features

FeatureMatrix sh::KeywordRanker::kw_features

private

kw_features_bias_vec

FeatureVector sh::KeywordRanker::kw_features_bias_vec

private

kw_pca_mat

FeatureMatrix sh::KeywordRanker::kw_pca_mat

private

kw_pca_mean_vec

FeatureVector sh::KeywordRanker::kw_pca_mean_vec

private

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The documentation for this class was generated from the following files:

• src/somhunter/rankers/keyword-ranker.h
• src/somhunter/rankers/keyword-ranker.cpp