#include <IndexHNSW.h>

Inheritance diagram for faiss::IndexHNSW:

Public Types
typedef HNSW::storage_idx_t	storage_idx_t

Public Types inherited from faiss::Index
using	idx_t = long
	all indices are this type

using	component_t = float

using	distance_t = float

Public Member Functions
	IndexHNSW (int d=0, int M=32)

	IndexHNSW (Index *storage, int M=32)

virtual DistanceComputer *	get_distance_computer () const =0

void	add (idx_t n, const float *x) override

void	train (idx_t n, const float *x) override
	Trains the storage if needed.

void	search (idx_t n, const float x, idx_t k, float distances, idx_t *labels) const override
	entry point for search

void	reconstruct (idx_t key, float *recons) const override

void	reset () override
	removes all elements from the database.

void	shrink_level_0_neighbors (int size)

void	search_level_0 (idx_t n, const float x, idx_t k, const storage_idx_t nearest, const float nearest_d, float distances, idx_t *labels, int nprobe=1, int search_type=1) const

void	init_level_0_from_knngraph (int k, const float D, const idx_t I)
	alternative graph building

void	init_level_0_from_entry_points (int npt, const storage_idx_t points, const storage_idx_t nearests)
	alternative graph building

void	reorder_links ()

void	link_singletons ()

Public Member Functions inherited from faiss::Index
	Index (idx_t d=0, MetricType metric=METRIC_L2)

virtual void	add_with_ids (idx_t n, const float x, const long xids)

virtual void	range_search (idx_t n, const float x, float radius, RangeSearchResult result) const

void	assign (idx_t n, const float x, idx_t labels, idx_t k=1)

virtual long	remove_ids (const IDSelector &sel)

virtual void	reconstruct_n (idx_t i0, idx_t ni, float *recons) const

virtual void	search_and_reconstruct (idx_t n, const float x, idx_t k, float distances, idx_t labels, float recons) const

void	compute_residual (const float x, float residual, idx_t key) const

void	display () const

Public Attributes
HNSW	hnsw

bool	own_fields

Index *	storage

ReconstructFromNeighbors *	reconstruct_from_neighbors

Public Attributes inherited from faiss::Index
int	d
	vector dimension

idx_t	ntotal
	total nb of indexed vectors

bool	verbose
	verbosity level

bool	is_trained
	set if the Index does not require training, or if training is done already

MetricType	metric_type
	type of metric this index uses for search

Detailed Description

The HNSW index is a normal random-access index with a HNSW link structure built on top

Definition at line 69 of file IndexHNSW.h.

Member Function Documentation

void faiss::IndexHNSW::add	(	idx_t	n,
		const float *	x
	)

overridevirtual

Add n vectors of dimension d to the index.

Vectors are implicitly assigned labels ntotal .. ntotal + n - 1 This function slices the input vectors in chuncks smaller than blocksize_add and calls add_core.

Parameters

x	input matrix, size n * d

Implements faiss::Index.

Definition at line 294 of file IndexHNSW.cpp.

void faiss::IndexHNSW::reconstruct	(	idx_t	key,
		float *	recons
	)		const

overridevirtual

Reconstruct a stored vector (or an approximation if lossy coding)

this function may not be defined for some indexes

Parameters

key	id of the vector to reconstruct
recons	reconstucted vector (size d)

Reimplemented from faiss::Index.

Definition at line 312 of file IndexHNSW.cpp.

void faiss::IndexHNSW::search_level_0	(	idx_t	n,
		const float *	x,
		idx_t	k,
		const storage_idx_t *	nearest,
		const float *	nearest_d,
		float *	distances,
		idx_t *	labels,
		int	nprobe = `1`,
		int	search_type = `1`
	)		const

Perform search only on level 0, given the starting points for each vertex.

Parameters

search_type 1:perform one search per nprobe, 2: enqueue all entry points

Definition at line 355 of file IndexHNSW.cpp.

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

/data/users/hoss/faiss/IndexHNSW.h
/data/users/hoss/faiss/IndexHNSW.cpp

Public Types

Public Member Functions

Public Attributes

Detailed Description

Member Function Documentation